Special Issue on Multidisciplinary Sciences and Engineering 2019-20

This study involved three departments of teachers and students. The concept of the flow-motivated exercise implemented with a set of flow nozzles. A computer-controlled airflow with specific music introduced, and the motion responses from the participants were analyzed during the initial test and field study. During the initial examination, we adjusted the magnitude and distance setting of the flow and allowed the children to grab the air without music. Structural design, magnetic valve, and interface were implemented based on the insights from the initial test. The redesign performed in a sitting position to reduce the need for students to deviate from the location and fit for physical disabilities during exercise. Four times of visually impaired students were arranged to observe the changes in the movements of students after being guided by the airflow during the teaching process. The performance of the fourth week is better than the previous three weeks. Almost all blind children can make movements in the right position. The cross-domain cooperation experience was beneficial to the facility design.

In this work, kaolin powder was filled in PP/LDPE blend as the filler with the amount from 0 to 14 wt%. The ratio of PP/LDPE was fixed as 50/50 in all the experiments. The tensile strength, impact strength, and hardness were investigated in according with ASTM. The results showed that the tensile strength of PP/LDPE blend was slightly increased, the hardness was also increased while the impact strength was decreased in the presence of kaolin powder as the filler from 0 to 14 wt.%.

Trade credit is an important cost reduction tool in the inventory management. The effect of trade credit is studied on the integrated system for sharing the cost benefits realized due to the permissible delay. Credit term factor is introduced to divide the cost benefits between the retailer and the supplier. The various costs in the inventory model are subjected to the same inflation rate. This research paper revisits EOQ model for remanufacturing process under green supply chain with the permissible delay available to the retailer. Numerical examples prove that the optimal re-ordering schedule exists and is unique. Also sensitivity analysis is performed on certain parameters to ascertain their logical implications.

Plants are living organisms that can hear and recognize the environment around them but cannot communicate to inform their needs. Thus, in the past, humans thought that it was impossible to communicate with plants. However, in this modern era, humans can be able to communicate with these plants. In this paper, we propose a model that can interact (Chat) with plants cultivated in the automated farm system based on Internet of Things (IoT) and Fuzzy Logic. According to the communication of plants and humans, we apply a chatbot algorithm for sending/receiving messages between users and automated smart farming. The messages are processed by the natural language processing (NLP) to parse and interpret the meaning of the conversation. The experimented plant in this paper is orchid, namely Dendrobium Sonia (Bomjo). The result from the evaluation shows that the average accuracy (Harmonic mean) of een the user and the orchid is equal to 0.71, the precision and recall 0.75 and 0.6 respectively.

This paper is an extension of research work originally presented in 2018 IEEE fifth International Congress on Information Science and Technology (CiSt). The research consists on developing method to diagnose electrical defects affecting wind turbine doubly-fed induction generator DFIG which constitutes a crucial part of wind energy conversion chain. First off all, we create a model of a non-defected wind conversion system based on mathematical equations introduced in Matlab Simulink. Then, we apply an indirect vector control stator field orientation in order to increase wind energy performance. With the aim of diagnosing the defects attacking wind turbine generator, we propose a method based on grouping of fast Fourier transform spectral analysis and Lissajous curves performed to generator stator and rotor currents. This diagnosis technique is applied to wind turbine in normal operation (non-defected generator) in order to have a reliable reference data for asynchronous generator behaviour. However, connected to the grid, wind turbine generator is affected by various faults occurring in electrical power networks. Therefore, the diagnosis method is applied also to a defected generator. Considering diversity of grid defects, we deal in the current paper with open stator supplying phases and open rotor feeding phases due to rotor side converter legs opening. Indeed, this diagnosis method allows diagnosing generator defects type and severity by comparing the resulting frequency spectrum analysis and Lissajous curves under abnormal condition operating to reference data obtained in case of non-defected generator. So, our proposed method contributes to DFIG defects identification and anticipation.
The simulations had been accomplished using Matlab Simulink. These results proved the efficiency and effectiveness of the proposed DFIG diagnosis method for wind energy conversion chain.

Anaphora resolution is one of the old problems in Natural Language Processing. It is the process of identifying the antecedent of an anaphoric expression in a natural language text. Most of the NLP applications such as text summarization, question answering, information extraction, machine translation etc. require the successful resolution of anaphors. In this paper, we propose a methodology for the resolution of pronominal anaphors present in Malayalam text document. The proposed methodology is a hybrid architecture employing machine learning and rule-based techniques. In our study, we have used a deep level tagger developed using a machine learning based algorithm. The deep level tagger provides detailed information regarding the number and gender of nouns in a text document. The morphological features of the language are effectively utilized for the computational analysis of Malayalam text. Despite using less amount of linguistic features, our system provides better results which can be utilized for higher level NLP tasks such as question answering,text summarization, machine translation, etc.

This paper proposed a frequency bandwidth required for the Control and Non-Payload Communications (CNPC) in autonomous operations of the Maritime Autonomous Surface Ship (MASS). The issue was to seek a radio spectrum to meet future demand for safe operations of autonomous ship at sea. As described in Document 5B/841 of ITU-R SG, safe navigation of autonomous ships relies on communications for command and control. Based on the operations required for the safe navigation of the MASS, the total bit rates were calculated. The spectrum requirements were obtained for command and control communications in operating the MASS safely. As a result, in terms of bandwidth, transmit rate, and transmit distance, state of the art satellite communication system was suitable for a safe operation of the MASS.

In this research work, we proposed a technique to decrease the complexity of 2-D Matrix Pencil (MP) for the direction of arrival (DOA) evaluation by combining two perpendicular arrays: The first one is the uniform linear array (ULA) and the second one is a uniform circular array (UCA). This special structure for the 2D Matrix Pencil pipe to a powerful methodology for real-time implementation on a digital signal processor, while the MP used to correlated and uncorrelated sources with the presence of a white noise. The obtained results show that proposed MP method gives better results at the level of the precision and the estimation of the DOA compared to the published measure.

Panjang Island is one of the islands which is categorized as a small island and is located in Jepara District, Jepara Regency, Central Java Province. The problem faced by Panjang Island is erosion, which increasingly erodes the shoreline and begins to damage buildings on the beach. A solution that is effective enough to overcome erosion or changes in the coastline is to build coastal shelters to reduce wave energy and increase sediment supply. The purpose of this study is to study the exact location of the submerged breakwater from aspects of wave parameters. The method used is wave forecasting and numerical wave model scenarios for submerged breakwater structures. The results showed wave height forecasting results in the western season (December, January, and February) is 2.66 meters, in the first transition season (March, April, May) is 2.14 meters, at east season (September, October, December) 1.45 meters, in the second transition season (June, July, August) is 2.26 meters. The model simulation results with a scenario based on the plan show the most effective damping in the east season with a reduction of 52.26%.

In Big Data, several solution providers offer distributions to handle this large amount of data. Given the variety of these solutions, we are working to provide universal meta-modeling for all layers of a Big Data system in order to address the issue of interoperability and portability between these solutions. As part of our continuous efforts to standardize concepts in Big Data world, we apply in this paper techniques related to Model-Driven Engineering “MDE” to propose a meta-model for the security layer in Big Data. This meta-model with the others that we have already proposed for the other layers of the Big Data system, will be used as a platform-independent according to Model-Driven Architecture pattern, which describes the structures of Big Data layers independently of any specific platform.

The IEEE802.11n based Wireless Local Area Networks (WLANs) have been extensively deployed due to the flexible coverage, the easy installation, and the lower cost. To reduce the energy consumption while increasing the performance, the elastic WLAN system has been studied, such that it can dynamically change the network configuration according to traffic demands. As well, the test-bed has been implemented and for the access point (AP), Raspberry Pi is used as a portable, energy conservation, and powerful computing device. Our test-bed measurements with a single AP of two concurrently communicating hosts found the unfairness throughput results, due to the TCP windows size became different among them. To overcome this drawback, in this paper, we propose the TCP fairness control method for two concurrently communicating hosts in the elastic WLAN system. By controlling the delay at the packet transmission, the slower host will obtain more transmission opportunities than a faster host. The delay is firstly calculated by the received signal strength (RSS) from every host. After that, the delay is controlled by the PI controller to balance the both throughputs. For evaluations, we execute the proposal in the elastic WLAN system test-bed and carry out extensive measurements, where the TCP throughput fairness is achieved.

In an enterprise Wifi network, indoor and dense, co-channel interference is a major issue. Wifi controllers help tackle this problem thanks to radio resource management (RRM). RRM is a fundamental building block of any controller functional architecture. One aim of RRM is to process the radio plan such as to maximize the overall network transmit opportunity. In this work, we present our dynamic RRM (dRRM), WLCx, solution in contrast to other research and vendors’ solutions. We build our solution model on a novel per-beam coverage representation approach. The idea of WLCx is to allow more control over the architecture design aspects and recommendations. This dynamization of RRM comes at a price in terms of time and resources consumption. To improve the scalability of our solution, we have introduced a Machine Learning (ML)-based optimization. Our ML-optimized dRRM solution, M-WLCx, achieves almost 79.77% time reduction in comparison with the basic WLCx solution.

Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of the shape of a head, was combined with soft-biometric traits such as the face wearing glasses, face wearing a cap/headgear, face with facial hairs, plain face, female face, and male face. These were experimented with, using images from Carl’s database and Terravic Facial Infrared Database, and used to train clusters of neural network algorithms for each biometric trait. These comprised Restricted Boltzmann Machines (RBM), Deep Belief Networks (DBN), and Feed Forward Neural Networks (FFNN). After feature extraction, using Fast Wavelet Transform (FWT), and Linear Discriminant Analysis (LDA). A classification error of 0.02887, 0.038695, 0.02381, 0.024629, 0.0268, 0.02369 and 0.03 was achieved for each biometric trait, respectively. Showing that they had each been learned, and could be used through a fusion method, to improve recognition. This was demonstrated using a test image, as the user, having four of the character traits (countenance, glasses, facial hair, and gender). Then attempting to recognize each trait, one after the other, using a cross-verification method. The algorithm was seen to return test values, close to those received during the training test, for each biometric trait.

The diversity of manuscripts according to their contents, forms, organizations and presentations provides a data-rich structures. The aim is to disseminate this cultural heritage in the images format to the general public via digital libraries. However, handwriting is an obstacle to text recognition algorithms in images, especially cursive writing of Arabic calligraphy. Most current search engines used by digital libraries are based on metadata and structured data manually transcribed in Ascii format. In this article, we propose an original method of pattern recognition for searching the content of Arabic handwritten documents based on the Word Spotting technique. Our method is both effective and simple, it consists in extracting a set of features from the words we segment in the target images and comparing them with the features of the words in the requested images. The principle of the method is to characterize each word with the Speeded Up Robust Features algorithm whose goal is to find all occurrences of query words in the target image even in the case of low-resolution images. We tested our method on hundreds of pages of Arabic manuscripts from the National Library of Rabat and the Digital Library of Leipzig University. The results obtained are encouraging compared to other methods based on the same Word Spotting technique.

Fatigue is broadly divided into two types depending on the content of a task: physical fatigue and mental fatigue. Mental fatigue is associated with human error. It is thus important to search for indicators that can easily evaluate mental fatigue. The aim of this study is to construct a system that can evaluate mental fatigue in a simple manner. To achieve this, we investigated the influence of the accuracy of linear discriminant analysis in two classes before and after the application of a mental load. In addition, we investigated whether the mental fatigue state can be estimated even when the number of trials for averaging is small, by combining the electroencephalogram power spectral density component and the P300 component. As a result, this combination of the power spectral density component with the P300 component resulted in measured waveforms that exhibited an accuracy of approximately 97%, even when the number of trials for averaging was as small as five trials.

This paper addresses the generation of stylized texts in a multilingual setup. A long short-term memory (LSTM) language model with extended phonetic and semantic embeddings is shown to capture poetic style when trained end-to-end without any expert knowledge. Phonetics seems to have a comparable contribution to the overall model performance as the information on the target author. The quality of the generated texts is estimated through bilingual evaluation understudy (BLEU), a new cross-entropy based metric, and a survey of human peers. When a style of target author is recognized by the humans, they do not seem to distinguish generated texts and originals.

Electrical energy shortage and expensive basic electricity costs are one of the problems that are occurred in Karimunjawa Island, Indonesia. The purpose of this research is to identify the potential of ocean currents energy as one of the alternatives to reduce the problem related to energy needs and to predict the electrical energy that can be obtained. The physical phenomena movement of ocean currents is made by using the 2-Dimensional hydrodynamic mathematical model. ADCP Multicell Argonaut-XR type is used to measure the speed of ocean currents to validate the model result. Tidal, wind, coordinate and bathymetry data are all the variables that are in the mathematical model of ocean current movement. The potential of electrical energy is determined by the value of power density which is calculated based on the speed ocean current model. The result of this research is the map of the potential distribution of ocean currents in Karimunjawa waters.

Fingerprint data is really protected by cancelable fingerprint template because it can be revoked when compromise and a new one can be reissued. We develop a touchless cancelable fingerprint template whose algorithm was published in our previous work. We implement here the algorithm and conducted several tests on several databases to confirm the stability of the model. To justify how specific keys are used, we used the Kolmogorv-Smirnov test (K-S) and the distribution histogram of legitimate / impostor scores. We compared two systems in which users register. This is the reason for the average value of K-S (0.7812) and similarity assessment (2.4703). These results improve sufficiently (6.1636 and 0.9934 for the successive separability and the K-S test) during the evaluation of the user keys through the second device. We have tested the diversity of curves that we generate. Our proposed non-contact revocable fingerprint model has demonstrated robustness against the security challenges that fingerprint authentication systems are exposed to. We evaluated it on our own database. The requirements of revocability, diversity and security are achieved with very good performance as evidenced by the FAR (False Acceptance rate) obtained on our database (0.0015).

