Volume 5, Issue 2

This paper focuses on the issue of distributed reinforcement learning (RL) for decision-making in cooperative multi-agent systems. Although this problem has been a topic of interest to many researchers, results obtained from these works aren’t sufficient and several difficulties have not yet been resolved, such as, the curse of dimensionality and the multi-agent coordination problem. These issues are aggravated exponentially as the number of agents or states increases, resulting in large memory requirement, slowness in learning speed, coordination failure and even no system convergence. As a solution, a new distributed RL algorithm, called the ThMLA-JAG method, is proposed here. Its main idea is to decompose the coor- dination of all agents into several two-agent coordination and to use a team-mate model for managing other agents’ experiences. Validation tests on a pursuit game show that the proposed method overcomes the aforementioned limitations and is a good alternative to RL methods when dealing with cooperative learning in mics environments while avoiding collisions with obstacles and other learners.

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News companies have a need to automate and make the process of writing about popular and new events more effective. Current technologies involve robotic programs that fill in values in templates and website listeners that notify editors when changes are made so that the editor can read up on the source change on the actual website. Editors can provide news faster and better if directly provided with abstracts of the external sources and categorical meta-data that supports what the text is about. To make categorical meta-data a reality an auto-categorization model was created and optimized for Swedish articles written by local news journalists. The problem was that it was not scale-able enough to use out of the box. Instead of having this local model that could make good predictions of the text documents, the model is to be deployed in the cloud and an API interface is created. The API can be accessed from the tools where the articles is being written and therefore these services can automatically assign categories to the articles once the journalist is done writing it. To allow scale-ability to several thousands of simultaneously categorized articles and at the same time improving the workflow of deploying new models easier the API is uploaded to Sagemaker where several models are trained and once an improved model is found that model will be used in production in such a way that the system organically adapts to new written articles. An evaluation of Sagemaker API was done and it was concluded that the complexity of this solution was polynomial.

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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.

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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.

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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.

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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%.

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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.

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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.

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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.

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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.

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Due to the attacks’ growth on sensitive databases by deploying advanced tools, beyond access control and authentication mechanisms, the database encryption remains a useful and effective way to ensure robust security of data stored within it. Any database encryption solution is based on a specific encryption model that determines how data is encrypted inside it. A relevant database encryption model must necessarily adopt a strong security policy of data encryption keys. It determines how these keys are generated, stored, and protected. In this work, we will implement an original solution that protects the encryption keys when encrypting data occurred at the Database Management System level. Our solution suggests protecting the keys by their encryption with other ones named Master Keys, which are generated according to the encryption granularity defined by the database encryption model. The proposed solution protects the keys of two database encryption models: at the level of the columns and the level of tables.

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Circular data are common in biological studies which are involved angle and direction measurements. An outlier in circular biological data mostly related to the abnormality of the data set. The existence of outliers may affect the final outcome of a data analysis. Thus, an outliers’ identification method is essential in circular biological data to determine the stage of abnormality for the sample that has been studied. Past studies were mostly focusing on detecting outliers for multivariate circular biological data. However, identifying outlier for univariate data is more essential in the abnormality stage investigation. In this study, outliers’ identification methods for univariate circular biological data have been reviewed. The strength and weaknesses of the methods are investigated and discussed.

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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.

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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.

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It was analyzed certain information about cyberattacks in Latin America and methods to counteract the aggressions that affect services, data and infrastructure. The problem is the cyberattack on information networks where there is interdependence between processes, people and devices within public organizations with the negative consequence of denial of services. The objective is to propose a protection model against cyberattacks in public organizations in Latin America to minimize the denial of public services. It was applied the deductive method and exploration to examine the information of cited articles. It resulted a General Model of Protection against Attacks, a Prototype of a network, a Algorithm in flowchart to minimize the attack arrival and a Formula of probability of attack arrival. It was concluded that in order to maintain the continuity of services and activities of public organizations, secure platforms must be in place to monitor and minimize possible attacks; our proposal has an attack detection accuracy of 87.49%.

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Lead concentration on surface soil (0-20 cm), root and aerial part of natural and cultivated pastures were evaluated, in the rainy season (March 2018), collected in 20 sites of a rural community located 20 km from the La Oroya metallurgical complex , which has been emitting to the environment particulate material with heavy metals since 1922. Lead concentration was determined by flame atomic absorption spectrometry. The data was statistically processed in SPSS 23. Lead levels in the soil, root and aerial part of the cultivated pastures were 224.75 ± 39.41, 169.13 + 58.79 and 20.73 ± 2.52 mg / kg (p <0.01). In natural pastures values were 210.87a ± 40.37, 184.36b + 52.66 and 19.47c ± 3.12 mg / kg (p <0.01). There are no differences between cultivated and natural pastures. Lead transfer factor from soil to root of cultivated and natural pastures was 0.75 and 0.87. Lead transfer factor value from soil to aerial part of cultivated and natural pastures was 0.092 in both. High lead content in soil and aerial part of the pastures used as food for high Andean cattle is a public health problem; livestock products produced in these soils would not be fit for human consumption.

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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.

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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.

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In many countries and regions in the world, earthquakes are one of the most common natural disasters, which affect both human life and property. To avoid negative effects of earthquake, the nonlinear response of structures under dynamic loading should be accurately modeled to investigate their actual behavior under earthquake loading to ensure safe and sound design. To yield proper results, accurate representative structural models should be developed for the elements resisting lateral loading and representative ground motions pertaining to the site should be employed. Then relating such response to that of elastic behavior should be conducted to correlate response modification factors in design codes with actual response. The main objective of the research is to investigate the effect of basements existence and considering soil pressure on retaining walls on the seismic response modification factor for reinforced concrete structures, based on ABAQUS software analysis results using pushover analysis and time history analysis. For this purpose, experimental results of individually tested RC structures are used in order to verify modeling technique to be adopted.

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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.

