Volume 4, Issue 6

With the development of big data, artificial intelligence and deep learning, various social information networks are becoming exponentially intelligent. Of all the various social networks, YouTube is so popular that it is called the YouTube era. Not only video viewers, but also actual video producers, influencer youtubers, are increasing, allowing individuals as well as operators to use and market contents on various topics. As the number of users and contents increases, the choice of information increases, but it is more difficult for individual and business owners to select information that meets their needs. Therefore, this study aims to analyze the channel of the subject that the user needs from various angles and provide the ranking of the channel to individuals and businesses. We crawl the channels and measure the average awareness and influencer youtuber of channels and channel videos by analyzing the qualitative data of quantitative data and comments which are statistical information. As a final case study, we recommend the English learning channel to individual users based on numerical data statistics and emotional analysis results to show the maximum of flipped learning effect regardless of time and space. Plus, we prove the maximum of the effectiveness of marketing by influencer channel which is influential to operators in the medium and long term.

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

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

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Transportation vendors are important for distribution companies to deliver goods or products. Operational problems of logistic process in transportation vendors’ activities are difficult to track and monitor directly in the field, such as driver’s position, the delivery, and so forth. These problems result in the difficulty to measure the performance of vendors’ activities. The aim of this research is to develop a system which covers monitoring and tracking of their logistic process operation problems. The system is built based on Android integrated with GPS and GSM. This system is also equipped with the ability to recapitulate the performance of transportation vendors in running activities of logistic operation. The performance is measured from some important components in logistic process. They are task asssment, on-time delivery, completed administration and availabilty. The result of this system is capable to show the vendor transportation’s key performance indicator (KPI) and minimalize bureaucratic problems.

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Since environmental requirements penetrate engineering processes to keep global warming and to reduce pollutant emissions, the system operation should be designed based on environmentally approach friendly. Operationally, the system processes are supported by energy suppliers to meet continuously energy transaction while clean and green energies are also targeted to keep the environmental conditions. In other word, the renewable energy source becomes an opportunity integration of a potential natural source inclusion into conventional energy producers. Technically, the energy balance is also important to optimize to get an optimal power portion during the operating period. These works are prioritized to search the balanced combination of the integrated energy mix composition. The works also present the novel computational intelligence to find out the energy portion using Artificial Salmon Tracking Algorithm. By considering technical requirements and tested on the integrated renewable energy plants, this algorithm is applied to optimize the economic power production. The works show dynamically the total power for feeding the energy consumption through local loads. The power production is also balanced in various combination portions of energy sources in accordance with the power demand as similar as discharged pollutants. Moreover, the computation has been obtained clearly for optimal solutions within 24 hours using a proposed algorithm.

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The objective of the study was to establish the relationship between coalition and employee spiritual engagement. The research was quantitative, and data was administered and retrieved from employees at the selected private radio firms. Content validity was utilised to ascertain the validity of the instrument, and the reliability of the instrument was established using Cronbach’s alpha coefficient. Kendall’s tau_b correlation was used to shows the result of the bivariate relationship between coalition and employee spiritual engagement (p > 0.05); hence, we accepted the null hypothesis. To know how much variance in employee spiritual engagement can be clarified by coalition, a simple linear regression was performed; with a result of 0.1(percent), it was evidenced that coalition had no effect on employee spiritual engagement. The finding of the study showed that there is no statistical relationship between coalition and employee spiritual engagement. The result of this study also bears practical implications; executives should understand that organisations cannot achieve a zero-level coalition activity. Although this behaviour via the results does not possess a statistical relationship, executives should articulate its optimized use within acceptable terms.

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Digitization forces industry players to adapt to transforming market situations and buyer behavior. Technological advances, buyer power, and sharpened competitive intensity imply that businesses are confronted with the menace of commoditization. For companies to perform successfully in the market, outdated business models ought to be rethought and new business models should be created. Unique selling propositions and differentiation through research, innovation, and holistic stakeholder involvement help industry players to master the change. A tool was built to support businesses facing the consequences of digital transformation: the Business Model Builder. This research paper explores the steps of creating a software version of the analog Business Model Builder. The digital twin enables firms to simulate the iterative adaptation of business models to permanently changing market circumstances and customer demands on an ongoing basis. The user of the tool can edit single variables, understand interrelations, and see the effect on the outcome of the business case, e.g., earnings before interest and taxes or economic value added. Accordingly, the simulation offers the opportunity to have a dynamic view of the business model where any variances of input parameters are reflected in the business case. Thus, profitability, feasibility, and functionality of a business model can be validated, tested, and reviewed in the digital simulation tool.