Fingerprint data is really protected by cancelable fingerprint template because it can be revoked when compromise and a new one can be reissued. We develop a touchless cancelable fingerprint template whose algorithm was published in our previous work. We implement here the algorithm and conducted several tests on several databases to confirm the stability of the model. To justify how specific keys are used, we used the Kolmogorv-Smirnov test (K-S) and the distribution histogram of legitimate / impostor scores. We compared two systems in which users register. This is the reason for the average value of K-S (0.7812) and similarity assessment (2.4703). These results improve sufficiently (6.1636 and 0.9934 for the successive separability and the K-S test) during the evaluation of the user keys through the second device. We have tested the diversity of curves that we generate. Our proposed non-contact revocable fingerprint model has demonstrated robustness against the security challenges that fingerprint authentication systems are exposed to. We evaluated it on our own database. The requirements of revocability, diversity and security are achieved with very good performance as evidenced by the FAR (False Acceptance rate) obtained on our database (0.0015).

The technological advance as well as needs of human beings made that systems became more and more complex. In contrast, the use and creation of new modelling languages became simple and no more reserved for a handful of language experts. Consequently, many new practices of systems implementation emerged, among them, the use of different domain specific modelling languages (DSMLs) to represent the same system. Indeed, complex systems are composed by many components sometimes belonging to various domains. Thus, many teams of experts collaborate to develop such systems. Moreover, teams tend to use different DSMLs to design their concerns. This new practice generates an accidental heterogeneity due to production of various heterogeneous models representing a same system. However, those heterogeneous models need absolutely to be coordinated to facilitate communication between stakeholders and of course to ease implementation and validation of systems. This paper proposes a composition interface–based approach to coordinate and integrate heterogeneous DSMLs in order to coordinate their models. The proposed composition interface is defined according to Bridge Design Pattern. To illustrate this approach two DSMLs are used: An Indoor Service Transport Modelling Language and an Internet of Things Modelling Language.

As well as physical computing, unplugged activity is important in ICT (Information and Communication Technology) education, that uses information and communications technology to support, enhance, and optimize the delivery of information, and software education. In order to achieve educational objectives in unplugged activity, evaluation metrics of learners are necessary. However, there is little work on evaluation metrics in unplugged activity. In this paper, evaluation metrics of learners are proposed and developed using based on the general design principles and opinions of experts.

Software is the primary and indispensable entity in our technologically driven world. Therefore, quality assurance, and in particular software testing, represents a vital component in the software development cycle. Throughout the years, many tools have been developed to collect metrics of software that had been implemented. These tools have some differences but continue to play an important role in improving the quality of software products. This paper introduces a newly developed tool, named Spectra Complexity Metrics System (SCMS), which compiles a novel taxonomy of complexity metrics of any given software written in the Java programming language. Our suggested metrics have been invented to identify and evaluate the characteristics of Java computer programs. They aim at increasing the efficiency of the testing process by significantly reducing the number of test cases without having a significant drop in test effectiveness. We assess our proposed taxonomy of different complexity metrics based on the product levels (statement, method, and class) and their characteristics. For further evaluation, our software metrics coverage is compared to other existing software metric tools. The results show the novelty of our taxonomy of complexity metrics and the capability of our tool to compute these measurements based on all three of the product level categories. We have published our tool at https://github.com/issararab/SCMS under an open-source license.

This paper proposes a new classification model distinguishing four classes of attacks in Wireless Sensor Networks (WSNs) namely: attacks based on the protocol stack, on the capability of the attacker, on the attack impacts and on the attack target. Then, it presents and classifies the most known attacks in WSNs based the proposed model. Simulations implemented under the NS3 simulator prove that the network lifetime can decrease by more than 45% in the presence of attacks. Afterwards, it discusses the main security methods and protocols of management and distribution of encryption keys used to ward off different types of attacks. Obtained results confirm that these security methods must be adapted to the specific characteristics of WSNs to achieve the intended objectives.

In more recent times, researchers have turned their attention to link prediction and the role link inference can play in better understanding the evolutionary nature of social networking sites. The objective of this paper is to present an in-depth review, analysis, and discussion of the cutting-edge link prediction methods that can be applied to better understand the development of social networks. The findings of the literature review reveal that there has been a steady increase in the number of published articles that present novel link prediction models that are designed to enhance the efficiency and accuracy of link prediction. In this paper, this most recent techniques to be proposed in this regard are compared and categorized, and features and evaluation metrics are presented for each approach. The results of the evaluation reveal that there are no complete or definitive methods available that can accurately and reliably be applied within different dynamic social networks to predict missing, emerging, and broken links within the network. The paper concludes by presenting potential future directions and recommendations for further studies

Through the Electrical Discharge Machining, the temperature is very high, which can lead to the material phase’s transformation and affects material properties, which can lead to failure of the products in the industry. This study aims to investigate the effect of a new input parameter (pulse cycle time Tc), with other parameters on the EDM responses, prediction models are developed. 3D Laser Microscope is used to measure the surface defects. And to assess the effect of using a silver-tungsten electrode on improving EDM performance during machining of powdered metallurgical high-speed steel which is a very important material in the industry, such as aerospace, automotive, and electrical power industries, it is used in structural components and heat exchangers. An integrated approach combines Response surface design and Genetic Algorithm optimization methodology for modeling and optimizing the process responses is utilized. Two software’s Minitab software and Matlab software were used for this purpose. The experimental results demonstrated comparative findings when the silver-tungsten electrode was used, and the optimization percentage was increased when the Genetic Algorithms method was used. Optimized values of the responses were as following: Micro-crack size was 0.965 µm, the optimization percentage is 20.64%. Tool Wear Rate was 0.0020 g/min, the optimization percentage is 13.04 %.

Map of prediction of fishing ground that already exists in Indonesia issued by the Bali Marine Research and Observation Center (BPOL) and the National Aeronautics and Space Agency (LAPAN) of Jakarta, there are still many weaknesses including the spatial aspect of the point of forecasting far from the coast and the unclear type of fish predicted. The lack of understanding of the type of fish predicted, the risk of fishermen carrying the wrong fishing gear so that when reaching the forecasting location, fishermen can not catch fish that are abundant. The method of determining fishing ground for demersal fisheries is carried out in three stages, first step, environmental tabulation of demersal fisheries, the second stage of mapping corals area and its supporting parameters, the third stage of mapping the demersal fishing ground. The results of the study obtained several statements, namely demersal fishing ground can be made based on an understanding of childhood fish habitat, adulthood, substrate base habitat, an optimum depth of catchment area. Sentinel 2A satellite imagery can be used to help determine the fishing ground of demersal fish species, but for the coastal waters of Jepara Regency, there are still obstacles related to spatial resolution and water turbidity. Field data is still needed to help determine the demersal fishing ground. Based on the fishing ground mapping, there are four economical types of fishery resources that live in the coral reef environment, namely Lobster, Red Snappers, Blue Line Seabass and Leopard Coral Grouper. The demersal fishing ground associated with corals in the Coastal Jepara Regency Waters which is seven segments apparently only four segments have the potential to become demersal fishing ground associated with coral reefs, namely the second to fourth segments, including the coastal waters of Jepara, Mlonggo, Bangsri, and Kembang. District and the most potential is the coastal waters of the Mlonggo District.

Content Based Image Retrieval (CBIR) for remote sensing image data is a tedious process due to high resolution and complexity of image interpretation. Development of feature extraction technique is a major portion to represent the image content in an optimal way. In this paper, we propose a feature descriptor which combines the color coherent pixel information and GLCM texture features in multi scale domain. Curvelet transform is used to decompose the image into coarse and detail coefficients. Then Gabor magnitude is computed for each coefficient to improve the directional information. GLCM texture features are extracted from the Gabor magnitude response. The novel feature set by combining the CCV and GLCM using curvelet and Gabor filter is developed. Mahalanobis distance measure is used to find the similarity between query and feature database. Average Normalized Modified Retrieval Rate (ANMRR) is computed to evaluate the performance with the state of art methods.

A fuzzy system is a rule-based system that uses human experts’ knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters. To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). FA is a nature-inspired algorithm that uses fireflies’ behavior to interpret data. This study explains in detail how fuzzy modeling works by using FA for detecting phishing. Phishing is an unsettled security problem that occurs in the world of internet connected computers. In order to experiment with the proposed method for the security threats, a database of phishing websites and SMS from different sources were used. As a result, the average accuracy for the phishing websites dataset achieved 98.86%, while the average value for the SMS dataset is 97.49%. In conclusion, both datasets show the best result in terms of the accuracy value for fuzzy modeling by using FA.

Nowadays the collaboration of organizations, systems or services becomes more and more answered in practice. Indeed, organizations try to expand their service, other to satisfy the needs of their customers. Thus, the need to work collaboratively with other partners whether internally or externally becomes trivial. However, process modeling in a collaborative environment becomes heavy because of the diversity of information exchanged and the complexity of shared task. Certainly, the BPMN is the most answered standard for the modeling of business processes, moreover it offers a collaborative diagram that allows to model collaborative processes, but later we will see that its capabilities are very limited. For that, we try in this work to create a collaborative business process modeling language that allows to better model these types of processes and respects some aspects of a collaborative environment. We used the BPMN extension mechanism to create our own language that we named «BPMN4Collaboration».

The safety management system is recognized by safety leading and lagging indicators, and their correlation with injury rates. The background on this specific subject is vague in definition, labelling, and indicators measurement. The comparativeness between leading and lagging indicators have been introduced in the constructing safety performance projects evaluation. Safety performance leading indicators are the metrics of the safety method in constructing work. While the lagging indicators associated with safety results. Many suggestions have been considered during the usage and selection of the effective leading indicators. Also, the research results outlined that the leading indicators can be used to discriminate the variances in the safety performance of projects. In this specified research, leading and lagging indicators have been reviewed and investigated. Eighteen papers have been investigated from the period of 2010 to 2019 in order to recognize the common leading and lagging indicators. In addition, this review will recognize the gaps in leading and lagging research in order to concentrate on extra studies in that field. Four papers mentioned the correlation between lagging and leading indicators. A scoping review is focusing on the points and the significant ideas associated with the research area in accordance with the history time.

This research aimed at developing a method of glaze material making from used glass bottle waste combined with kaolin. Then, the microstructure and hardness level of glaze products were characterized. Furnace heaters were used in research to heat glaze material by varying the holding time of 30, 45 and 60 minutes. The composition of glaze material was varied with the ratio between glass and kaolin of 70:30, 80:20 and 90:10. The results revealed that the process of glaze material making was successfully carried out. The results of the hardness test showed that at the 30 minutes holding time, the hardness was 82.53 VHN. The hardness value increased when the holding time was 45 minutes with an average hardness value of 85.03 VHN. The highest average hardness obtained when the variation of 60 minutes holding time was 87.6 VHN. The difference in hardness value in variation possibly occurred because of the differences in the distribution of amorphous solids, porosity, and pinhole which was influenced by the differences in glass and kaolin composition.

This work implements a MIMO (Multiple Input Multiple Output) FO (Fractional Order) control system for controlling the level and temperature of the water inside a tank by means of two inflow rates: cold and hot water, which are mixed to produce an outflow rate. Such a process exhibits coupling between inputs and outputs. A linear model of the plant is obtained experimentally. Such a model, the transfer matrix function of the plant, is used to design a centralized MIMO IO (Integer Order) controller that permits to achieve complete decoupling between the set points of level and temperature and the corresponding controlled outputs: level and temperature in the tank. The MIMO FO controller is obtained making fractional all de transfer functions of the MIMO IO controller. Experimental results demonstrate that the MIMO FO control system improves the control performance of the plant outputs: level and temperature of the water in the tank.

In recent years, development of aerial autonomous systems and cameras have allowed increasing enormously the number of aerial images, and their applications in many research areas. One of the most common applications is the mosaicking of images to improve the analysis by getting representations of larger areas with high spatial resolution. This paper describes a simple method for mosaicking aerial images acquired by unmanned aerial vehicles during programmed flights. The images were acquired in two scenarios: a city and a forest in the Peruvian Amazon, for vegetation monitoring purposes. The proposed method is a modification of the automatic homography estimation method using the RANSAC algorithm. It is based on flight trajectory and the calculation of symmetric transfer error per inliers. This method was implemented in scientific language and the performance was compared with a commercial software with respect to two aspects: processing time and geolocation errors. We obtained similar results in both aspects with a simple method using images for natural resources monitoring. In the best case, the proposed method is 6 minutes 48 seconds faster than the compared software and, the root mean squared error of geolocation in X-axis and Y-axis obtained by proposed method are less than the obtained by the compared software in 0.5268 and 0.5598 meters respectively.

With increasing photovoltaic (PV) penetration on distribution feeders, voltage functions is always a challenge. To control these variations due to the intermittent nature of PV generation,many utility companies use the traditional voltage regulating devices such as ON/OFF load tap changers, voltage regulators, switched capacitor banks and reactors. The use of smart inverters (SI) has been reported to provide a more effective and economical way of voltage regulation on distribution feeder. It then becomes necessary to optimally control the operation of these traditional voltage regulating devices and the SIs. This paper presents a multi-objective technique that minimizes the voltage fluctuation (by implementing conservative voltage reduction), the overall system active power losses and the amount of reactive power injection from the capacitor banks with various constraints on the smart inverter reactive power injection and voltage regulator switching. The proposed algorithm is tested on an IEEE 34 node system with six units of 300kW (400kV A SIs) PVs integrated using real data from an existing 1.4MW PV plant located at FIU. The Pareto optimization results of the proposed algorithm show the various optimal values of the PVs power factor, the voltage regulator settings and the capacitor reactive power injection. Using one of the Pareto optimal solutions, the results show that the system bus voltage profiles, total system power losses and capacitor reactive power injection were e ized.