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Concept of university higher education quality is linked to the relevance of an educational project that promotes institutional transformation to improve the comprehensive training of new professionals. In this context, the research objective is to determine the graduates satisfaction level, trained with curricula 1979, 1985 and 1995 who have more than 20 years of graduation from Zootechnical Faculty of the Universidad Nacional del Centro del Perú (UNCP), the main deficiencies perceived by graduates in curriculum development, areas of knowledge that should be reinforced and the reasons for dissatisfaction, and have more evidence for curriculum improvement. These plans respond to a traditional educational model, by objectives, without competence assessment system, repetitive learning, and insufficient laboratories implementation. A questionnaire was applied with questions to know the employment situation, continuing education, curricular relevance, areas to be reinforced and satisfaction level with training received in the study years. Sixty graduates in the research were considered, with systematic probabilistic sampling carried out in graduates meeting; This sampling is very efficient when there are a limited number of subjects that have the same qualities as the target population, that is, graduates of the UNCP Faculty of Zootechnics trained with 1979, 1985 and 1995 curricula. Data was analyzed in SPSS 23. Research provides information to improve the educational quality of UNCP zootechnical engineering academic program.

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This research to applying the application of e-smart farming to control the sprinkler irrigation on agricultural land. This study aims to be able to help farmers to solve the watering problems that are manually carried out into watering done automatically and controlled, besides that this research also obtained data about the level of moisture content from sensor soil moisture, air temperature from the temperature sensor, and rainfall data from Rain Sensor as well as setting the right time using automatically scheduled Real-Time Clock (RTC) for watering time. This system is a combination of hardware and software components. The hardware part consists of systems and software embedded in the form of android-based applications. Consists of three sections, namely the Sensor block, the farm station controller, and the home station controller at the farmer’s house. The implementation of the smart farming application in this study obtained quite good results. The final results of this study indicate that the tools applied can assist farmers in implementing smart farming systems. The results can be seen in the success of several temperatures, soil humidity, and rain sensor tests. Moreover, there is no barrier between smart farming applications on the base station and the farm station using 2.4GHz Wireless ZigBee, and sending data in real-time from the sensor block on the farm station server using ESP8266. Besides, the sprinkler watering system also has no problems when watering agricultural land when receiving orders from the application.

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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).

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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.

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This paper studies and compares the effectiveness of four different features and their combinations on the recognition accuracy of handwritten Bangla characters. The longest run, chain code histogram, shadow, and Gabor filter-based features and their eleven (11) combinations were tested on a standard Bangla database of 15; 000 basic handwritten characters to compare their recognition performances. From the experiments performed, it was observed that the combination of the longest run, chain code histogram, and the shadow features (having feature vector sizes of 20, 20, and 16 respectively) produce the highest recognition accuracy of 84:01%. Furthermore, inclusion of a feature with a large vector size compared to the other features in the combination generally dominates the recognition accuracy. In our case, inclusion of the Gabor filter-based features with a vector size of 1024 in the combination produced a recognition accuracy of 69:71%, which is worse than the accuracy obtained using the other three features. The analysis of the results indicates that the combinations of different feature vectors produce better accuracy as long as the sizes of each individual feature vector is comparable with each other in the combination.

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Electrostatic suspension systems have great potential applications in contactless transportation objects since they allow many different materials to be suspended. The electrostatic suspension will be widely applied in practice if the system cost is inexpensive. This paper presents an electrostatic suspension system controlled by using pulse width modulation (PWM). The use of PWM in electrostatic suspension system will reduce the system cost since inexpensive switching power amplifiers could be applied instead of linear analogue power amplifiers, which are bulky and costly. The simulation and experimental results are performed and showed that PWM can be used effectively to control the position of the levitated object in the electrostatic suspension.

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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.

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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.

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In the present article, we introduce a foveation-based optimized embedded and its optimized version image coders thereafter called VOEFIC/MOEFIC and its related foveation wavelet visible difference predictor FWVDP coding quality metric. It advances a visually advanced foveal weighting mask that regulates the wavelet-based image spectrum before its encoding by the SPIHT encoder. It intends to arrive at a destined compression rate with a significant quality improvement for a disposed of binary budget, witnessing separation, and a foveal locale that locates the object in the zone of concern ROI. The coder embodies a couple of masking achieves build on the human psycho-visual quality criteria. Hence, the coder administers the foveal model to weigh the source wavelets samples, reshapes its spectrum content, adapts its shape, discards or somewhat shrinks the redundant excess and finally enhances the visual quality. The foveal weighting mask is computed indoors wavelet sub-bands as come after. First, it administers the foveal wavelet-based filter depending on the intention point so that it removes or at least reduces the imperceptible frequencies around the zone of concern. Next, it augments the picture contrast according to wavelet JND thresholds to manage brightening and nice the contrast above the distortion just notable. Once refined, the weighted wavelet spectrum will be embedded coded using the standard SPIHT to reach a desired binary bit budget. The manuscript also advances a foveation-based objective quality evaluator that embodies a psycho-visual quality criterion identified with the visual cortex framework. This investigator furnishes a foveal score FPS having the power of detecting probable errors and measuring objectively the compression quality. Keep in mind that the foveal coder VOEFIC and its visually upgraded variant MOEFIC, have similar complexity as their reference SPIHT. In contrast, their gathered data highlight the visual coding advancement and the boost ratio purchased in its quality gain.

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Demak is located on the north coast of Java, precisely in Central Java Province, Indonesia which has many problems related to erosion and shoreline degradation. This study attempts to analyze, identify, and select the materials to build eco-friendly permeable breakwater in Demak. The research was conducted during 2014, consist of several activities, i.e. identified the condition of breakwaters position, materials, and construction, did literature study of identification type breakwaters, study area, sediment, chemical reaction, then reverse design and modification for eco-friendly permeable breakwater. The result is a design of eco-friendly permeable breakwater which used a material of PVC pipe and Bamboo. PVC has excellent chemical resistance, also will increase sedimentation process and accelerate coastal changes towards the sea. Effectiveness level of breakwater made from combination of tire and PVC was 62%, and reveal to be more economical than other general-purpose plastics such as PE, PP, or PS.

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This work describes a case study carried out in an automotive company. The main objective was to increase the productivity of the last workstation of an assembly line by implementing an AGV System to transport finished goods to the warehouse. A comprehensive analysis of Value Added and Non-Value Added activities were performed to understand the current state of the workstation. By using the Spaghetti Diagram, the worker’s movements were mapped and quantified. To eliminate motion and material transport and therefore increase productivity, an AGV system was implemented. To design this particular system, it was necessary to determine the required number of AGVs and their capacity, picking and delivery locations and the flow path. Activities such as transporting the containers and moving around to pick up the same containers were eliminated, thus contributing to a better ergonomics and an increase in safety. The Cycle Time was also reduced and therefore productivity was increased.