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Source parameters of tsunami waves are an essential part of any modern tsunami warning system. Recalculation of a measured time series (wave profile obtained by a seabed-based pressure sensor) in terms of initial sea surface displacement at tsunami source is among the most (or) one of the promising approaches to be applied in a warning center. The “orthogonal decomposition”, that was proposed and studied earlier by the authors, is numerically studied here. Realistic shape of sea surface displacement and digital bathymetry of the southern part of Japan are used. To study functionality of the proposed approach, wave profiles are obtained by the sensors of DONET – Dense Oceanfloor Network system for Earthquakes and Tsunamis – pressure gauge network of Japan. We stress on the quality of tsunami source parameters reconstruction as well as on time required. As observed, just a part of the first wave period is enough for robust determination of such source parameters as amplitude and total volume of water. Results of numerical tests are summarized in tables and then discussed.

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

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Problem statement: In general, the water hyacinth is a biennial aquatic plant for many seasons with propagated quickly to become serious weeds in general water sources. The water hyacinth is caused carbon dioxide in the atmosphere as a greenhouse effect, which leads to climate change, the environmental concerns of the world today. The agricultural residue materials are the most used manufactured material in the world through a lot of water hyacinth plant but a little is used efficiently. One approach to reduce agricultural waste and add value to them is to produce a fiber composite like roof tiles. Roof tiles are a product developed to replace natural fiber by mixing agricultural residues materials containing fiber such as rice straw, kenaf, corn cob, rice husk and palm fruit bunch. with adhesives, waterproof adhesives or other materials. Approach: This work is also aimed to investigate the influence of adhesive on roof tiles product from water hyacinth fiber. The urea-formaldehyde adhesive was added into the water hyacinth roof tile in 10%, 12%, and 14% weight ratios. It is then hot pressed and tested to determine physical, mechanical and thermal properties according to the industrial standard. Other factors are considered: temperature compression, the shape of roof tiles and distribution of moisture to roof tiles, heat transfer between sheets during compression, compression time, suitable compression and hardening before or after glueing of the adhesives. Results: The experimental observation revealed that the proportion obtained of 12% of the Urea-formaldehyde adhesive from the weight of the water hyacinth roof tile mixture, will absorb the adhesive better. Conclusion: With knowledge and technology, the roof tiles manufactured from water hyacinth can raise the quality of life as an innovative product for commercial utilization.

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Photovoltaic systems and monitoring go hand in hand. There is no better way to check the health of your photovoltaic system than to utilize a remote monitoring system. Monitoring and tracking of photovoltaic systems are crucial for reliable functioning and optimal yield of any solar electric system. This paper aims to introduce a remote electronic monitoring system. The said system will allow us to retrieve, process and transfer, in real-time, the photovoltaic station data remotely. The main objective of this work is to build a robust system that could be said as a reliable and low-price system, which will allow the transfer of the installation state to the remote operator in real-time or store it on an online database. Our intelligent wireless system is contained two parts, the first part including a hardware system designed around a microcontroller card (the Raspberry pi3 card) and a second part including the software part, which is the installation and configuration of open source applications on the Raspberry card. On the other hand, the configuration of an online database is presented. The database will offer us the possibility to store and process the station’s data remotely and in real-time. Moreover, we also developed an application that plays the role of an interface for our monitoring Raspberry Pi3 machine.

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

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

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

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

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

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

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

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The technical and vocational institutions are the key feeders for skilled human capital in the robotic revolution economy. It is essential to engage the students by creating new, affordable robotics at a fraction of the cost. This study presents the design and simulation of a six-axis robot manipulator specifically made for education and training. The robot was developed based on Chriss-Annin’s configuration. The robot arm was printed using Fused Deposition Modelling technique using the acrylonitrile butadiene styrene filament. Before it was constructed, the arm parameters were assessed using Scilab as the tool and the traditional and fundamental methods: the Denevit-Hartenberg representation, the forward kinematics, the inverse kinematics, and the trajectory planning. The outcomes showed that the arm was working well on positioning and path planning. Therefore, the complete assembly of the robot should be able to assume a role in education and training. This work is an extension of the paper entitled “Lightweight Robot Manipulator for TVET Training using FDM Technique” published in 2018 Symposium on Electrical, Mechatronics and Applied Science 2018 (SEMA 2018).