In this paper an offline motion-planning algorithm is presented for robotic manipulators. In this method to solve the path-planning task, the Transition-based Rapidly-exploring Random Tree (T-RRT) algorithm was applied, that requires a cost-function over the search space. The goal of this cost-function is to keep distance between the actual position and configurations that cause collisions. The paper presents two possible cost function generation methods. The first one is based on multidimensional Gauss functions and the second solution uses fuzzy function-approximation to determine the cost all over the configuration space. At last, the trajectory generator method will be introduced that calculates the desired shape of the function of joint variables and their derivatives. The algorithm is universal, the only restriction is that the manipulator and the environment are modelled by their bounding polyhedra. To demonstrate the presented approach, simulation were performed in MATLAB Simulink environment using the Mitsubishi RV-2F-Q robotic manipulator.

Orthogonal Frequency Division Multiplexing (OFDM) is a modulation format that has recently attracted lots of consideration interior the long-haul fiber-optic transmission community. The most important advantage of optical OOFDM is its unlimited capability of canceling Inter-Symbol Interference (ISI) caused by Chromatic Dispersion (CD) and Polarization-Mode Dispersion (PMD). Specifically, Coherent OOFDM (CO-OFDM) presents a good and effective modulation method in modern optical communication systems. However, due to its high Peak to Average Power Ratio (PAPR), the performance of CO-OFDM is affected by nonlinear impairments. In this paper, we propose a new joint nonlinear technique; L3-by-3; with a distortion technique; clip-ping; that bypass the requirement for the use of any side information (SI) to minimize the high PAPR value of the transmitted signal and consequently improve various fiber nonlinear impacts through PAPR reduction. The simulation results reveal dependable and excellent signal recapture at the receiver and an effectively minimized PAPR level at the sender side.

The basics of unconventional design of current circuits of two-valued and multi-valued memory elements (ME) for storing current digital signals and flip-flops of the main types on their basis are considered. A nontraditional method of ME synthesis is proposed, which is based on the mathematical tool of linear algebra. Linear equations, structural and functional schemes of the main types of logic elements for the construction of ME are given. CMOS-circuitry of various versions of realization of linear logic elements of multi-valued MEs is considered. The comparative analysis is carried out and advantages and disadvantages of linear realization of current two-valued memory elements and flip-flops on their basis in comparison with potential (Boolean) realization are defined. The forecast of merits and demerits of linear implementation of multi-valued memory elements is given

Lean ERP system is considered among the new trends of systems in the manufacturing sector, it has become one of the most widely adopted systems, thanks to its various benefits such as: a centralized database which gathers all the data of the enterprise in a single database which is accessible to all the departments, reduction in costs, high performance and best quality and many other advantages. However, many companies are starting the implementation of the hybrid Lean ERP system without prior study of the project. This may lead to its improper implementation which can impact negatively the enterprise and its stakeholders.
It is in this context that our study aims to help future companies wishing to implement the hybrid Lean ERP system, through identification, study and an analysis of critical success factors (CSFs) of Lean ERP necessary to this implementation, while focusing on different groups of stakeholders and their interactions with CSFs.

Stability or balance is an integral component to perform daily activities without incurring injury or to be dependent on others. Sportsmen tend to have better balance than non-sports people but less is known about the single-leg balance ability. Furthermore, few studies analyzed the dynamic phase of single-leg stance that may contribute to better overall balance. Sports like football tend to have instances where the player’s non-dominant leg keeps them in an upright position while the dominant leg kicks, passes and stops the ball. We aim to study the single-leg balance between collegiate footballers and sedentary students in eyes-closed (EC) and eyes-opened (EO) conditions and their contributing components to keep a body in an up-right position. Twenty collegiate footballers and 20 sedentary students conducted the unipedal stance test (UPST) on each leg with EO and EC conditions while standing on a force platform. We captured center of pressure (CoP) distance travelled, stance duration and using a 3D motion capture system, we assessed lower limb movement at six different anatomical sites. Results showed that footballers had better overall balance compared to sedentary students only in the non-dominant leg, EC condition with 12 footballers versus four sedentary students completing the full 45s stance (p=0.01) The other three UPST conditions did not show significant differences between groups. The CoP distance in the initial dynamic state and total UPST were both significantly shorter in footballers than sedentary students (p<0.05) during the non-dominant leg, EC stance. Our multivariable linear regression model significantly predicted time for UPST on non-dominant leg with EC up to 76.8% (p<0.001) with the first 5-s of greater trochanter movement significantly contributing to total time taken for UPST in footballers. Overall, playing football may enhance balance control intrinsically especially for the non-dominant side while being less reliant on visual input to maintain balance.

The greenhouse climate system is very hard to manipulate because the variables involved are closely correlated. This study aims to enhance the regulation performance of greenhouse climate system based on adaptive neural-fuzzy inference system (ANFIS). The ANFIS is a hybrid technique that incorporates the fuzzy logic theory and artificial neural network algorithms. The employed control system has the ability to stabilize the climatic variables inside greenhouse system at required levels for crops development. The datasets utilized to train ANFIS model was obtained by implementing a fuzzy logic controller under MATLAB Simulink environment. The feasibility, reliability and robustness of the adopted strategy have been experimentally studied. The experiments conducted in real-time show that the proposed technique provides good tracking, short response time and high robustness with regard to outside perturbations and non-linear behaviors of greenhouse systems.

VANET as a subclass of MANET is composed of a set of vehicles equipped with wireless transceivers, to build dynamic networks without the need of any pre-existing infrastructure. Over the last few decades, the area of routing protocols in VANETs has been extensively studied. Nevertheless, this area remains even more challenging due to some features of VANETs, such as the high speed of vehicles, the often-disconnected links and the particular mobility pattern. Routing protocols in VANETs could be splitted into four categories: topology, position, multicast and broadcast-based routing protocols. In this paper, we provide a novel detailed taxonomy of routing protocols in VANETs then we present the advantages and drawbacks of each category. Moreover, we clear up the techniques adopted by each of the most popular routing protocols based on the vehicles’ position and the topology of the networks. To explore the strengths and weaknesses of each routing protocols, basing on their suitability for VANET, we implemented them by using SUMO and NS3 as simulation tools applied on a real street map of Oujda city. We have extracted the used map from Open Street Map (OSM). Finally, we present our future works used for optimizing the greedy forwarding technique that is adopted by some position-based routing protocols in VANETs. Our suggested technique is based on the angle direction and three other important parameters of the relaying node.

This research aims to develop the methodology to assess effectiveness of distributed information systems (hereinafter IS). The effectiveness of information systems is reviewed along with their reliability. The article underlines the importance of reliability assessment for large geographically distributed systems. We suggest the approach based on the hierarchical presentation of reliability scheme that constitutes the core of the mathematical model for reliability of a distributed system. The key advantage of the suggested approach is its applicability on geographically distributed systems of different architecture. Successful testing during effectiveness and reliability assessment on 3 geographically distributed IS allows to suggest that the developed methodology is ready to be used in IS reliability assessment projects.

In our era, human and machine must share the same workspace in various plants such as warehouse logistics, material transportation, manufacturing factory or assisted human. The collaboration is essential to maintain the safe operation and the complete mission. In this paper, a design of anti-vibration scheme using Spline generator for grounded vehicle platform in human-machine interaction is introduced. This hardware structure is able to play a role as carrier in loading application or human assistant in real life. In most of cases, vehicle must convey cargo from start point to destination instead of human while its reference trajectory conflicts with human’s movement. The proposed algorithm helps to carry out a decision of stopping strategy with the least vibration as possible to avoid accident. From the test results, the proposed design is feasible and capable to apply in numerous industries.

Learning and mental and physical counselling for visually impaired children are important. However, due to the lack of visual sense assistance, Physical Activity will gradually degenerate without proper enhancement, which may require the care of others for life. Inner fear and sensitive psychological factors hinder the development of living ability. Strengthening physical activity of visually impaired children improves their ability and reduces psychological obstacles, which is conducive to getting along well with others. The distributed vibration developed in this study can enhance children’s physical exercise. Through music rhythm, children’s psychological resistance is reduced, and their body movements are triggered by distributed vibration, which has an impact on the physical activity of children with visual impairment.
Seven kindergarten-age children were selected to participate in a 16-week tutoring. A score was recorded based on the assessment form, teaching record, and interviews with parents or students. The results showed that vibration and music are helpful in developing a young child’s motor skills. After two sessions of tutoring, player became more interested in participating along with the music and tactile signals. Players were able to correctly identify the limbs that corresponded to the vibration and gesture with their hands and feet. Assistive technology had a positive effect on the physical activity of the visually impaired children.

Day by day, the data on the web becomes very huge which makes it difficult to find relevant information. Search engines are one of the successful factors that can retrieve information from the Web. The process of seeking information by search engines helps users find information on the internet, however it is not an easy task to find the exact information from this massive data available on the Web. Semantic Web technology has an ability to focus on metadata rather than syntax, which made the semantic search engines to search for the meaning of keywords instead of the keyword syntax. Consequently, an effective role of performance in conventional search engines can be achieved by rising the accuracy of information returned by a search query. In this paper, a survey for syntactic-based search engines and semantic-based search engines are studied, a comprehensive comparison between the two is presented, finally, their technologies are compared and discussed.

In times of crisis or traumatic transformation processes, one of the most frequent negative externalities is that the self-image of a city deteriorates among its stakeholders, which affects their economic and social expectations and decisions. The internalisation of this externality must be a key objective for the local public manager so that any initiative can be carried out with collective support and collaboration. When applied to this end, city marketing and the instruments that this technology makes available to city managers provide optimal results.

The currently available variety of modern, highly-parallel universal processors includes multi-core CPU and many-core GPU (Graphics Processing Units) from different vendors. Systems composed of such processors enable high-performance execution of demanding applications like numerical Finite Element Methods. However, today’s application pro- gramming for parallel systems lacks performance portability: the same program code cannot achieve stable high performance on different parallel architectures. One of the main reasons for this is that parallel programs are developed by utilizing system-specific profiling interfaces of the corresponding hardware vendors. We describe a novel, portable profiling interface: its design, implementation, and evaluation within the popular framework DUNE for solving differential equations using finite element methods. Our profiler is built on top of the PACXX framework for parallel programming in C++, and it supports portable parallel single profiling tool on various target hardware platforms.

The poultry house is the area where the chickens are maintained for the main purpose to improve the productivity and the environmental conditions for the broilers. The growth of chickens inside the poultry house can be affected by several criterions such as relative humidity and temperature. In this paper, we propose to design and implement experimentally a state-PID feedback controller in order to achieve a high stabilization of the dynamics systems of the poultry process. The purpose of this study is to keep the temperature and relative humidity at desired values and to eliminate the disturbance generated during the winter climate. The effectiveness of the proposed controller is evaluated through numerical examples and with an experimental poultry house prototype. To feature more the efficiency of the proposed approach implemented, a comparative study has been conducted between the results achieved by the proposed method and the state-PI feedback controller and that of a state feedback controller.

Peer Assisted Study Sessions (PASS) is a student let program designed to support students transitioning into university and tackling traditionally difficult first year core subjects. The model is collaborative with student leaders facilitating activities and discussions driven by student need. Consistently research has found that students can benefit, in terms of increased grades, from attending PASS, however findings for online delivery modes are mixed. These studies have generally only compared face to face (F2F) with online modes of PASS-like programs for one subject. No study has compared different subjects from varying disciplines to investigate if the benefits of PASS online are the same for all students. PASS at UOW conducted a pilot study of synchronous online sessions, tested across three different first year university subjects. A total of 1.471 students enrolled into these subjects, with 409 attending some form of PASS. Result revealed PASS students gained significantly higher average final marks compared to students who did not attend any type of PASS, regardless off subject. However, results for PASS varied depending upon mode of delivery engaged in (F2F or online) and also with subject. Although not all differences were statistically significant, trends suggest a student/subject interaction that may vary the amount of benefit gained from PASS online formats. Possible drivers for these results are discussed as well as consideration given to cohort effects and student skills for online learning modes.

This paper describes a silicon carbide-field effect transistor (SiC-FET) gas sensor that is able to detect NO, O2, NH3, CO, and SO2. The gate of the sensor FET is a gas detection layer that consists of yttria-stabilized zirconia, nickel oxide, and platinum. The threshold voltages of the sensor depend on the target gas concentration, measurement temperature, and sensor gate materials. The device on SiC substrate can measure gas at temperatures up to 800°C. The gate material dependence and the wide-range temperature dependence of the sensitivity make it possible to detect the concentration of each component in a mixture of gases. In addition, a gate stack composed of composite materials improves the sensitivity of the FET sensor by helping to maintain the sensor’s heat resistance and the reproducibility of its measurements.

Web services give a new view of the web as the biggest, widely accepted and the most straightforward distributed software platform. Their composition into applications and business processes is still a complex, non-trivial task, requiring highly rational efforts not only from the software developers, but from the quality assurance specialists. The provision ?f web service compositions’ quality brings a lot of challenges due to variability of difficulties at infrastructure, service and choreography levels and the need of different types of testing in unknown context and environment. A consolidated quality assurance methodology that advances the fundamental understanding of testing in terms of concepts, models, techniques, standards and automation is required. This methodology needs to enable effective exploration, comparison, evaluation and selection of testing approaches, platforms and tools.
This article proposes such a methodology and reviews the current testing approaches for single and composite web services from an objective, holistic perspective. The methodology is presented as an end-to-end testing procedure, in which activities are facilitated by a set of testing approaches, techniques and best practices. A concrete solution is recommended for actual implementation of each activity either through selection among the most appropriate and effective existing approaches or development of new approaches, mainly in case of critical issues such as dependencies analysis, partner web services’ isolation and injection of faults. A common framework that integrates different testing tools automates the methodology. Its applicability, completeness, level of automation, and level of novelty is evaluated through testing of real testing scenarios.