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The digital factory is a concept signing a new era for industry, the so-called Industry 4.0, in which ordinary production systems like manufacturing plants, machineries and utilities are being equipped with diagnostic and sensitive instrumentation to be connected to digital shared networks. This data-sharing, trough the big data management techniques, is a fully integrated base on which digital tools can be installed and exchange information. Data stored from physical world of machines can be redirected to simulation environments like Digital Twins and can be inspected, for several purposes like predictive analysis, by humans too. On top of these scopes, within the realization of an Internet of Things, there is safety, especially in industrial sites where injury risk for operators and workers is a key factor for production sustainability. This paper, starting from a tested case study in mechanical stressed monitoring, focuses on the application of upgraded augmented reality systems for safety practices, expanding the area of interest to electric and overheating risk mitigation in electrical equipment and to emergency management.

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Job tenure is an important factor for both employees and employers. Sometimes, for employees, this time is a criterion in starting new job, and also for employers when they have to hire new employees. It measures the length of time that employees have been in their current job or with their current employer. Analyzing factors, which affect the job tenure, is important for companies, as well as for employee.
Job tenure is a duration concepts, so we have applied survival analysis to model the tenure for Albanian employees, in several different private and public companies.
First, Kaplan-Meier method is used to estimate the survival function for time. Then Cox proportional hazards model is used to assess the impact of the predictors in job termination. This study demonstrated the important role that the current age of the employee, the age at which he started the job, salary, gender, position, education, marital status and years of work in front of the current position may have on job tenure.

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Currently, there is a growing interest for applying gamification in e-learning due to innovations in technologies and pedagogies. However, motivation and engagement related problems can arise when the gamification elements are not personalized to match the individual’s needs. Therefore, this research proposes a Hybrid Learning Model that combines both Gamification and Personality Traits to increase academic achievement and motivation for students who are studying foreign languages online. The methodology for the Hybrid Learning Model includes three different stages: pre-play stage where the students’ personalities are gathered using the Big Five Personality questionnaire, gameplay stage where students’ dominant personalities are examined to create gamified learning systems based on the Felder-Silverman Learning Style Model, and the post-play stage where the effectiveness of the Hybrid Learning Model is measured through a recall test to measure achievement and an ARCS motivation questionnaire to measure motivation using various statistical analysis. The Hybrid Learning Model is applied to a language learning web application named VocaManager and tested the Korean vocabulary skills of non-native students who were learning Korean at a local language center in Indonesia. Using SPSS software, the results showed that students who studied under the Hybrid Learning Model had a significant improvement in both their learning achievements and motivation. In addition, the research revealed a significant positive correlation between students’ motivation and students’ academic achievements.

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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.

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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.

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The high flow of vessel traffic affects the difficulty of monitoring vessel in the middle of the sea because of limited human visibility, occurrence of vessel accidents at the sea and other illegal activities that illustrate abnormal vessel behavior such as oil bunkering, piracy, illegal fishing and other crimes that will continue and will certainly have an impact on losses in several aspects. the author collects studies using Automatic Identification System (AIS) data as a basis for analysis to see the behavior of vessels at the sea, in addition to that AIS data can also be combined with other sensor data to strengthen monitoring of vessel movements at the sea, this is very supportive in detecting the anomalous behavior of vessel that often occur outside the reach of human vision or the sea patrol on duty. This paper uses the Systematic Literature Review (SLR) method in identifying, evaluating, and interpreting various methods of studies related to vessel anomalous behavior at the sea the author highlights several methods that are always applied to studies that already exist in detecting vessels anomalous behavior, the study detected the movement of vessel with AIS data from the history of vessel locations and fusion with another sensor in seeing movements of abnormal vessel behavior through patterns that were formed. This paper refers to various studies and reviews some of them about the use of AIS track data history in vessel including combining with other data to detect anomalous behavior of vessel, the results of the analysis are used to find out activities that have the potential for illegal activities or other crimes that can be detrimental and can be used as decision making, the authors hope the results of this paper can be an option to be applied to the surveillance system of vessel around the territorial waters in order to guard against crime and other illegal behavior

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Middleboxes like load balancers are being used by all the corporations to manage and support their infrastructures. These devices see a large amount of bandwidth every day. This might include a range of protocols which might be varying from network layer to the application layer. This traffic can be corrupt or malicious thus causing these devices to fail or get exploited. Citrix NetScaler Application Delivery Controller (ADC) is one of such ADC which provides supple transportation services for conventional, containerized and microservice applications from the data centre or any cloud. NetScaler supports robust security, excellent L4-L7 load balancing, authentic Global server load balancing (GSLB), and enhanced uptime. Scapy is one of the most powerful and interactive packet manipulation software. Scapy is a powerful network manipulation module which is distributed as a python module. Python being a powerful scripting language helps in exploring this in various use cases. In this paper we discuss using Scapy with Python to script application layer protocols with controlled packet structure which helps in testing these middleboxes. We use these modules to explore Citrix Netscaler ADC which is widely being used. Our present work involves development of server-client Model for the following protocols namely FTP, HTTPS and TFTP. FTP protocol developed using scapy has support for both IPv4 and IPv6. All these scripts built using scapy are open sourced.

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The purpose of this research is to build an android based pathfinding adventure game where user gets information about Indonesian culture, especially the traditional houses including the folk songs and the traditional weapons in certain areas. The method used is by questionnaires, interviews, observation, and literature study. This application also implements the A* algorithm to solve the pathfinding problems. The result of this research is “The Adventure of BipBop” app that can make the user can feel the experience of playing that is not only entertaining but also as a medium to convey about the culture of Indonesia and help preserve the traditional house of Indonesia. Most of the respondents find out that the application can provide Indonesian culture well (91.7%). Furthermore, this application can realize about 84.5% of players to help preserve the traditional culture in Indonesia.

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This current situation will affect the future, technology models that are unthinkable or which impossible to happen pops up one by one. Like the hologram, this technology began to develop as a solution to increase user comfort in operating a system that is needed. This paper explains the development of hologram technology that is currently available and what the prediction of future technology models will be.

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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.

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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.

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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.

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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.