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It is widely known that students’ exposure to poor postures due to inappropriate classroom furniture design may contribute to the increase of the prevalence of musculoskeletal disorders symptoms that if not identified on time could lead to severe health issues. In this context, due to the unavailability of scientific studies related to this topic in Ecuador, the aim of this research is twofold. The first aim was to define the classroom furniture design parameters’ dimensions for university students according to relevant anthropometric information. The second aim is to conduct a preliminary diagnostic of the appropriateness of classroom furniture currently used in Ecuadorian universities to students’ anthropometric characteristics. The obtained results are particularly relevant as the ten design parameters here proposed could be the starting point to the creation of a specific Ecuadorian standard to regulate classroom furniture design for university students. That would ensure domestic and foreign manufacturers could offer furniture more secure and adequate to the anthropometric characteristics of the university population of Ecuador. On the other hand, the preliminary study found evidence that all the examined classroom furniture presented mismatches in at least five design parameters, and students exposed to them over the past twelve months had a high prevalence of symptoms of musculoskeletal disorders in the hips, back, thighs, and neck.

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Recitation and listening of the Holy Quran with Tajweed is an essential activity as a Muslim and is a part of the faith. In this article, we use a machine learning approach for the Quran Reciter recognition. We use the database of Twelve Qari who recites the last Ten Surah of Quran. The twelve Qari thus represents the 12-class problem. Two approaches are used for audio representation, firstly, the audio is analyzed in the frequency domain, and secondly, the audio is treated as images through Spectrogram. The Mel Frequency Cepstral Coefficients (MFCC) and Pitch are used as the features for model learning in the first case. In the second case of audio as images, Auto-correlograms are used to extract features. In both cases, the features are learned with the classical machine learning which includes the Naïve Bayes, J48, and the Random Forest. These classifiers are selected due to their over-all good performance in the state-of-the-art. It is observed that classifiers can efficiently learn the separation between classes, when the audio is represented by the MFCC, and the Pitch features. In such a case, we get 88% recognition accuracy with the Naïve Bayes and the Random Forest showing that Qari can be effectively recognized from the recitation of the Quranic verses.

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Nowadays, as the Information and Technology rapidly growing all across the world, Indonesia as one of many developed countries always tries to keep up relating to this trend. Regarding to this situation, the use of Information and Technology in various fields are greatly enhanced, and not to mention businesses. There are a lot of businesses using technology, building a start-up is one of the common ways to combine technology with innovation. Intrapreneurship is a media to develop new venture within an organization and to exploit new opportunities. To help the continuity of entrepreneurship, there must be an Innovation Management that serves help to develop ideas from the internal employees and always find the best solution to help the intrapreneurs grows in the best environment. To make a better decision making, management need some tools to monitor and evaluate the Intrapreneurs. Data Dashboard aims to help the decision maker to see the Intrapreneurs’ performance and at once feel their pain and gain. With those insights that can be obtained from the dashboard, hopefully, management can get enough information to make the best decision regarding the continuity status of each Intrapreneurs. This research will provide the dashboard with some algorithm to show the recommendation data about the status of Intrapreneurs.

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In this paper, we present a joint source-channel decoding (JSCD) scheme for image transmission. The binary sequences, resulting from the compression of several number of image blocks using arithmetic coding (AC), are written line-wise in the so called read- matrix (RM). In succession, a systematic Low Density Parity Check (LDPC) encoding is applied to the sequence produced by the column-wise reading of the RM. The proposed approach to JSCD incorporates error-free AC-decoder information feedback and error- detection AC-decoder information feedback in each sub-sequence. An error resilience (ER) technique within AC provides whether the input sequence is correct or not and possibly identifies the corrupt segment. In case of error detection, the reliabilities of the bits in the AC decoder input stream are estimated involving the detection delay distribution of the erroneous symbols. This information is provided to the iterative LDPC decoder after a bit back-tracking stage. Experimental results show that the proposed JSCD scheme outperforms the separated source-channel model and reduces the number of decoding iterations.