With advances in information and communication technologies and internet technologies, we have many benefits in our daily life. Most people have smart devices and use them for their work and leisure, and so on. However, these advances technologies brought us various side effects such as copyright violation, internet addiction, cybercrimes, personal information infringement, etc. In order to cope with those side effects, it is very important to teach information and communication ethics to students as early as possible. In addition, in order to teach young students, first, their awareness to information and communication ethics needs to be tested. In the literature, most awareness test tools are to test knowledge of information and communication ethics. In fact, those awareness tools have not consider sensitivity for information and communication ethics. In this work, an extensive and integrated sensitivity measurement tool is developed. At first sensitivity measurement standards are developed based on literature review works. Many elementary school teachers and ICT education experts survey the initial standards. Finally, sensitivity measurement standards are finalized with 6 areas and 19 standards. It is hoped that the proposed standards will be very helpful to diagnose awareness of elementary school students for information and communication ethics.

In the domain of business process management, the configurable process model is widely used to optimize time and cost of business process models design, which is known as the concept of “reuse”. Using process mining techniques for process model discovery helps to provide a better view on processes and improve quality of models. The majority of existing configurable model discovery approaches work intensively on control flow discovery as main process perspective without considering other perspectives such as resources and data, and do not propose a detailed discovery of variability elements. In addition, the configurable process model creation is generally done by merging variant models not directly from event logs, which is not the optimal way to get a reliable configurable process model. This paper presents an overview of new multi-perspective variability discovery approach. The approach respects the variability of different process perspectives and allows users to create a configurable process model directly from event logs.

This study presents a root cause analysis of biometric vulnerabilities and provides a comprehensive typology of metadata in biometric adaptation. Although they are more reliable and secure than traditional authentication methods, biometric techniques are subject to vulnerabilities that pose challenges. Faced with the proliferation of cases of identity theft and fraud, biometrics is increasingly used to protect assets and people in several areas such as commercial, forensic and government applications. As a first step, a metadata analysis was performed. A focus has then been placed on their role in the fight against biometric vulnerabilities. Thus, the vulnerabilities studied have been classified into two main categories: intrinsic limits and adverse attacks. Finally, one of the scenarios considered was implemented, particularly the case of the combination of skin color with facial recognition. The implementation resulted in encouraging results with an Area Under the Curve (AUC) of 0.826 for the face system and 0.908 for the multimodal system.

This paper proposes an algorithm aimed at quantifying the expression of KI-67 protein in digital images of breast biopsy tissue samples obtained through an optical microscope. The algorithm allows to obtain a report on the quantity of non-proliferating and proliferating cells through the detection and quantification of KI-67. The sample analysis via software aims to reduce the level of subjectivity in the diagnosis of diseases such as breast cancer. The algorithm proposed involves the application of statistical image processing techniques, adaptive thresholds, object segmentation and color filtering. A method of analysis and quantification of overlapping cells is also proposed to improve the efficiency of the algorithm. The results of the method proposed were satisfactory, as they were highly correlated with those obtained by visual inspection by pathologists.

Currently Indonesia is working actively in the implementation of the Smart Cities initiative program. However, to be able to apply the concept, there are three main elements that must be prepared as the basic foundation. These elements are structure, infrastructure, and superstructure. In this study we focused on the problem of the high cost of funding needed to finance these three elements. Therefore, we are of the opinion that the government must create new investment opportunities outside the stock exchange whose impacts can also be directly used for financing programs. In this study, we conducted an investigation of the interest of urban people to invest in online channels. The aim is to determine the decision-making behavior of the Indonesian people in non-consumptive capital expenditure activities when the government creates and publishes financing instruments on the market. The hope is to be able to create a national development financing strategy that is in accordance with the characteristics of the Indonesian people and right on target.

In high voltage engineering, air is the one insulation gas that can ionized cause by electrical discharge. Air consisted of many gases such as O2, N2, CO2, H2, etc. In order to study the characteristic of the insulation gas, we can apply density functional theory (DFT) to determine gas ionization level such as charge distribution and excitation energy. These data are shown the stability of gas molecule when ionization process occure cause by electrical discharge, ultraviolet light, etc. For application on ozone production by electrical discharge, the oxygen atom can transform to ozone need energy above the stabiity excitation energy of oxygen.

A framework is an amalgamation of integrated tools, libraries, utilities and its coordination to interact with the other automation components. The motive of designing a test automation framework is to implement uniform standards towards automation throughout the organization to achieve the desired outcomes. Test automation framework is required to maintain the standardization of the activities performed to manipulate the operations (addition, modification and deletion) on the test scripts and functions easily, to provide the scalability and reliability. Tools, process and testing team are the three key player of test automation. The proposed framework is based on the consideration of test environment (includes language binding, IDE, automation tools and testing framework). Selenium WebDriver is used as web application automation framework to execute test across multiple browsers that supports multiple operating system with variant programming language. Selection of WebDriver automation tool for this framework is due to their internal architecture to directly communicate with browser for fast execution. The combination of test automation tools (i.e. Java, Eclipse, Selenium and TestNG) makes JEST for designing test automation framework. Both Positive and negative test must be performed to verify functionalities of applications to handle unusual exceptions.

This paper shows a method applied during the reconstruction of an existing middle size Italian hospital. In fact, during this delicate phase, the project had a significant decrease in storage space and access gates for goods, medicines and medical devices. This aspect has a negative impact on road traffic. There was no consensus among the management on how to deal with this problem. In addition, a great tension between engineers and warehouse managers made it impossible to find a solution. For the best of our knowledge there is no available literature on this topic. Hence, a deep analysis had been carried out according to the Business Process Reengineering (BPR). For this reason, a hospital lean group has been created and a statistically study on storage volume inside the warehouse and a monitoring of trucks and goods arrival has been implemented. Three different solutions had been identified through data collection, design of experiments and lean application. The first one was focused on an exclusively internal management, the second one on an exclusively external management whereas the last one was focused on a partially internal scenario. Advantages, disadvantages, costs and the impact on the road traffic has been highlighted for each scenario. Afterward the Management had all the elements to make the best decision. The method reported in this study could be extended during the construction or reconstruction of any company that needs a warehouse or to face a problem in a tense atmosphere.

Here the work approaches the detection of fruit maturity level. In addition, a gas sensor is proposed to obtain better sensitivity to know the level of ethylene gas released from matured fruit. Better sensitivity can be achieved by obtaining an enhanced active area, changing the intermediate layer thickness and the pitch value of the electrode. Hexagonal nanostructured zinc oxide is used as a sensing layer. Finally, frequency shift and a total displacement of the device are increased. The hexagonal structured ZnO nanorod-based surface acoustic wave gas sensor may be used to detect ethylene gas in fruit ripening sensor with enhanced sensitivity. This paper reports a simulation of Surface Acoustic Wave (SAW) wave propagation with respect to interdigitated transducer (IDT), piezoelectric material and sensing layers.

This review paper discusses recent research outcomes of fabricating three-dimensional (3D) heterogeneous structures in complementary metal-oxide-semiconductor (CMOS) integrated circuit (IC) technologies to enable smart future chips. The CMOS-based 3D heterogeneous structures demonstrated are vertical magnetic-cored inductors for radio-frequency (RF) ICs, through-back-end-of-line (BEOL) metal wall structures for global flying noise isolation, above-IC nano crossbar array electrostatic discharge (ESD) protection devices and graphene-based nano electromechanical (NEM) switch ESD protection structures, and individually controlled multiple-gated MOS field-effect transistors (MOSFET) for non-binary computing. These disruptive 3D heterogeneous structure concepts can potentially enable future smart IC chips in Si CMOS IC platforms.

A novel control technique is implemented for TA converter. This converter is used for charging of electric vehicle Battery from a Photo Voltaic (PV) Module. TA converter is one type of non-isolated buck-boost converter. This converter provides positive output voltage. This article is an extension work that is originally presented in 2019 IEEE International Conference on Sustainable Energy Technologies (ICSET). A Comparative study of the performances of different converters has been described. The Paraconsistent Logic (PL) is used for a PI controller. The performance of new Paraconsistent Logic based PI (PLPI) controller is compared with the conventional PI controller. This control has the similar action as PI and the logical actions as structured in Paraconsistent Logic. Operational details of TA converter with the different performances has been described in this article. MATLAB is used to validate the performance by developing both state space and simulation model. The robustness of the controller is compared with traditional PI controller. The hardware of the TA converter with the new PLPI control technique is projected and also matched with simulation results.

In fast charging station for Battery Electric Vehicles (BEVs) the three-phase PWM (Pulse Width Modulation) inverters generate parasitic Differential-Mode Voltages (DMV) and Common-Mode Voltages (CMV). Parasitic voltages are a side effect of using the width modulation to shape the phase-to-phase inverter’s voltage. In this article the authors present a mathematical description of the differential-mode (DM) and common-mode (CM) voltages and carry out their spectral analysis. Based on the spectral harmonics analysis, the authors present a method for filtration of harmonics of DM and CM voltages aimed at limiting the capacitance parasitic currents: due to DM voltage – phase-to-phase parasitic current and CM voltage – ground parasitic currents. A resonant filter was used to eliminate harmonics of the input rectifier of the DC/DC converter supplied from a voltage inverter. As a result of tests, the T HD harmonic content factor was significantly reduced and ground leakage ted from the PE electric shock protection system.

In fast charging station for Battery Electric Vehicles (BEVs) the three-phase PWM (Pulse Width Modulation) inverters generate parasitic Differential-Mode Voltages (DMV) and Common-Mode Voltages (CMV). Parasitic voltages are a side effect of using the width modulation to shape the phase-to-phase inverter’s voltage. In this article the authors present a mathematical description of the differential-mode (DM) and common-mode (CM) voltages and carry out their spectral analysis. Based on the spectral harmonics analysis, the authors present a method for filtration of harmonics of DM and CM voltages aimed at limiting the capacitance parasitic currents: due to DM voltage – phase-to-phase parasitic current and CM voltage – ground parasitic currents. A resonant filter was used to eliminate harmonics of the input rectifier of the DC/DC converter supplied from a voltage inverter. As a result of tests, the T HD harmonic content factor was significantly reduced and ground leakage ted from the PE electric shock protection system.

Metamaterial antennas are some sort of antennas which utilize metamaterials to improve the efficiency of small (small electrical) antenna systems and also enhance the antenna’s radiation pattern. The unusual properties of metamaterials such as coefficients of permittivity and permeability, as well as the negative refractive index, have led to increase the use of these artificial materials in variant fields including microwave engineering and medical applications. This paper explores a metamaterial coating and impact of it on a microstrip patch antenna from two different perspectives on satellite and biomedical applications. For this purpose, a microstrip antenna is modeled using CST software and then a particular metamaterial cover is configured upon the patch antenna to enhance its efficiency such as radiation pattern and directivity. The method is arranged in several stages and the output of the antenna is then analyzed in each stage after applying some adjustments to the design process. On the other hand, because the type and position of the applicator on the tissue is a consequential variable, in order to improve the effectiveness of hyperthermia treatment in medical applications, in the next step the metamaterial antenna is applied to hyperthermia treatment on the body tissue. Eventually the results of metamaterial antenna are compared with the usual antenna.

Stress occurring in the early days of an individual was often assumed to cause several health consequences. A number of reports indicated that having to deal with unfavourable events or distress situation at a young age could tweak stress responses leading to a broad spectrum of poor mental and physical health condition. Therefore, changes identified within stress response were recommended to be taken as a measure in regulating and managing such health situation. This study combines the biomarker that represents both autonomic nervous system (ANS) and hypothalamic-pituitary-adrenocorticol (HPA) as a single measure to classify the stress response based on traumatic childhood experience and propose a stress response index as a future health indicator. Electrocardiograph (ECG), blood pressure, pulse rate and salivary cortisol (SCort) were collected from 12 participants who had traumatic childhood experience while the remaining 11 acted as the control group. The recording session was done during a Paced Auditory Serial Addition Test (PASAT). HRV was then computed from the ECG and the HRV features were extracted. Next, the best HRV features were selected using Genetic Algorithm (GA). Biomarkers such as BP, PR and SCort were then integrated with 12 HRV features picked from GA. The integrations were conducted using two fusion methods which are Euclidean distance and serial fusion. The differences in reaction of the fused features were then identified. Based on the result, the Euclidean distance (ed) which is the fused feature by the parallel fusion, displayed the most efficient reaction with accuracy, sensitivity, and specificity at 80.0%, 83.3% and 78.3%, respectively. Support Vector Machine (SVM) was utilized to attain such result. The fused feature performance was then fed into SVM which produced indexes on stress responses. The result retrieved from these indexes acts as a measure in handling future health deliverability and perhaps could eventually enhance the health care platform for midlife individuals.

An experiment to determine the performance of a thermoelectric powered by solar panel for a large cooler box was carried out. The size of the cooler box tested was 1000 mm x 500 mm x 400 mm and inside the cooler box, a plastic bottle containing 19 liters of water was placed. The thermoelectric hot side was cooled using a mini channel flowed with water. Meanwhile, the cold side of the thermoelectric was connected to the inner heat sink to absorb heat inside the cooler box. The thermoelectric was powered from a battery charged by solar panels directly. There were 2 solar panels, each of which had a power of 100 WP. The cooler box was tested for 6 days in June 2019. The results showed that the lowest temperature on the thermoelectric cold side was around 16.21°C, while the lowest temperature inside the cooler box was 24.25°C. The experimental COPs obtained were ranging from 0.01 to 0.76. Moreover, in general, solar panels were potential as power sources for thermoelectric cooling systems.