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In this work, an integrated metamaterial filter design in close proximity with monopole antenna is proposed for vehicular communication applications. A cylindrical screen formed by an array of metamaterial cells is designed to be reflective at 5.9 GHz in order to enhance antenna performance in intelligent vehicle transport systems. The unit cell proposed design based on Frequency Selective Surface (FSS) is made of a square loop element glued to a thin substrate to ensure a band-stop filtering behavior. This geometry is symmetrical providing the advantage of polarization independency and exhibiting angular stability up to 45? for both Transverse Electric (TE) and Transverse Magnetic (TM) modes. More importantly, antenna gain and directivity enhancement are illustrated when the cylindrical FSS layer is added at a small distance from the monopole radiator. Antenna bandwidth reduction is also detected due to the presence of the added FSS layer which is suitable for Vehicle to Vehicle (V2V) communications.

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This paper investigates the in plane behavior of unreinforced masonry (URM) walls externally strengthening on both sides by different configurations of unidirectional carbon fiber reinforced polymer (CFRP) wraps. In order to evaluate the effectiveness of using the strengthening systems to improve the in plane behavior of masonry walls, the experimental program was conducted by testing four specimens. Initially, URM wall without retrofitting system; considered as a reference; was tested. The other specimens were retrofitted on both sides by different configurations of unidirectional CFRP wraps. Walls were tested following diagonal tensile (shear) test method. Then the effect of position, spacing, and reinforcement ratio on ductility, stiffness, shear behavior and failure modes of URM wall were evaluated. Experimental results confirmed the effectiveness of using CFRP in improving energy dissipation, strength, stiffness and ductility of URM wall. Furthermore, the strengthening system affected in a direct way the shear capacity and the deformability of URM walls.

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Unreinforced masonry (URM) wall is one of the oldest types of walls used around the world. During earthquakes, URM walls present a real danger to life safety due to their behavior characterized by a brittle failure caused by their feeble shear resistance to in-plane loads, which make their strengthening necessary. Numerous studies had been used fiber reinforced polymer (FRP) as strengthening systems to upgrade the seismic behavior of masonry walls. In this study, the effectiveness of using carbon fiber reinforced polymer (CFRP) to increase the energy dissipation and the load carrying capacity of URM walls subjected to in-plane loading is experimentally investigated. Tests were carried on five walls subjected to diagonal compression loadings, one wall was considered as a reference and the other were retrofitted by different configurations of unidirectional CFRP wraps. Despite the advantages associated with the use of such systems, it remains expensive to use, therefore in this study, different ratio and configurations of CFRP wraps were used to reinforce masonry walls to enhance their resistance with less costs. The parameters under investigation are the dimensions, the number and the orientation of CFRP layers. It was concluded that the CFRP enhance the shear resistance and the deformability of URM walls. Results show The CFRP wraps had a significant influence on the URM wall behavior. Important amelioration of deformations and ultimate shear strength were observed when the specimen reaches its peak load, it was determined that the use of CFRP wrap even in smaller ratios increased ductility, the load-bearing capacity and the in-plane shear strength capacity of the masonry walls. The compressive strength of the strengthened walls had experimentally observed to be 147.31% to 319.35% higher than URM wall. The CFRP wraps presents an important solution for the improvement of the in-plane behavior of masonry walls.

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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.

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The possibility to apply non-linear transformation of the Wilson-Hilferty type to the Pois- son random variable is investigated using an analytic approach, in order to improve the convergence towards the large-parameter Gaussian limit. Considering the already existing non-linear transformation for the Gamma distribution, the original Wilson-Hilferty and a higher-order transformations are showed and approximations for the Gamma function are illustrated. From this, an approximate algorithm which exploits standard Gaussian random numbers is established, in order to generate Poisson random numbers of any parameter m. The algorithm performance is also assessed. The convenience of this approximate approach it resides in the fact that simulations often could be computationally demanding so that optimized algorithms have to be adopted for the efficient extraction of Poisson random numbers with variable parameter m.

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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.

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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.

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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.

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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.

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The huge growth in cloud storage utilization over the past years has made a big demand for an advanced technique and strong tools to make services even more practical and secure. Data privacy in cloud computing has become one of the biggest concerns for both individuals and organizations which adds more pressure on cloud service providers to gain more trust. This paper surveys various privacy-preserving techniques in cloud computing fields, and addresses the highlights and tools used in each technique with an explanation of what and why these tools were used. This work aims to focus on the most innovative and strongest techniques that researchers has figured and tested so far.

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The reformation of energy hubs has significantly augmented the apprehensions about the levels of dependency between different energy sources which often can also be discussed as independent systems conventionally. This research brings focus on the formulation and analysis of an integrated system with bi-directional energy conversions and its effects on the stability of the system for the benefit of overall secure and cost-effective operations. A general unification approach is adopted for the integration of two energy systems to execute optimal flow analysis in the form of one system based on Newton-Raphson scheme. PV solar energy is added into the system via electrical power system (EPS) to analyze the effects of renewable energy on electric network. A case study is presented to analyze the operational status of EPS and natural gas system (NGS) and effects of different factors on each system. The applicability of the proposed method is established by analysis of 20-Node Belgian gas network combined with IEEE-39 test system. The proposed method verifies not only that integrated systems with P2G capabilities and bi directional conversion increases the rate of smooth and reliable operations significantly but also discusses the limitations still present.

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This is era of new technology; most of information is collected from internet, web sites. Some people uses data from research papers, thesis, and website as it is and publish as their own research without giving proper acknowledgement. This term is known as plagiarism. There are two types of plagiarism detection methods, i) Extrinsic plagiarism detection ii) Intrinsic plagiarism detection. Through extrinsic plagiarism utilizing reference corpus plagiarism is observed, while in intrinsic plagiarism identification, using author’s writing style, plagiarism can be identified. If the anonymous text is written by unknown author. By using authorship analysis we can find original author of text. Authorship analysis is having three types i)Author identification ii) Author characterization and iii) Similarity detection. This paper mainly focuses on author identification for Marathi language. To calculate projection in two different files, we used feature vectors of main author file and summary file of other authors. The result of average projection shows, there is similarity in main author file and summary file of different authors, it also shows summary file of each author is having impact of main author file.

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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.

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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.

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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.