Noninvasive measurement of skin tissue oxygen saturation, StO2, is of interest especially in the studies of wound healing and detection of vascular diseases. This work aims to compare Partial Least Square (PLS) regression, K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) technique in the prediction of StO2 using spectral data obtained from Monte Carlo simulations. We found a good performance of PLS technique with mean and standard deviation (SD) of the absolute prediction errors given by 2(1.37) % for noisy data with signal-to-noise ratio (SNR) of 30 dB. The errors increased to 4.67(3.87) % under SNR of 20 dB. This is followed by KNN technique, which calculated errors varied from 4.28(3.58) % to 7.61(6.08) % with a decrease in SNR. Meanwhile ANN produced large errors in its prediction ranging from 4 to 9 % for the considered SNR values. This work concluded PLS is suitable for use in selecting significant spectral information for the development of prediction models using artificial intelligent (AI) system or a hybrid combination of AIs to achieve a higher accuracy.

In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter out the key features and perform multi-scale convolution of key features. And we apply this module to the design of high performance small neural networks. The experiments are carried out on 101_food and caltech-256 benchmark datasets. Experiments show that the module has higher performance than classical module, and the small convolution networks based on the module has less parameters and more excellent performance.

The increase in employment and productivity is crucial for the economic growth of the European Union. Specifically, the employment of young people needs to be increased. The excessively theoretical approach to education is identified as one of the most significant problems in the educational system. Acquirement of practical experience while study, presents for the students the advantage when applying for a job or starting their own business. Self-employment or entrepreneurship might be one of the partial solutions for high youth unemployment in EU countries. The information and communication technologies transform education processes already for decades. The education in the area of entrepreneurship is also the field where these transformations occur. New educational forms and tools are being used in this area. Project-Based Learning and virtual laboratory are two examples of such new forms of education supported by information and communication technologies used in entrepreneurial education. This paper aims to present how project-based learning and virtual laboratory can support entrepreneurial education on the examples of two courses offered at our faculty. Through project-based learning, participants of these courses achieve the opportunity to implement their knowledge, skills, and experience to solve practical problems. It, all together, enhances the students’ motivation and involvement in the educational process. They also practical experience establishing and managing a small virtual business within the virtual laboratory of entrepreneurial education. The paper describes the setup of these courses, their content, and evaluation by students and achieved results. The findings show that project-based learning and the virtual lab supporting entrepreneurship education via electronic tools are useful ways of entrepreneurial skills development.

As an emergent technology in Internet of Things (IoT), the ultimate target of fog computing is to provide a widely distributed computational resources and data repository closer to the network edge providing heterogeneous systems both in terms of software and hardware. The fog system must have the capability to deal with huge number of resources and users at the same time, such increased size sometimes presents the issue of performance degradation. Therefore, the fog should be able to support adaptability, scalability, and extensibility to avoid such degradation by adopting efficiently and effectively an optimal resource selection and allocation model. As many fog users have limited interest in, or knowledge of fog middleware issues, it follows that in a large fog environment the best approach would be to have an automated system for resource selection and allocation. Such an approach eliminates the need for user intervention. This paper proposes a fog resource selection service based on neural network to perform resource selection tasks by coordinating with the metascheduler. Five different selection algorithm were used to evaluate the prediction model for resource selection. In addition to introducing a history update and management algorithm to manage and control the storage of the history log records.

Many real-life applications based on the wireless sensor networks are equipped with data aggregation mechanisms for suppressing or even overcoming negative environmental effects and data redundancy. In this paper, we present an extended analysis of the linear average consensus algorithm for distributed summing with bounded execution over wireless sensor networks. We compare a centralized and a fully-distributed stopping criterion proposed for the wireless sensor networks with a varied initial configuration over random geometric graphs with 200 vertices in order to identify the optimal initial configuration of both analyzed stopping criteria and the algorithm as well as finding out which stopping criterion ensures higher performance of the examined algorithm in terms of the estimation precision and the pressed as the iteration number for the consensus.

In this scientific work, the basic synergetic principles of the development of the paradigm of civilizations are substantiated, an assessment of the time boundaries within which civilizations exist, the features of their own path of development of Uzbek culture are revealed. It is especially drawn attention to the sociocultural codes of civilization, a combination of which identifies the essence of Uzbek civilization. However, gives the reasons for the threat of the existence of civilizations and the prospects for their further development. The problem of the paradigm of civilizations interested many inquisitive minds of mankind, philosophical schools and trends. Its origins can be found in antiquity and in the Middle Ages. Dosocrats, Plato, Aristotle, Stoics, Epicureans, Neoplatonists, Thomas Aquinas, al-Farabi, Ibn Sina developed problems of society and history within the framework of the classical metaphysical and dialectical-idealistic tradition. It is believed that the modern form and meaning of the term civilization in some cases preserves what was put into circulation, first of all, by the French and English enlighteners in the second half of the 18th century, who proposed a universal scheme for the development of mankind – savagery, barbarism, civilization and focused on the search for the source of the development of society, the driving forces of history: V. Voltaire, J. Kondors, A. Turgot. This problem has not been developed in Uzbekistan from a philosophical point of view, in particular, that part of it that deals with ontological and epistemological aspects. In connection with the study, dialectical, formal-logical, historical-morphological methods were used, as well as comparative analysis methods.

Technological developments in the Internet and communications have created a vastly complex and dynamic context with diverse heterogeneous networks and fast growth of mobile devices and multimedia. As the Internet becomes the primary mode of communication for many organisations there is requirement to enhance quality of service (QoS) from heterogeneous systems and networks. Traditional networks such as TETRA have become increasingly incapable of addressing the demand for media rich, bandwidth intensive traffic flows and applications. Mission-critical multimedia over new generation mobile networks face QoS constraints. This research explores a novel solution for quality of service performance for streaming mission-critical video data in OpenFlow SDN networks. A Meter Band Rate Evaluation (MBE) mechanism is advanced that improves the native QoS capability of OpenFlow and OpenDaylight. The MBE is a physical component added to the OpenFlow meter table to evaluate and dynamically adjust traffic rates and allows the traffic volume to be specified relative to other traffic in the network. Its design and development are presented, and the mechanism is verified through a simulated experiment in an SDN testbed. The results identified that QoS performance experienced a significant percentage increase when the MBE was active. These findings contribute a novel Meter Band Rate Evaluation mechanism that extends the native capability of OpenFlow and OpenDaylight to enhance the efficiency of QoS provision.

The paper discusses the features of the implementation and functioning of digital self-timed circuits. They have a naturally high tolerance to short-term single soft errors caused by various factors, such as nuclear particles, radiation, and others. Combinational self-timed circuits using dual-rail coding of signals are naturally immune to 91% of typical soft errors classified in the paper. The remaining critical soft errors are related to the state of the dual-rail signal, opposite to the spacer and forbidden in traditional dual-rail coding of signals. Paper proposes to consider this state as the second spacer and to indicate it as a spacer to increase the self-timed circuit tolerance to soft errors. Together with an improved indication of the self-timed pipeline, this provides masking of 100% of the considered typical soft errors in combinational self-timed circuits. Due to internal feedback, self-timed latches and flip-flops are less protected from soft errors, as are synchronous memory cells. But thanks to their indication and the input and output signals generation discipline, they are also immune to 89% of typical soft errors. Usage of the self-timed latches and flip-flops with dual-rail coding of information outputs increases the tolerance of self-timed latches and flip-flops to soft errors by 2%. Application of the DICE-like approach to circuitry and layout design of sequential self-timed circuits provide an increase in their tolerance to the single soft errors up to the level of 100%.

Recent years have seen a continued pattern of development in the cloud computing field. Numerous approaches to maximize file transfer capacity are still completely standing for use on cloud computing storage; however, they do not maximize the advantage of data migration scalability and elasticity in cloud storage. One potential problem is that elasticity takes time; however, the scalability attributes that have not been fully exploited include multicore chips and parallelization that can further be leveraged to enhance the overall data transfer performance and efficiency. In that regard, considerable effort has been directed to multiprocessors. Such systems involve a plurality of processors or functioning units capable of independent operation to process separate tasks in parallel. Nevertheless, the penalization is complicated when a task requires several resources or signals to proceed with meaningful computation. Thus, accommodating equitable priority among tasks further complicates operations. In this paper, we propose a parallel server to cloud storage transfer system in which parallelism method can only be utilized in case of transferring a large number of files and applied in order to increase the transfer throughput. The data is transmitted into several chunks via TCP network within the same period slot in a single data path which indicates dataflow on parallelism. Our target in this system is that increasing number of processors and the problem size will simultaneously maintain the efficiency of the data transfer system. The proposed model is based on the combination of dynamic segmentation, CRS, AES, and hashing [1]. In summary, the proposed model shows the potential to enhance the performance by increasing the data transferability. The performance of the proposed model will be measured with the help of comparing the average execution time with the number of processors and speedup of the entire parallel system.

In this paper, a regenerative energy recovery system for electric vehicles charging a battery at a low speed is proposed. When a permanent magnet synchronous motor driving the electric vehicles is driven by a generator, the generated voltage is controlled to rise or drop by using the L-C resonance circuit. As the circuit only has three capacitors and three IGBTs, the proposed system is very simple. A resonance frequency is found through frequency analysis of the L-C resonance circuit; furthermore, using the resonance effect, a generated voltage control algorithm is proposed. PI duty control in the algorithm raises the generated voltage and reverse PI duty control in the algorithm reduces the generated voltage. The results of simulations and experiments confirm that a remodeled electric vehicle by the proposed system is charged to the driving battery. The results also demonstrate that a small energy storage capacity, which is a disadvantage of the electric vehicle, is largely compensated without increasing the complexity of the electric vehicle.

This paper is an extension of work originally presented in 2019 International Conference on Automation, Computational and Technology Management (ICACTM). A micro-strip patch in-body designed antenna is constructed on pacemaker to monitor and control the pacemaker wirelessly. The antenna is intended for ISM (Industrial, Scientific, and Medical) band (2.4 GHz to 2.48 GHz). A perfect electric conductor (PEC) is considered as pacemaker body and used as the ground of the propounded antenna having dimensions 40 x 30 x 10 mm3. The patch material is chosen Copper having dimensions 35 x 22 x 0.1 mm3 and covered up with substrate material Rogers R03010 (loss tangent ? = 0.0035 and dielectric constant, ?r = 10.2) with thickness of 1.55 mm to make it compatible in human body. The designed antenna is placed and analyzed in 2/3 muscle equivalent phantom by changing the depth of the antenna. Results disclose that operating frequency is 2.464 GHz with reflection coefficient -28.37 dB. The antenna maintains frequency range from 1.8075 GHz to 3.445 GHz, which represents wide bandwidth of 1.6375 GHz. To ensure the human body safety, specific absorption rate is analyzed and found 0.937 W/Kg for 10g tissue at operating frequency, which makes it biocompatible. The surface current distribution, Voltage Standing Wave Ratio, Current density, far-field radiation characteristics, radiation efficiency, and total efficiency are investigated to analyze the effect and performance of the designed antenna. CST Microwave Studio is used for simulation and analysis the parameters of the antenna.

Wireless Body Area Network (WBAN) aims to monitor patient’s health remotely, by using mini medical sensors that are attached on the human body to collect important data via the wireless network. However, this type of communication is very vulnerable to various types of attacks, poses serious problems to the individual’s life who wears the nodes. In this paper, we present a new classification of the most dangerous attacks based on different criteria, which gives us a clear vision of how attacks affect a WBAN system. Moreover, this classification will help us to specify the strength and the weakness of each attack in order to facilitate the development of a new intrusion detection system (IDS). In the second part of this work, we develop a novel IDS for detecting three types of jamming attacks in WBAN. The proposed methodology is based on the network parameters as an indicator to differentiate the normal case from the abnormal case like false alert or attack state. Through simulation analysis that was applied on Castalia platform by using OMNET++ as a simulator, proves that the proposed IDS have a great effect for detecting the presence of jamming attack in the network.

Medical images are transmitted via the Internet or the hospital intranet which include many important information about the patient’s personal information. Medical image encryption is a technology that can effectively protect the information contained in these medical images. In this paper, we give a secure and trusty Combined Cellular Automata (CoCA) based medical image encryption algorithm. CoCA is made up of a nonlinear CA and a linear 90/150 maximum length CA, and three dimensional generalized chaotic map. The proposed algorithm consists of two phases. The first phase encryption process that changes pixel values of a given image using two CoCAs. The second phase is to change the position of each pixel in the image encrypted using the three dimensional generalized chaotic cat map that can change with effect the position of pixels not only in two dimensions horizontally and vertically but also in color plane three colored channels simultaneously. We show the stability and high reliability of the given color medical image cryptosystem through detailed analysis and various statistical experimental tests.

This article deals with the issue of parking houses, storage mechanisms and how to control them. A laboratory model of a multi-storey underground automatic parking house was designed and created for this purpose, which is used to test a new innovative way of storing cars and specialized approaches to driving actuators. The model is based on an aluminum profile frame to which a newly made linear two-stage dual-sided telescopic mechanism and a two-axis positioning mechanism is attached. The emphasis is placed on the smooth movement of all axes which limits shocks caused by mechanism speed change while moving to a defined position.

Recurrent Neural Networks has been widely used by researchers in the domain of weather prediction. Weather Prediction is forecasting the atmosphere for the future. In this proposed paper, Deep LSTM networks has been implemented which is the variant of RNNs having additional memory block and gates making them capable of remembering long term dependencies. Fifteen years hourly meteorological data of Brazil weather stations for the period of 2000-2016 collected from Kaggle.com has been analyzed for 1 hour and 24 hour time lag using Keras libraries on Spark framework. Hidden layers of the network have been increased up to three to examine its impact on accuracy of the network and it was found that network with 2 hidden layers provides good accuracy in lesser learning runtime. From the experimental results, it is also concluded that Adam optimizer provides best results when compared with SGD and RMSProp optimizer.

One of the creative industries with rapid growth is the airbrush industry. Airbrush art, especially realist, is identical to the field of automotive engineering in the combination of art and technology. The research is directed to prove how the difficult realist airbrush competency can be achieved by Vocational High School (VHS) students in a short time. Also, the research synchronises the increase in entrepreneurial understanding of VHS students in real business incubation in the realist airbrush industry. The final results show that entrepreneurial learning needs to add elements of art as a stage in the acquisition of real competencies.

Breast cancer has an important incidence in women mortality worldwide. Currently, mam- mography is considered the gold standard for breast abnormalities screening examinations, since it aids in the early detection and diagnosis of the illness. However, both identification of mass lesions and its malignancy classification is a challenging problem for artificial intelligence. In this work, we extend our previous research in mammogram classification, where we studied NasNet and MobileNet in transfer learning to train a breast abnormality malignancy classifier, and include models like: VGG, Resnet, Xception and Resnext. How- ever, training deep learning models tends to overfit. This problem is also carried out in this work. Our results show that Fine Tuning achieves the best classifier performance in VGG16 with AUC value of 0.844 in the CBIS-DDSM dataset.

Air pollution is responsible for increased morbidity and mortality due to respiratory problems mainly caused by long term exposure. Although the emissions of principal air pollutants are highly regulated, there is a lack of information about the real extent of personal exposure for an accurate health impact assessment. To tackle these challenges, local air pollution measurements and citizen involvement based on the small IoT devices became necessary. The Tel-MonAer platform is based on IoT devices and Edge/Cloud computing technologies and allows the (near) real-time monitoring of Particulate Matter air pollutants considering the complex chemistry and influence of various parameters (i.e. air humidity, wind speed, temperature). The aim of this paper is the assessment of the influence that air humidity has on the PM concentrations measured with IoT devices based on laser beam technologies. The results showed that in order to increase the accuracy of PM concentrations values a threshold value for relative humidity of 80% needs to be considered. When humidity values are below 80%, the PM concentration values are considered valid, while for values over the threshold, a specific correction algorithm needs to be applied. This paper presents the correction algorithm (based on the type of sensor and humidity) and the testing results (an increase of at least 2.5 times of the correlation coefficient between the corrected and reference values).

This paper presents hybrid solar thermal/electricity automated oven. The work compares sliding mode control (SMC) to traditional PID control of the oven system using MATLAB/Simulink 2014b model. SMC control method shows faster rise and settling time. The control technique has been designed to automate change of temperature level of the oven by accepting multiple reference inputs. This has been implemented using microcontroller programed in C++. Flat-plate solar thermal collector and paint curing oven have also been implemented for experimental test. The results obtain from the experiments are in conformity to the simulation results. The collector delivers 43.27% of the total energy required to operate the oven up to 120°C at 200W/m2 solar insolation. Calculation of payback period for commercial viability on the cost of the collector installation indicates a year and four months for an average insolation of seven hours per day. These results demonstrate that the research work is effective and solves the problem of temperature control in curing modern organic paints and the challenge of power requirements in the operation of oven.

The article is devoted to the formalization and development of the theory of sequential experimental design for optimal identification of dynamic objects. The algorithmic and technical support for a system of sequential D-optimal identification for a wide class of dynamic objects in real time is considered. This system is universal and can be used for optimal identification of real objects and continuous technological processes.

A Software Defined Network (SDN) architecture is characterized by decoupling the data plane and control plane. This feature enables the establishment of a programmable environ- ment in which the control plane acts under the data plane, managing and configuring the network over a standard protocol, such as OpenFlow. Although there are numerous benefits to the SDN architecture, security is still a matter of concern, as the decoupling expands the attack surface on the network. Denial of service (DoS) attacks is one of the major challenges for the SDN architecture, mainly due to the vulnerabilities existing between the control and data planes. This paper proposes an enhancement to the SDN architecture enhanced with DoS attack detection mechanisms. Two techniques have been evaluated to identify of DoS attacks: entropy and chi-square. Both techniques use OpenFlow switches statistics so that it is possible to distinguish benign traffic from spurious traffic. Experimental results show that entropy and chi-square present similar results in terms of spurious flow detection accuracy. However, on average, chi-square requires about 14.89% fewer packets to detect the attack when compared to entropy.

Stirling engines working with relatively low temperature are attractive for the future, especially for applications like water pumping without concentration system and low temperature heat recovery. The present work is the continuation of a series of works on the optimization of this type of machines. The main objective of this paper is to investigate the performance of low temperature differential Stirling engine (LT-SE) regenerator by adopting a theoretical model based on heat transfer and frictional pressure drop correlations. Since the speed and the Reynolds number of this type of machines are low, the correlations concerning pressure drop were validated by comparing the calculated results with experimental measurements on a LT-SE prototype. Based on this model, several calculations were conducted in order to know how LT-SE designers can attain a desired value for regenerator effectiveness. In fact, the effect of six parameters on regenerator performances was investigated. Studied parameters are: engine speed, regenerator volume, regenerator porosity, wires diameter, working fluid type and regenerator fibers arrangement. The effect of these parameters was especially checked on pressure drop, heat transfer coefficient, regenerator and engine efficiencies. Results indicated many designing recommendations for LT-SE having the same power range of our prototype: a regenerator length around Lreg= 1.41 × displacer stroke, a wire diameter around dw= 0.15mm, a porosity around ?= 0.75. Results indicated also that the most performant working fluid is Helium.

The technology of electronic steering with force feedback is related to electronic vehicle control. This technology is also known as “steer-by-wire” technology and is specific in that there is not any mechanical connection between the axle and the steering wheel. This technology is currently not very widespread. However, developments in the automotive industry are slowly moving towards this technology in the context of autonomous vehicles. This study includes a review of current technologies in this area and suggests a technical solution for Steer-by-Wire technology and its verification in the real vehicle model in the university environment.

In recent years, several projects which are supported by information and communications technologies (ICT) have been developed in the agricultural domain to promote more precise agricultural activities. These projects account for different kinds of key ICT terms such as internet of things (IoT), wireless sensors networks (WSN), cloud computing (CC). These projects are used for different agricultural products; and it is a well-known fact that they can be essential to perform precise agricultural activities for the relevant agricultural products. The implementation of these projects successfully depends on the extent to which various stakeholders provide support by leveraging relevant data, gathered from heterogenous data sources. Agriculture domain has a great number of stakeholders. These stakeholders need sophisticated data and appropriate intelligence to get benefits in order to perform precise agricultural activities. Authors agreed with scholars that “Open Data” idea, which means accessing data published on the web and available in a machine-readable format is an appropriate way to get benefits for precise agriculture by relevant stakeholders. In this paper, authors shall investigate the open data term in an agricultural context, create an open data processing model, and develop an IoT-based solution to gather environmental data from agricultural fields. Authors also show viability of the proposed model by developing an ICT-based solution. Considering the socioeconomic importance of hazelnut for Turkey, the stakeholders of hazelnut domain still have problems such as availability, meaningful, accuracy of the hazelnut related data. Therefore, authors shall focus on hazelnut within the scope of this paper.

This paper represents analysis of principles providing maximally reliable delay estimation of signal synchronization devices in telecommunication. Clock synchronization schemes on the base of stochastic models, graph-analytic interpretation, analytical functional description and their parameters selection in case of real complex hindrance are analyzed. Dependences between dispersion of maximally reliable estimation of synchronization devices and signal to noise ratio (SNR) are represented. Analytical expressions and dependences are obtained for deviation of synchronization error with respect to SNR at the output of discriminator. Diagrams of state are formed for assessment of digital synchronization device in case of error state. Calculated error of numerical solution of the equation of a stationary grid method. We obtain the schedule of the distribution of the probability density synchronization errors for different values of the normalized time. The functions performed by the symbolic synchronization circle, features of the construction of the timing error detector (TED) are analyzed. The Gardner, Early-Late, Mueller & Muller TED, their error and the S-curve equation are investigated. The dependence of the relative timing error on the SNR is obtained. The article examines the effects of interpolation and decimation conditions in the forming filters of digital communication systems.

Immersive output and natural input are two core aspects of a virtual reality experience. Current systems are frequently operated by a controller or gesture-based approach. However, these techniques are either very accurate but require an effort to learn, or very natural but miss haptic feedback for optimal precision. We transfer ubiquitous touch interaction with haptic feedback into a virtual environment. To validate the performance of our im- plementation, we performed a user study with 28 participants. As the results show, the movable and cheap real world object supplies an accurate touch detection that is equal to a laserpointer-based interaction with a controller. Moreover, the virtual tablet can extend the functionality of a real world tablet. Additional information can be displayed in mid-air around the touchable area and the tablet can be turned over to interact with both sides. Therefore, touch interaction in virtual environments allows easy to learn and precise system interaction and can even augment the established touch metaphor with new paradigms.

In this article, a new form of UWB (ultra-wide-band) antenna operating to the desired specifications, obtained from a base antenna to which some modifications are made. The proximity of the antennas causes a mutual coupling phenomenon thus generating an apparent modification of their characteristics. It is therefore crucial to have the minimum level of insulation with a small possible separation distance between the antennas to ensure efficient operation of our multiple input and multiple output (MIMO) system. The separation spacing between the antennas is close to 0.15?0 (?0 is the wavelength in free space), where the coupling can be very weak. To overcome this weakness, two efficient methods are applied to minimize mutual coupling in a four-element MIMO antenna, such as the use of the neutralization line and the use of split ring resonator metamaterial (SRR). The objective of our paper is, on the one hand the design of UWB antenna, and on the other hand to minimize the coupling between four UWB-MIMO antennas using the two methods of isolation mentioned above. A coupling minimization of more than 15 dB is obtained using the neutralization line and more than 20 dB with the use of metamaterial while maintaining the operating band and radiation specifications of the MIMO antennas.

In recent years there has been technological growth in the field of facility location, considering it as a significant factor to achieve greater competition among companies. The present work gives a methodological solution for a territorial redesign in a Mexican automotive parts distribution company with the support of Geotechnological tools like Geographic Information Systems (GIS) and Global Positioning System (GPS). The objective of this research is the improvement of customer service and, at the same time, a reduction in logistics costs. In this research, were evaluated and proposed two scenarios. The first the re-allocation of the current customers to the nearest distribution center, obtaining a decrease of the distance of 5.08%; and a second scenario where the opening of four peripheral warehouses reduces up to 24.6% of the total kilometers traveled. Currently, the company is evaluating which scenario is the most convenient for the company based on its resources and expansion plans. The value of this work is to be taking into account real-world results and manage a large amount of data as well as consider the constraint of impedance.

In recent years, research has been conducted focused on the use of technologies in the classroom, but one of the main problems is to demonstrate that the use of this technology favors learning compared to traditional methods. One of these technologies is augmented reality that allows seeing virtual objects superimposed in the real world, but to achieve its correct use it is necessary to evaluate the usability that is the ease with which an interface is used. In this work we develop and analyze from two perspectives an educational application for zoology that uses augmented reality, a first perspective is usability, where an analysis has been carried out on how the correct design of an augmented reality application should be focusing on heuristic evaluations, the second perspective is at the educational level where we analyze it at the classroom level where we measure the different learning methods (Traditional Learning, Self Learning, and Guided Learning) and which one should be used.

In the new technologies for producing electricity from wind gusts, a new class of wind power converter has been proposed. The hybrid autogyro uses the principle of autorotation to generate lift. This paper proposes to take advantage of this rotation to also generate energy. There are systems that use flying wings or airplanes to reach winds that blow in layers of the atmosphere that are inaccessible to traditional wind turbines. Wind gusts are disturbances that significantly affect the behavior of this kind of aircraft. However wind gust is the source of energy and this wind speed increases with the aircraft’s altitude. This paper reviews the mathematical model of the hybrid autogyro aircraft and proposes a control algorithm to ensure that the vehicle remains horizontal in forward flight, in this way is possible to maximize the generated energy, this concept is tested in numerical simulations.

Nowadays the buildings sector is one of the key sectors to achieve sustainability, with the correspondent consumers, in particular, the household consumers, having the need to perform sustainable choices every day, regarding the appliances to be acquired from the market. This is not only due to government’s growing concerns about sustainability but also with the consumers on having sustainable solutions, given the different economic, social (including their comfort) and environmental needs. However, the existence of several electrical appliances on market, with all their different issues, brands and models, together with the several tradeoffs referred before, difficult the consumer’s choices, on having sustainable solutions in the market. Therefore, this work, presents an approach, by using Multi-Attribute Value Theory (MAVT), integrated with metaheuristics, which uses Evolutionary Algorithms (EA) to provide suitable and sustainable market solutions to a consumer, according to its own needs. Based on the achieved solutions and considering the relative importance, given to each consumer, and regarding each dimension of sustainability, it’s possible to achieve several savings, namely electrical and water consumption, CO2 emissions, among others. A case study shall be shown, to demonstrate the applicability of the proposed approach.