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Mobile banking and mobile payment are currently always used by customers for financial payments. With customer payments, it is usually easier to make payments with mobile payment, because it is more practical and direct than mobile banking. However, is the privacy of both platforms understood by the customer? Research questions to be answered: 1) What are the factors that influence privacy issues in mobile banking? 2) What are the factors that influence privacy issues with mobile payments? 3) What are the factors that influence confidence in mobile banking? 4) What are the factors that influence confidence in mobile payments? 5) Does the privacy factor influence the perceived privacy? 6) Does the confidence factor influence the perceived privacy? There are two research models and 12 (twelve) hypotheses for each model. Privacy risk, subjective norm, information management factors positive influence on privacy interest, and trust. Care about privacy and trust have a positive influence on mobile payment.

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Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution methods, as explored here, can improve these image analyses working on before or after convolutional neural networks. Our methods are focused on building better image qualities into the original image components so that these feature extraction methods become more effective when applied later. Our super-resolution preprocessing resulted in better deep learning in the number of classified objects, especially for small objects when tested on the VOC2007, MSO, and COCO2017 datasets.

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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.

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Dental plaque is considered a possible causative agent of major dental diseases. People must develop oral care skills at an early age with family support. This study aims to assist parents and to reduce children’s fear while cleaning their teeth. An interactive game challenges children’s brushing ability. Arduino modules and software platform was utilized to build a functional prototype. The status of the palm movements identified using a sensing module within brusher. When the cumulative number of swipes exceeds a specified target, the LED moves to the next position. Children became more attentive and adjusted to their corresponding tooth positions according to changes in the hippo’s dental light. The average brushing time increased to 226 seconds, with the assistance of the partner. An interactive novelty toothbrush with Bluetooth module was built and evaluated. The contribution of the work is observing children’s needs and guide them to brush their teeth from an intimate perspective.

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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.

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Time-series is a sequence of observations that are taken sequentially over time. Modelling a system that generates a future value from past observations is considered as time-series forecasting system. Recurrent neural network is a machine learning method that is widely used in the prediction of future values. Due to variant improvements on recurrent neural networks, choosing of the best model for better prediction generation is dependent on problem domain and model design characteristics. Ensemble forecasting is more accurate than single model due to the combination of more than one model for forecasting. Designing an ensemble model of recurrent neural network for time-series forecasting applications would enhance prediction accuracy and improve performance. This paper highlights some of the challenges that are faced by the design of the ensemble model of different recurrent neural network versions, and surveys some of the most relevant works in order to give a direction of how to conduct ensemble learning research in the future. Based on the reviewed literature, we propose a framework for time-series forecasting based on the using of ensemble technique.

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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.

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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).

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Jeju Island is the largest island of South Korea and has an independent electric supply system. The island has a special energy plan that realizes itself a carbon-free region by 2030. Wind and solar energy resources are considered as an important means. The introduction of weather-variable renewable energy generation sources into the electric power system makes it unstable. The main content of this study was to investigate the capacity factor of large scale renewable energy (solar, wind) power plants operated in Jeju Island during the electric power peak time. We can see their utilization rate or contribution rate during the power peak time by the value of their capacity factors. The largest 18 solar power plants (SPP) and 8 wind power plants (WPP) on the island were chosen and the 4, 12, 25, 50 and 100% electric power peak times were set for this study. There are two electric power peak seasons, summer and winter, in Jeju Island when the electric power demand arrives at peak. Generation of renewable energy plants depends on weather and the climates of the 5 regions of Jeju Island are a little different from one another. So, we investigated the difference between the average capacity factors of the 5 region’s renewable plants. WPPs showed a high contribution to the power grid only during winter peak time and SPPs did high contribution to the power grid only during summer peak time, while WPPs showed low contribution to the power grid during summer peak time and SPPs did low contribution to power grid during winter peak time. WPPs and SPPs have inter-compensation relation in the aspect to contribute to the power grid.

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Fraud, as regards means of payment, means the behavior of any legal or natural one that makes an abnormal or irregular use of a way of payment, elements of it or information contained therein, to improperly obtain an honest, service or enrichment, and or causing financial damage to the one that has distributed the means of payment to a user or a 3rd party; Contests in bad faith a legitimate payment order of which she is that the initiator. during this paper we are getting to propose an approach to managing the risks, it consists to mix a machine learning with an ontology-based on a payment system to succeed in this objective. Machine learning may be a field of study that improves their performance in solving tasks without being explicitly programmed by each. An ontology is that the structured set of terms and ideas that represent the meaning of an information field, whether by the metadata of a namespace, or the elements of a domain of knowledge.

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Flash memory reliability and the performance have been confirmed as an improvement in the storage subsystem technological advancement, especially in supporting an embedded system solution. Conversely, the main constraint of the storage device is the erase-before-write characteristic in handling both write and re-write I/O operations. More attention must be taken into consideration to handle both I/O operations. To overwhelm this constraint, a time-consuming garbage collection scheme has been introduced. This paper presents an optimized cleaning scheme that significantly reduces the required cleaning collection cost without interfering the memory I/O operations. The candidate sector to be erased is being determined by a score factor together with an erasure count before selecting the actual victim sector to be cleaned. The experimental results show the proposed approach assists in reducing the garbage collection cost since the number of sectors used in handling the I/O operations is being minimized. Even the sector becomes the candidates, but the score factor will be the tiebreaker to determine whether the sector needs to be cleaned or not. On the contrary, the proposed scheme increases the number of copy operations due to new sector requirement while the degree of the wear-levelling emulate the standing sector cleaning scheme.

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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.

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Higher Education Institutions (HEIs) have begun rapidly adopting, selecting and implementing ERP systems due to the call by various governments to streamline their processes and practices. While ERPs are expanding at much faster rate, there is pressure on most HEIs to ensure quality. For quality model, ISO/IEC 25010 is an international standard for software and systems quality evaluation. With the introduction of three specific new sub-factors, this paper presents a new model based on the ISO/IEC 25010 for the evaluation of quality enterprise resource planning (ERP) systems. This new model can be used to select and adopt ERP systems in higher education institutions. It can also serve as a guide in implementing ERP systems in higher education institutions. The new model comprises eight factors which include functional suitability, reliability, usability, performance efficiency, compatibility, security, maintainability and portability. These eight quality factors are further divided into thirty-four (34) sub-factors. Thus, the outcome of this study is a model developed for quality evaluation of ERP systems in HEIs.