Bull service is the natural copulation by a purebred male carabao with a female counterpart. This is part of the bull loan agenda of the Philippine Carabao Center-Visayas State University (PCC-VSU), one of the 12 regional centers of PCC. For the past years, PCC-VSU used averaging of bull services count of previous years and sometimes did a little tweaking of the formulas in setting annual targets. Some targets fell short in the actual accomplishment that may have led to achieving lesser animal products. There is a need for resource optimization. Resource optimization through Auto-Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) forecasting can be used in the setting of goals of future number of copulations. This study deals with the comparative assessment of ARIMA and ANN in 4-step and 12-step ahead time series forecasting of bull services. This endeavor dealt with quarterly data from 2002 to 2017. In ARIMA, the for 4-step ahead (1-year) forecasting had the data from 2002 to 2016 for training while data from 2017 was employed for testing. ARIMA 12-step ahead (3-year) forecasting had data from 2002 to 2014 for training and 2015 to 2017 for testing. The ANN 4-step ahead prediction made use of data from 2002 to 2015 for training, 2016 for validation and 2017 for testing. ANN 12-step forecasting had data from 2002 to 2011 for training, 2012 to 2014 for validation and 2015 to 2017 for testing. R studio, a tool for statistical computing was employed in the analysis. Based on the performance measures Root Mean Square Error, Mean Absolute Percent Error and Mean Absolute Error the ANN outshines the ARIMA in both 4-step and 12-step ahead forecasting. The ANN forecasting can surely help in optimizing the center’s resources. The forecasting of bull services using multivariate series is recommended.

The goal of this research work is first to investigate the comparison between a batch and a continuous pyrolysis reactor (at 500, 550 and 600 °C) and the eventual differences and similarities that are obtained by analysing the obtained liquid and gas compositions. All the products formed were examined: liquids by GC-MS/FID and Karl Fischer titration, gases by GC-FID/TCD and solids by thermogravimetric analysis (TGA). It was observed that even though not the same pyrolytic reactor was used, the parameters rendering the maximum yield of bio-oil were the same in both cases: 500 °C under 500 mL/min N2 (~58 wt. %). Furthermore, it was observed that while changing the temperature affected significantly the product distribution, varying the gas residence time did not cause much change to the product distribution. This was due to the fact that pyrolysis was occurring within the same intermediate regime (?: ~9 min), and that the limiting factor of the reaction was thus the biomass particle residence time (20.6 s), not that of the gas. Finally, the observations obtained for product distributions and evolution for both the batch and the continuous setups were compared, and discrepancies between results from the two setups were found. This led to the conclusion that comparisons between reactors of different scales need to be undertaken with caution as the results might not be directly comparable.

The internet of things has resulted in the design and development of many electronic sensors that need to be integrated with various technologies. Engineering academics need ongoing training relating to this integration as they need to subsequently teach their students. This relates to continuous professional development. The purpose of this article is to illustrate how engineering academics from a vocational college have been able to engage with the theory and practice of sensor integration with Arduino technology, thereby strengthening or reconstructing their conceptual knowledge of these electronic components. A case study is used where experts in electrical engineering designed and facilitated an academic development workshop (2 days in duration) to address a need for continuous professional development. Eighteen academics from a local vocational college attended this workshop where the first goal was to determine their conceptual knowledge of 10 electronic components using an electronic responsive system (pre-test). The second goal was to facilitate a “hands-on” laboratory session where academics had to physically integrate various sensors with an Arduino microcontroller. A post-test online questionnaire was then used to determine their conceptual knowledge again, in order to ascertain the impact of the workshop. Results indicate that their conceptual knowledge was reconstructed with regard to the purpose and use of capacitors, Zener diodes, transformers, ultrasonic sensors, reed switches and passive infrared receivers. A problematic question arose relating to photocells in the first workshop that was held in 2017, which was resolved by the facilitators prior to offering a second workshop in 2018. Positive feedback was received from the participants regarding the relevance and presentation of the workshops. The novelty of this work relates to the design of a practical workshop where all participants are engaged to either strengthen, or reconstruct, their conceptual knowledge regarding electronic components that may be integrated with Arduino technology.

Limited functionalities of the Academic Progress Information System (SIsKA) has direct consequences on the quality of thesis management service at the authors’ magister study program of the authors’ university. This research focused on the significant improvement from the previous User Experience Questionnaire (UEQ) result of SIsKA. That significant improvement was based on the recommendations from the previous Heuristic Evaluation (HE) and two additional usability evaluation methods. All of those improvements have been applied to the new Academic Progress Information System that was called SIsKA Next Generation (SIsKA-NG). Overall, there are three usability evaluation methods were used in this research, namely the Performance Measurement (PM), the Retrospective Think Aloud (RTA), and the UEQ. The PM through the effectiveness analysis and the efficiency analysis each provided 11 and 16 recommendations, while The RTA provided 39 recommendations. The UEQ provided the assessment on SIsKA-NG with level excellent on aspect of attractiveness, efficiency, dependability, stimulation, and novelty; and with level good on aspect of perspicuity. It was considered as a significant improvement of the UEQ result of SIsKA-NG compared to the previous UEQ result of SIsKA because of the better assessment on four aspects with level excellent on SIsKA-NG, namely attractiveness, efficiency, dependability, and novelty. Same assessments are on two aspects, namely perspicuity and stimulation. SIsKA-NG still need to be improved based on the aspect of perspicuity, additional recommendations from the conducted Focus Group Discussion, and procedural White Box testing for code evaluation.

This paper presents a collaborative interaction model (CIAO) and several behaviour rules that could enhance brainstorming results. The model is composed of five elements which may be used during brainstorming sessions, consisting of activities performed by partici- pants which are characteristic of different modes of interaction. Some sequences of these interactions may be considered more or less adequate than others. In particular, in order to get better results during brainstorming activities participants must respect certain rules when they write their ideas and when they consider notes written by somebody else. We argue that a multi-agent system can recognize different interaction modes and verify the respect of these rules by analyzing videos and notes produced by the participants in real time. Such a system must be trained as a machine learning system before being used during actual meetings. This system can simplify the role of the meeting facilitator. It can send a summary of the meeting situation, such as the proportion of each mode of interaction and identify behaviors that may need to be addressed. We present how feedback could be sent individually or addressed to the entire team. We will begin by presenting the interaction model, then propose an automatic recognition of these modes from video recordings and log analysis. We also address the necessity of rules and the structure of a multi-agent system which is able to verify whether or not the participants are respecting them. Finally, we propose how experiments could show the level of acceptance of such a system by users. The goal of this prospective research is to define a non-intrusive system that can be used during brainstorming sessions, based on an interaction model to enhance the quality of meeting results.

To supply a stable and efficient electricity, small-scaled wind turbine’s brake system plays an immense role in various wind speeds. Small-wind power generation systems are difficult to operate in strong wind region since the turbine could be over-rotated and damaged if the brake system is not robust enough to maintain a stable angular velocity. Most of the small-scaled wind turbines use friction brakes to control the turbine speed for a stable electricity output. Since the friction brake are run out of time and needs frequent maintenance and eventually replacement, we introduce an eddy current based wind turbine brake system which is contactless with the rotor as an alternative to the friction brake system. The advantage of the proposed brake system is that the energy loss due to the friction will be reduced and will be more durable than the friction brake. The flow of this study is at first we did the analogical experiment of blade destruction to set to the maximum allowed angular velocity. Later, in order to verify the performance and stability requirement the mathematical implementation of eddy current brake system have done in DC-Green house for various wind penetration. Eventually the feasibility of eddy current brake system is confirmed in simulation results.

We describe an efficient system-level simulator that, starting from the architecture of a well-specified transmissive medium (a channel modelled as single-ended or coupled differential microstrips plus cables) and including the system-level characteristics of transmitter and receiver (voltage swing, impedance, etc.), computes the eye diagram and the bit-error rate that is obtained in high-speed serial interfaces. Various equalization techniques are included, such as feed-forward equalization at the transmitter, continuous-time linear equalization and decision-feedback equalization at the receiver. The impact of clock and data jitter on the overall system performance can easily be taken into account and fully adaptive equalization can be simulated without increasing the computational burden or the model’s complexity.

Vibrotactile feedback is increasingly becoming an essential feedback component in several non-medical and medical areas. One area that vibrotactile feedback has not been explored as an intervention tool is in sports science. In addition, vibrotactile feedback lacks scientific evidence as a feedback mechanism within the sports world. A portable vibrotactile feedback system was developed to understand how a human perceives vibrotactile feedback while performing walking and running tasks. The system incorporates a model-based simulation framework to check human motion and visualize key performance metrics. We performed a pilot study on twenty-six subjects to understand the accuracy of human perception of vibrotactile feedback using the system we developed. Here, we investigated the type, number, and location of haptic feedbacks that would yield better subject perceived accuracy during walking and running. Findings suggested that staggered vibrotactile feedback would lead to higher accuracy than continuous vibrotactile feedback especially when more than two motors were used. For the subjects perception accuracy for all motor combinations, we observed an average that was 9.3% higher for walking compared to running. For one motor, the perception accuracy decreased by only 3.38% while running compared to walking. The decrease was much more significant for higher combinations of motors. The decrease in the perception accuracy of the motor locations was significantly less for both staggered (p < 0.001) and one motor (p < modes.

In this paper, the vulnerabilities and the security attacks against vehicular networks, SDN architecture and some security solutions for SDVN are studied. Secondly, a complete and improved version of the secure HSDN-GRA routing protocol based on a distributed trust model is proposed where public keys of the vehicles are managed in a distributed way. Besides, in this approach, a weight is assigned to every vehicle, which is calculated from its freeload and its trust values per those of the neighbors. The trust value is deduced from the historical interactions stored in a log of communication errors. To measure the trust value, three unreliable behaviors occurred in a time interval are considered. The vehicle with the role of cluster head hosts a list of each vehicles misbehaviors forming a log of communication errors. A vehicle will be chosen as the next relay according to its weight. As a positive result of this complete proposed approach, the following security requirements are achieved: the vehicle’s authentication and the data integrity are guaranteed by a signature mechanism, whereas an encrypted function is used to ensure the confidentiality of the exchanged data. The goal is to protect the routing process against malicious and unstable nodes. Finally, the implementation details and simulation analysis are given, and a comparative study between the secure and the insecure HSDN-GRA is presented in the presence of a percentage of malicious nodes in the network. The perspective of managing non-collaborative vehicles is briefly introduced as future work.

This study built and tested a research model to determine the determinants that impact students’ actual use of the learning management system. A survey questionnaire was used to gather data from 148 university students who used LMS in their course of study. The structural equation model was used to analyze quantitative data. The study revealed that (1) performance expectancy, effort expectancy and institutional support positively impacted students’ actual use of LMS, (2) social influence and infrastructure support did not positively impact students’ actual use, (3) gender had a significantly moderated effect on the correlation between institutional support and actual usage of technology. This study added to existing studies on the use of UTAUT in explaining students’ actual use of technology in developing nations. Implications for practice, drawbacks and future directions are discussed.

One of the most critical challenges that large companies, small enterprises and research institutes face, when commercializing their innovations, is the transfer process at the moment of scaling up. These organizations often transfer their innovation to either existing business units or create a new business entirely. The process of transferring innovations to an existing unit is known as corporate venture, while creating a new business is called spinoff. Both processes have been studied separately, but not yet together and from different business sectors and countries. In order to understand both processes, this article compares the commercialization of disruptive innovations from these sectors: electronics, information technology, telecommunications, engineering, healthcare, biotechnology or research equipment. The article used multiple case study methodology from commercialization ¬projects carried out in large, small and medium-sized companies and research institutes based in Spain, Germany, UK and Finland. The findings showed that certain activities needed to be done at pre-transition /commercialization, transition/commercialization, and post-transition/commercialization phases to reach a successful transition. Furthermore, the study provides similarities between the corporate venture and spinoff approaches that include team formation, network development and getting the commitment from the company and stakeholders. Additionally, the article outlines divergences between the approaches which consist of innovation readiness, knowledge management or the activities of the post-transition phase. The article also provides insight for innovation scholars, commercialization practitioners, and business enterprises. Therefore, the article contributes to the commercialization of disruptive innovations.

One of the most critical challenges that large companies, small enterprises and research institutes face, when commercializing their innovations, is the transfer process at the moment of scaling up. These organizations often transfer their innovation to either existing business units or create a new business entirely. The process of transferring innovations to an existing unit is known as corporate venture, while creating a new business is called spinoff. Both processes have been studied separately, but not yet together and from different business sectors and countries. In order to understand both processes, this article compares the commercialization of disruptive innovations from these sectors: electronics, information technology, telecommunications, engineering, healthcare, biotechnology or research equipment. The article used multiple case study methodology from commercialization ¬projects carried out in large, small and medium-sized companies and research institutes based in Spain, Germany, UK and Finland. The findings showed that certain activities needed to be done at pre-transition /commercialization, transition/commercialization, and post-transition/commercialization phases to reach a successful transition. Furthermore, the study provides similarities between the corporate venture and spinoff approaches that include team formation, network development and getting the commitment from the company and stakeholders. Additionally, the article outlines divergences between the approaches which consist of innovation readiness, knowledge management or the activities of the post-transition phase. The article also provides insight for innovation scholars, commercialization practitioners, and business enterprises. Therefore, the article contributes to the commercialization of disruptive innovations.

All trucks heading into the paper mill MONDI, Slovakia, have to pass an automatic security check. It controls if storage of its wood load meets all standards of safety. Each truck is scanned by a group of 2D scanners. After that the inspection of timber load is done by a software with use of the data gained by these scanners. The security software is universal for all kinds of storage of timber loads. This article is dedicated to deal with a problem of classification a kind of wood storage on a semi-trailer. The classification is solved by training a convolutional neural network on datasets with recorded trucks of both kinds to learn patterns distinguishing them. The image classification is done with use of images recorded by a set of cameras. By determining a type of storage, it is possible to execute the safety check for a specific type of wood load with better result than the universal check.