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Object Instance Recognition aims to classify objects specifically and usually use a single reference image. It is possible to be used in many applications such as visual search, information retrieval and augmented reality. However, various things affect the appearance of the objects, which makes the recognition process harder, especially if a single reference image is used. In this paper, we proposed a combination method between Salient Object Detection and Object Instance Recognition using Image Matching and Geometric Verification. Salient Object Detection is used during initial processing (feature extraction), while Geometric Verification is performed using Best Score Increasing Subsequence (BSIS). Experimental results showed that the F? score and Mean Absolute Error (MAE) of saliency map on Stanford Mobile Visual Search Dataset (SMVS) are quite satisfactory. While the results of the combination method show 1.92% performance improvement than the previous method which is BSIS without Salient Object Detection.

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The research presents a statistical analysis that characterize the environment of the admitted students to Higher Public Education Institutions, by providing an overview of student’s distribution to the courses of studies offered by universities in Albania, such as, economy, medicine, technical etc., and grouping them according to the relative density of 38 (thirty eight) administrative units /districts. The aim of the research focuses on the trends that these units present in the main areas of study mentioned above. We want to if there is a connection between come and the courses of studies. So, in other words to see the trends according to district. The clustering was performed using the Ward’s method of Cluster Analysis (CA Hierarchy Methodology). This research seeks to develop a very careful description in order to detect typical features and furthermore to understand the situation. The assessment combines a total analysis to a relative comparative analysis of study programs offered by universities. Also, it analysis different indicators.
The analysis is based on a choice obtained from the NG 2014 (National
Graduation) of Ministry of Education and Sports (MES). The soft used is SPSS
Statistic 25.

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In this study, a theoretical simulation was performed using the Schrodinger-Poisson method to elucidate the formation factors for two-dimensional electron gas in InGaAs-based HEMTs. No visible change was observed in the carrier density and the potential shape. The inflection point of the energy level and the agreement of the energy level in each dimension were confirmed for the change in the number of carriers in the channel layer. It was found that the number of electrons at this coincidence point almost coincided with the number of electrons in the IV characteristics measured by the previous research for each gate voltage. The change in carrier state suggested that a 2DEG was formed. In addition, by considering the transport of carriers on the crystal lattice plane as a cause of the inflection point of the energy level, it was suggested that it might be caused due to the occurrence of the degeneracy process at a certain moment. From these results, it was experimentally and theoretically shown that the formation of 2DEG was caused by the carrier degeneration and the state change.

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This paper discusses a new Tone Mapping (TM) approach converting a High Dynamic Range (HDR) image into a Low Dynamic Range (LDR) image able at the same time to extract the relevant details and enhance the contrast of LDR images to ensure a good LDR image visual quality. This approach uses an advantage of multiresolution and piecewise linear perceptual quantization. While multiresolution part at each resolution level extracts much more detail information from HDR image to become a LDR coarse image, perceptual quantizer part adjusts the LDR coarse by the pixel’s distribution using a piecewise linear function so that the final LDR image can be visualized near human visual system. Simulation results provide good results, both in terms of visual quality and TMQI metric, compared to existing competitive TM approaches.

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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.

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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.

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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.

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The need for air conditioning in rural areas where there is no source of electricity, leads to look for alternative solutions. Usage of Solar thermal system drive vapor jet refrigeration cycle (VJRC) instead of the traditional air conditioning systems, contributes in the reduction of the Global Worming and Ozone Depletion. The main objective of this paper is to test the visibility of using VJRC driven by solar thermal energy in rural areas to cover the cooling load demand of a typical movable house unit (TMH). After the mathematical modeling of the VJRC, the characteristic curves and tables where obtained by using engineering equation solver (EES) software assuming a constant evaporator temperature and various generator and condenser temperatures. TRNBuild subsystem in TRNSYS software was used to emulate TMH cooling load demand using weather data for two selected locations (Hebron and Jericho cities). TRNSYS software was used to investigate the validity of the proposed system in summer (May to September) for the two suggested locations. Three main parameters were studied in the proposed system, location, evacuated tube solar collector (ETC) area and hot storage tank volume. The results of the overall simulation of the proposed system indicated that the system efficiency in Hebron city was much higher than Jericho city due to climate and design conditions. In addition, it is found that there were many options for the system size can be selected to provide a percentage of the human comfort.

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In the software engineering research, several works focus on advantages of multi-modeling, which facilitate modeling a system by separating of concerns. The Model Driven Engineering approach relies on model to design software artefacts during the software development lifecycle. Handling such models involves describing some model management operators like ‘ composition ‘. That is an operation which consist to fuse a set of models into one (or more) incorporated model relating the application context. The present work, introduces a formal approach for UML-compliant model composition focused on three-actions: matching, checking and merging. Each composition action is represented by one or many graph transformations rules. The composition operator’s syntax is specified with triple graph grammars (TGGs) formalism.

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With the addition of thing of internet applications to 5G smartphones, mobile standby time and ultra-low-power sensing systems have become increasingly important. Nowadays, such sensing systems typically reduce power consumption to microwatts. This paper presents segmented and non-binary weighted capacitance DACs, low power, high resolution, an asynchronous clock, a spark-detect, vcm-based switching and direct switching, and reconfigurable 9- to 12-bit DACs to meet different sensing system applications. Multi-voltage is used to achieve microwatt-level power consumption. The analog/digit voltage is 1.5V/0.9V, respectively and can adjust the 4-mode resolutions (9/10/11/12 bits). The performance of the SNDR achieves 50.78, 58.53, 62.42, and 66.51db, respectively and consumes 2.69uW and results in a figure of merit (FoM) of 30.4fJ/conversion step for 12-bit mode.

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Different models and standards of information security were analyzed, to adopt a model that mitigates vulnerabilities, risks and threats in the quota allocation process for the State University in Ecuador. The main objective is defining a prototype for the management of processes and information security in this type of organization. It was used the deductive and exploratory research method to analyze the information in the references. In this work, the characteristics of the attacks were analyzed. It turned out a model performs the detection and defense of attacks based on the differences in data and time between them and the browsing behavior of normal users. It was concluded that the prototypes presented as results are an alternative to improve the security of the processes and the flow of information and that these can be used as a reference in this type of organization.

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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.

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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.

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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.

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Rural electrification and sustainable energy services to the less privileged is à major challenge faced in Nigeria. Off-grid power generation via small hydropower plant would mitigate this challenge. This Paper discusses the awareness and assessment of small hydro power for off-grid electrification in rural/isolated areas in Nigeria. In this research, the method of onsite data collection and evaluation was used. Data was measured and collected at water fall of 21 meters high. The velocity of the water and flow rate were measured and calculated respectively. From the onsite analysis carried out for a one-year period, the result shows output power generated in each month. The analytical observation revealed that the output power generated in the rainy season was higher than that of dry season. The data were compiled and plotted using Excel spreadsheet. The output power generated from the rainy season in Nigeria is higher than that of dry season. August has the highest output power (110.728867 kW), while December has the least output power (101.125352 kW). From the output power gotten we can term it a micro hydropower plant. With this each of the monthly generated power can serve 5 villages in rural/isolated areas with average connection of 200houses, assuming 100W compact power supply to each house hold. Nigeria as a developing country will gain a lot from Small Hydro Power (SHP) and it has minimal environmental hazard.

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In the Moroccan seismic code, infill walls are considered as secondary elements and their lateral strength and stiffness are neglected in the design when considering horizontal seismic loads. In this article we propose to investigate the effect of infill on the seismic performance of the buildings. A 6-stories reinforced concrete frame building is investigated. The concept of equivalent strut is used for infill panel. Diagonal strut carries only compression forces. Strut properties are calculated according to the FEMA306.Software analysis SAP2000 is used to conduct numerical simulations. Numerical results show that there is a change in the internal forces, in the fundamental period of vibration and in the lateral story drift when masonry infill is included in the design. Seismic behavior of infill frame is different from that predicted by bare frame.

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This paper uses the RC-triggered MOSFET-based electrostatic discharge (ESD) power clamp to conduct ESD from ESD events and not affect the ultra-low power sensor system. Then using the stacked device include stacked MOSFET or stacked BJT to reduce the leakage current which increases with temperature. Moreover, we compare gate-driven method and two-level–driven with both gate-driven and substrate-driven methods to determine the most efficient method in terms of layout area, leakage current, Human Body Model (HBM)/Machine Model (MM), and turn-on time. The proposed design of the power ESD clamp (IO15c/IO15e/IO15c_resize) has an HBM ESD protection level with a Positive higher than 8KV, 5.5KV, 8KV, and an MM ESD protection level with a Positive higher than 600V, 300V, 1000V. The power ESD clamp (IO15c/IO15e) consumes nearly 3.5pW/16.45nW and 2.8pW/16.89nW at temperatures of 25°C and 125°C, respectively, when AVDD3 is 1.0V.

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This paper provides an insight about the significance of the enterprise technical architecture (ETA) in enabling and supporting the implementation of the South African National Health Insurance (NHI). Design: Existing documentations from both academic and government domains were gathered, and analyzed using the hermeneutics technique, from the perspective of interpretivist approach. Based on the analysis, the paper reveals the cruciality of the ETA in the implementation of the Universal health coverage (NHC) in the South African environment. The paper is intended to be of use for the core stakeholders of the NHI, which include governments’ administrations, IT specialists, health practitioners, as well as academics.

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Face recognition in low resolution images has challenges in active research because face recognition is usually implemented in high resolution images (HR). In general, research leads to a combination of pre-processing and training models. Therefore, this study aims to classify low-resolution face images using a combination of pre-processing and deep learning. In addition, this study also aims to compare evaluation results based on differences in epoch values. In this research will use the Trunk Branch Ensemble – Convolutional Neural Network (TBE-CNN) as one of Convolutional Neural Network (CNN) architecture combined with the pre-processing method which is super resolution to get better accuracy compared to the state-of -art. Then the model is trained with different epoch values, that is 40 and 100, to compare the performance of the best classification. This study was evaluated by YTD Dataset. Based on the test results, this proposed method has achieved better results compared to the previous method, which gives an increase of 1%. After that, training results from different epoch values used also produce different accuracy at the training model but have no effect on validation and testing model. The training using epoch = 100 has an accuracy increase of 3% compared to training using epoch = 40 and the loss ratio obtained at the training is decreased by 20% compared to training at epoch = 40. Furthermore, optimization parameters are used and reducing computing time when training models and validation will be future research.

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With the advent of the Internet of Things Technologies (IOT), smart homes, and smart city applications, E-Nose was created. Almost of gas sensors consisting the electronic nose system suffer from cross sensitivity and lack of selectivity. Coupling smart gas sensors with artificial intelligence algorithms can thus empower conventional gas sensing technologies and increase accuracy in gas detection. This study describes the overall types of smart gas sensors used in air quality control, signal pre-processing and extraction features. Also it presents pattern recognition methods used in E-nose applications including linear methods such as Linear Discriminant Analysis LDA, K-Nearest Neighbors KNN and Non-linear such as algorithms Support vector Machine SVM and Artificial Neural Network ANN and their impact on improving accuracy rate for gas detection. Finally, this paper summarizes by providing directions for about how to leverage the benefits of combining these classifiers which is known as Data fusion approach and ensemble classifiers.

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Dry Eye Disease (DED) is one of the commonly occurring chronic disease today, affecting the vision of eye. It causes severe discomfort in eye, visual disturbance and blurred vision impacting the quality of life of patients. Due to recent advancements in Artificial Intelligence (AI) and rapid progress of analytics techniques, several image modality based computerized DED detection techniques are available in literature. These techniques transform image data into real and actionable insights and thus, provide new understanding and ways for better and quicker treatment. In addition, they assist ophthalmologist to diagnose dry eye disease precisely as well as to reduce the cost of healthcare. In this paper, we present a review on computerized DED detection techniques covering all available techniques. In addition, we present a parametric evaluation of these techniques based on our identified set of parameters. Though surveys on clinical DED detection techniques are available, this is the first attempt in literature to log down all computerized DED detection techniques at one place. Our survey will assist researchers and ophthalmologists to understand various technological advancements in the field of DED detection. As a little amount of work has been done in the field of automatizing dry eye disease detection, the field provides plenty of research opportunities to develop an automated efficient DED detection technique.