This research work mainly presents the design and development of a small-scaled wheeled robot, which can be controlled using multiple controlling interfaces using some new technological trends. Raspberry Pi 3 as the main controller, Python as the programming language integrated with the Robot Operating System (ROS) and Virtual Network Computing (VNC) for screen sharing are utilized in order to control the robot. Laptop Keys, Graphical User Interface (GUI) on PC, Virtual Network Computing on smart phones, Joystick connected to Laptop using python integrated with Robot Operating System, Voice commanding through an android app integrated with python and ROS and Internet of Things using a customized webpage with Node MCU as the controller are the dominant control interfaces. A Local Area Network is established in order to communicate with the micro-controllers wirelessly. The robot can be controlled with multiple interfaces by using its corresponding commands. The robot is made to survive in five different paths, controlled by all the six methods and the time for each response obtained was appraised and illustrated properly.

As many digital documents are required in various environments, paper documents are digitized by scanner, fax, digital camera and specific software. In the case of a scanned document, we need to check whether the document is right sided or upside down because the orientation of the scanned document is determined by the orientation in which the paper document is placed. It is time-consuming for a person to check all the documents whether they are upside down. We propose an algorithm that can automatically determine upside down documents. The proposed artificial neural network-based method shows a high accuracy and efficiency in time for general documents. In addition, OCR-based method and CNN-based method were used to compare with the performance of the proposed method.

It is difficult to accurately segment brain MRI in the complex structures of brain tumors, blurred borders, and external variables such as noise. Much research in developing as well as developed countries show that the number of individuals suffering tumor of the brain has died as a result of the inaccurate diagnosis. The proposed article, a novel hybrid method improves segmentation accuracy. The proposed research includes three basic steps. In the first step, the adaptive filter based on mean and local variance is utilized for noise removal in the input images. It helps in de-noising to a different orientation and scale, creates numerous responses for all components in the medical images while preserving the edges. In the second step, the development of a hybrid method takes place. It is the combination of extended K-mean clustering and fuzzy C-mean clustering. The purpose of the research is to develop a hybrid segmentation structure of single-channel T1 MR Images for multiform benign and malignant tumors. It removes the limitation of prefixed cluster size which helps in improving the segmentation accuracy by reducing the sensitivity of the clustering parameters. In the third step, the morphological non-linear operation performed for the removal of the non-tumor part. The proposed approach is evaluated against various statistical parameters such as mean, standard deviation, entropy, correlation, homogeneity, smoothness and variance. The parameters result predicts a greater balance between the automated tumor areas extracted by radiologists with the tumor areas extracted by the proposed method. The findings show that the proposed hybrid method achieves a 98% level of segmentation accuracy.

This article considers the creation of a program / website as an example of a centralized system for all universities in order to more easily familiarize an applicant and / or student with the internal politics and capabilities of the university. Existing problems in the training system are examined, why distance learning is relevant, what problems exist in it and how they can be solved. Based on the proposed distance learning projects, an argument is built on its meaninglessness without further advancement, and how a website concept can help solve this problem. The concept of the website and its possible implementation using existing analogues in other areas that successfully complete the tasks are considered. Theoretically, using the proposed methods, the concept will simplify the choice of a further place of study for schoolchildren and applicants. The method consists in parsing the desired university website into the necessary categories: a number of specialties, disciplines, foreign programs, distance learning materials and so on. This will allow you to create a library of universities, their materials and open data (specialties, disciplines), without coming to excesses, such as creating a video hosting service for broadcasting recorded disciplines, less data to be stored, and more.

Modern microcontrollers are capable to realize not only traditional PID-regulators but also adaptive ones. Object of control parameters estimation is the biggest part of adaptive control from the point of view of time consumption. The ways to reduce this time for digital control systems based on ARM-CORTEX 32-bit and 64-bit processors are shown in the article. These ways include source code refactoring, using vector registers and parallelism of code. As result of program improvement, a new algorithm for least squares method was suggested. Intrinsics for vector operations and OMP directives were added to the program to realize data and code parallelism. All options were tested for time consumption in order to find out the best decision. The program suggested may be useful while realizing adaptive controller based on single-board mini-computers and microcontrollers

The European drone market has been showing steady growth year after year. New EU drone rules will come into force as of July 1st, 2020, with the European Union setting itself the target to replace national rules with a common regulation with the ultimate goal of creating a harmonized European drone market. This study will clarify that the EU’s regulatory framework covers all types of existing and future drone operations, creating an international market for unmanned aircraft services. This move will facilitate the enforcement of citizen’s privacy rights and address security issues and environmental concerns to the benefit of the EU citizens. Moreover, this study will show that national legislators are now faced with the difficult task of replacing their national regulations with EU rules, however these were drafted so fast that they still leave a number of issues to be decided on by national legislators. The method of this study comprised of content analysis of existing legislation. The current doctrine were confronted with existing regulations, documents, and materials.

Analytical researches on a potential performance of multipath multiple-input multiple-output (MIMO) systems inspire the development of new technologies that decompose a MIMO channel into independent sub-channels on the condition of constrained transmit power. Moreover, in current studies of inter-symbol interference (ISI) MIMO systems, there is an assumption that channel state information (CSI) at receivers and/or transmitters is perfect. In this paper, we propose a hybrid design of precoding and equalization schemes based on the unweighted minimum mean square error criterion that not only eliminates the ISI but also improves the system performance. Additionally, the impact of imperfect channel knowledge at receivers on the system performance of MIMO ISI system is investigated. The simulation result shown that the proposed hybrid design of precoding and equalization with shared redundancy outperforms the conventional method in all considered scenarios. Furthermore, the proposed and the conventional schemes are extremely sensitive to the CSI factor, the performance of these systems is quickly deteriorated when the accuracy of channel estimation decreases.

The increase in the number of elderly people requires multiple efforts to maintain their well-being and health. A wide variety of products and services have been created to enable seniors to live at home for as long as possible. The market success of these solutions depends on acceptance by the different stakeholders. Older people are reluctant to change their environment, most notably their home. Solutions must provide a benefit and/or reduce risks related to their everyday life in order to be accepted. Design methods are mainly focused on needs analysis, while acceptability assessment models are based on the study of benefits. A need may also correspond to a risk that may be present in the initial situation and that has to be eliminated or reduced. The notion of risk is not sufficiently integrated in these models. This paper proposes a new approach to analyze the actual situation of elderly people at home based on risk analysis. The objective is to contribute to the design of solutions that will be more readily accepted by this population. A model for estimating the risk of falling has been proposed. The probability of two elderly people falling in their home is assessed using this model. The design and improvement of solutions are explored using the results obtained.

Several drive mechanisms for different robots are at hand in current days. Bicycle steering, Ackerman steering, differential drive are some principal drive mechanisms that are being deployed in robots these days. The differential drive needs the wheel rotations to be updated very frequently. But it is most commonly deployed on the robots with two wheels and casters, as discussed in this work. It also can be used to have an independent control for each of the wheels with independent control signals. This work deals with the modeling of the differential drive mechanism for a robot with two main drive wheels and two casters, which takes the angular orientation of the steering wheel as input. For simplicity, this work considers that casters have no influence on any aspect of the differential drive. An adaptive model, whose output depends on the real-time input from the gamers steering wheel and produces required output has been formulated. This work differs from the other differential drives in the context that the steering wheel and the robot wheels have no physical connection. The proposed model has been implemented in python and integrated with the Robot Operating System (ROS). The steering wheel, which is used to generate commands using, is attached to the controller at the control station and the ROS_Node thus created is used to read the values from the steering and generate commands for each of the left and right wheels. These commands are transferred to the controller on the mobile platform, which in turn generates control signals for actuators. This work also deals with the deployment of the proposed model using the Universal Robot Description Format (URDF) of the robot in the Gazebo simulation and evaluating it using the Nitho Drive Pro steering wheel. To prove that the differential drive mechanism can be used to control the robot efficiently in any type of terrain, a ROS python node is used to control and maneuver the robot.

This paper describes the design method of a nonlinear flight controller for a fixed-wing UAV with a thrust vectoring system (TVS) using the backstepping method. The flight dynamics of the UAV exhibits strong nonlinear coupling behavior between its translational and rotational motion. The backstepping algorithm has been successfully applied to controller design for such a nonlinear system. However, the main idea of the method is to use some of the state variables as virtual control inputs that need ungeneratable forces by the UAV. To overcome this problem, we use the TVS that can generate thrust in an arbitrary direction. Numerical simulation is performed to confirm the effectiveness of the proposed control method for a fixed-wing UAV with the TVS.

The paper proposes the design and simulation of a 6 Degree of Freedom (DOF) robotic arm, tailored for the coconut crop harvesting, assistive robots like wheelchairs and Home robots, Search and rescue robots for disastrous environments, Collaborative robots for research use. A kinematics-based solution has been developed for the robotic arm which makes it easier to operate and use. Keyboard, GUI, Joystick are the three control interfaces used in the paper. The robotic control interfaces proposed in the paper were developed using the Robot Operating System (ROS). The 6- DOF articulated robotic arm was designed and visualized in RVIZ. The kinematics helped for the easy manipulation of the robotic arm with the end effector. The methodologies proposed in the research work are easy to operate and inexpensive. The designed 6 DOF robotic arm, the first three DOFs are for positioning of the robot’s arm, while the residual three are used for manipulation of the gripper.

Nowadays, process automation and smart systems have gained increasing importance in a wide variety of sectors, and robotics have a fundamental role in it. Therefore, it has attracted greater research interests; among them, Underactuated Mechanical Systems (UMS) have been the subject of many studies, due to their application capabilities in different disciplines. Nevertheless, control of UMS is remarkably more difficult compared to other mechanical systems, owing to their non-linearities caused by the presence of fewer independent control actuators with respect to the degrees of freedom of the mechanism (which characterizes the UMS). Among them, the Furuta Pendulum has been frequently listed as an ideal showcase for different controller models, controlled often through non-lineal controllers like Sliding-Mode and Model Reference Adaptive controllers (SMC and MRAC respectively). In the case of SMC the chattering is the price to be paid, meanwhile issues regarding the coupling between control and the adaptation loops are the main drawbacks for MRAC approaches; coupled with the obvious complexity of implementation of both controllers. Hence, recovering the best features of the MRAC, an Artificial Neural Network (ANN) is implemented in this work, in order to take advantage of their classification capabilities for non-linear systems, their low computational cost and therefore, their suitability for simple implementations. The proposal in this work, shows an improved behavior for the stabilization of the system in the upright position, compared to a typical MRAC-PID structure, managing to keep the pendulum in the desired position with reduced oscillations. This work, is oriented to the real implementation of the embedded controller system for the Furuta pendulum, through a Microcontroller Unit (MCU). Results in this work, shows an average 58.39% improvement regarding the error through time and the effort from the controller.

Our research investigates the use of causal modeling and its application towards mapping out cybersecurity threat patterns. We test the strength of various methods of data breaches over its impact on the breach’s discovery time as well as the number of records lost. Utilizing a Causal Modeling framework, we simulate the isolation of confounding variables while testing the robustness of varying estimators. The motivation is to shed a unique insight provided by the usage of Causal Modeling in cybersecurity.

Face explicitly provides the direct and quick way to evaluate human soft biometric information such as race, age and gender. Race is a group of human beings who differ from human beings of other races with respect to physical or social attributes. Race identification plays a significant role in applications such as criminal judgment and forensic art, human computer interface, and psychology science based applications as it provides crucial information about the person. However, categorizing a person into respective race category is a challenging task because human faces comprise of complex and uncertain facial features. Several racial categorization methods are available in literature to identify race groups of humans. In this paper, we present a comprehensive and comparative review of these racial categorization methods. Our review covers survey of the important concepts, comparative analysis of single model as well as multi model racial categorization methods, applications, and challenges in racial categorization. Our review provides state-of-the-art technical information concerning racial categorization and hence, will be useful to the research community for development of efficient and robust racial categorization methods

The paper presents sharing several of experiences and practices on smart robotic application for overhead transmission line maintenance and inspection. First, the pilot-line pulling robot is an invention used to pull a pilot line which is an important step for additional high voltage conductor installation. The puller robot can traverse the overhead ground wire, OHGW, and pulls a lead line via a set of cradle blocks at intervals, carrying the line above the ground. The robotic puller passes over barriers below the power line, such as the road with traffic, power distribution lines, river, or vegetation making tasks achieved conveniently, safely, and rapidly without impact on nearby communities. The robot was further utilized to pull a lead line/conductor crossing over the electrical substation without interrupting energy and pull a lead line for the improvement of transmission line ground clearances. The developed pilot-line pulling robot has been accredited as the corporate best practice; the standards for innovation, operation, and maintenance are archived for works at all EGAT transmission line operation & maintenance units nationally. Moreover, EGAT was now jointly investigating with universities on a new robotic device for aerial transmission line inspection. The target of the research is to create a mobile robot prototype for inspection of overhead power lines. The inspection robot shall crawl along the ground wire and transpose autonomously across installed equipment on the ground wire, such as vibration dampers, suspension clamps, compression dead ends, etc. In addition, the inspection robot is able to take photos and videos during a transmission line inspection in both offline and online features. Using the robot, transmission line inspection’s labor cost can be reduced, and the new method helps improve patrol and inspection efficiency, comparing to the conventional manpower method. Trough utilization of the new maintenance and inspection robots, utilities can minimize transmission line operation & maintenance budget.