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Dementia is one of the three primary diseases that increases the level of nursing care required for the elderly. Dementia can lead to an increased burden not only on those who have contracted it, but also their families and the surrounding environment; initiatives for preventing dementia and slowing the decline of cognitive function are expected to reduce these burdens. This study focuses on phototherapy as an alternative non-pharmaceutical treatment for dementia. This study examined the activity of elderly dementia patients to determine the effect of phototherapy on their circadian rhythms. A total of 15 dementia patients within the age range of 86.3 ± 6.2, were selected as subjects, and the data were collected using a wristwatch data logger (Actiwatch2). The phototherapy consisted of 5,500 lux intensity light exposure from 7 a.m. to 9 a.m., and data measurements were taken for three 14-day periods, i.e., before, during, and after phototherapy. Frequency analysis using discrete Fourier transform and nonlinear analysis called Hurst exponential and translation error were used to analyze the activity data. Compared to before phototherapy, the Hurst exponent values during phototherapy showed a significant increase in value (p<0.05) and the translation error values showed a trend of decreasing. The increase in the Hurst exponent values seen in the present experiment suggests that phototherapy may have improved the cyclicality of the circadian rhythm. However, when the phototherapy ended, the subjects’ Hurst exponent values returned to the previous levels observed prior to phototherapy, and no significant differences in data were found before or after phototherapy. Thus, phototherapy, a possible treatment of sleep disorders, is also effective in promoting regularity in circadian rhythms in elderly dementia patients to a certain extent.

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The document describes the advancement of technology in commercial negotiations and functionality for various electronic transactions in Ecuador, with the aim of analyzing the blockchain and its adoption in managing e-commerce. The quantitative approach with a deductive and descriptive method has been used to identify the benefits in transactional activities and data security, both customers and businesses. The results indicated that it is effective use of cryptography, the algorithm EDCSA, together with the SHA algorithm to maintain greater security efforts. It was concluded that the use of these algorithms are effective for transactions of buying and selling and financial aspects, but it needs to maintain a permanent control and simulation processes to avoid flaws in procedures

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The need to optimally explore Nigeria’s diverse mineral resource endowments via sustainable value chain practices has, in recent times, been the focus of the Nigerian government and relevant stakeholders. This development has amongst other things, been made a necessity since the decline in Nigeria’s crude oil export and earnings, as well as the increased effort and commitment of the government to significantly diversify the economy from reliance on agriculture and the oil and gas sectors. This challenge has directed government efforts towards promoting the exploration of the solid mineral sector, to leverage its opportunities to attract investors and further sustainable development. The concept of sustainable development demands that economic ventures be both viable and environmentally sustainable. As a result of the self-seeking ethos of market economies, it is often necessary for the law to step in to moderate the profit-oriented tendencies of commercial interest. The paper aims to examine the sustainable development of Nigeria’s solid mineral sector through legal intervention. The objectives are to:(i) determine the importance of law to the sustainable development of Nigeria’s solid mineral sector;(ii) ascertain the current provisions of laws and policies in relation to the operation of the solid mineral sector and their impact on the sustainable development of the sector and (iii) make informed recommendations on how to use law as a tool to promote the sustainable development of Nigeria’s solid mineral sector. This study employed a qualitative approach in examining how well the current legal framework governing the solid mineral sector in Nigeria is positioned to promote sustainable development. It was found that the major impediments to the sustainable development of the solid mineral sector in Nigeria are centralization of ownership and resultant alienation of communities, restiveness in alienated communities, poor administrative infrastructure and implementation of laws and policies, and corruption.

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Nowadays Augmented Reality (AR) is very popular in teaching and learning, especially in leading student to observe learning material targets which supported by online learning resources using mobile device and wireless technology. Because English is a foreign language, most students have problems in learning English. Generally, their problems were related to low motivation, bad study habit and attitude toward learning. Significantly, formative assessment is important in improving student learning achievement. furthermore, a formative assessment can help teachers to identified students’ progress, modify instruction, provide immediately feedback and achieve learning goals. The aim of this study was to build Mobile Based Assessment with Augmented Reality based on formative assessment mechanism, examine student’s learning achievement, student’s acceptance and student’s motivation in Basic English Learning. A total of 34 elementary students of Grade 4 were selected to participated in this study. The descriptive analysis was used to analyze and described the data obtained. The result indicated that using Mobile Based Assessment with Augmented Reality based on formative assessment mechanism improved not only student’s learning achievement but also student’s motivation in Basic English Learning.

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In this paper, a novel quantum transmission protocol which are based on the quantum no-key protocol is proposed. First, the quantum no-key protocol is discussed to show its important and its non-efficient on data transmission over quantum channel. Then, we improve it to carry many data bits via transmission. In addition, the error correction code is discussed and emerged into the proposed protocol to secure the transmission over quantum channel noise. Finally, the evaluation of transfer cost is discussed to show the effective of our proposed system.

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Prior to the 19th century discovery of Portland Cement (PC), Lime Based Mortar remained popular due to its flexibility, permeability and more importantly, associated low carbon emissions. However, lime’s characteristic delayed setting/hardening time, low mechanical strength, poor internal cohesion and some volumetric changes have overshadowed significance of its outstanding features particularly, flexibility, and consequently put its overall use into decline. This study therefore aims at integrating an industrial by-product, Ground Granulated Blast Furnace Slag (slag) with lime, in form of lime-slag mortar, with a view to addressing lime shortcomings for improved performance. The methodology involved mortars with the same Binder/Aggregate (B/A) mix ratio (1:3) using five separate volumetric compositions of ‘lime-slag’ binders (i.e. 1:1, 1:2, 1:3, 2:1 and 3:1). Physical properties of the mortars involving their Water/Binder (W/B) ratios, Air Contents and Bulk Densities were recorded. Comparative evaluations of the compositions in hardened state, involving mechanical characteristics, were carried out at specific intervals through a twelve-month curing period. These were partly monitored through assessments of the composites’ microstructural behaviours over a six-month period. Results of the investigation show that addition of slag to mortars facilitate slightly larger pores with increased porosity. These effects are however minimal (i.e. from 23.42% to 25.37% porosity) when slag content is at equal volumetric content with lime. Also, at this same volumetric composition, the results show beneficial effects of slag on the composite’s mechanical properties; while the flexural strength is increased by 50%, the compressive strength is improved by about 250%. Despite the improved mechanical characteristics, the composite exhibits comparable (with lime only) capacity for deformation absorptions, thus, preserving lime’s known fundamental flexibility property. This is important for material’s durability, and overall sustainable constructions.

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