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The Citrix NetScaler CPX, is one of the many Application Delivery Controllers (ADCs), which is used mainly for load balancing between the application servers in a datacenter network. ADCs are typically placed in the demilitarized zone in an organization’s network, handling the connectivity of the external clients to the organization’s servers. While performing load balancing between the servers, there is need for better routing between application servers. Route Health Injection (RHI) delegates the control of routing protocol announcement to a server based on the health of a service and the connectivity of the server to the network. This paper discusses on how the current version of NetScaler CPX is integrated with a third-party routing stack, Quagga, to enable the connectivity of the clients to the servers, with the additional feature of Route Health Injection (RHI) for better routing.

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This article presents an analysis on the existing correlation of the specific and global performance of teachers in UNTELS engineering schools, whose data collection was carried out during the development of the first academic semester of the year 2019, using the Survey technique; which presents indicators classified in two dimensions: “Specific Dimension of Teaching Performance” and “Global Dimension of Teaching Performance”, the first dimension includes indicators such as course planning, teaching strategies, teaching communication, student communication, administration of the class, and personal and professional traits, that the teacher shows towards the student; Likewise, the global dimension is related to the student’s appreciation, as to whether the teacher surveyed should continue with the development of the course. This research was carried out, due to the low percentage of satisfaction in the student survey, and the appreciations in some negative cases, of the students in the Professional Engineering Schools. For this, initially it was sought to identify the number of teachers by Professional School of Engineering, whose teaching performance is poor, resulting in 17 teachers, which represents 14.05% of the total number of teachers; with which it was determined the Specific Dimension that presents the lowest level of qualification, resulting in Dimension 2 (D2): Didactic strategies, with an average grade of 10.41; These results will allow decisions to be made by the University authorities, regarding the development of a pedagogical training plan focused on improving said dimension, thus benefiting teachers in improving their teaching methodology. According to the analysis made, the dimensions of the specific and global performance of teachers in UNTELS engineering schools show a high positive level of Pearson’s correlation.

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Student dissatisfaction is of the utmost importance when it comes to establishing a process of continuous improvement in a University. Currently, at the National Technological University of Lima Sur (UNTELS) there is no information regarding the levels of student dissatisfaction with the services offered by UNTELS. In this context, the purpose of this research project is to collect information from the students of the Professional Careers of Systems Engineering, Environmental Engineering, Mechanical and Electrical Engineering, Electronic Engineering and Communications, and Business Administration of the academic semesters 2017-I, 2017-II and 2018-I. To assess student dissatisfaction, a physical questionnaire was applied; through which the indicator of the highest level of dissatisfaction was determined, being “Sufficient work tables or capacity”, corresponding to the category of laboratory service, whose value of dissatisfaction is 65.61%, 47.23% and 52.11%; in the academic semesters 2017-I, 2017-II and 2018-I, respectively. Next, the indicators whose level of research is greater than 40% were determined, with three indexes of higher percentage of increase, these are; Registration and enrollment, Internet Service and the Efficiency of Administrative Personal Work; These results are intended to take relevant actions for the continuous improvement of the educational quality of UNTELS.

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This paper presents the setup of eye tracking calibration methodology and the preliminary test results of the training model from the eye tracking data. Eye tracking requires good accuracy from the calibration process of the human eyes feature extraction from facial region. Viola-Jones algorithm is applied for this purpose by using Haar Basic feature filters based on Adaboost algorithm which extract the facial region from an image. From the extracted region, the eyes feature is selected to find the center coordinate of the iris and be mapped with the calibration point coordinates to create the training model of the eye calibration process. Thus, this paper shows the performance and efficiency of three training functions in Neural Network algorithm to get the best training model with fewer error for more efficient eye tracking calibration process.

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

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

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

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

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

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

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

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In recent years, researchers have focused on the development of many applications of information and communication which could lead to enhance human life. The congestion and road traffic are one of the most problems facing the ambulance transportation to provide fast healthcare services for patients. In this work, a tracking and data transfer system has been introduced such that a central monitoring and tracking unit can observe ambulance using MQTT protocol where each vehicle is occupied with the embedded system unit. When an ambulance being on the road it will communicate with other cars by means of socket communication whenever the ambulance enters a new region of the city. Chat between drivers has been designed using speech recognition library-based Google API. The proposed system has been designed and implemented using a python source network programming.

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In this paper, we would like to discuss the methods and ideologies used to create a database to be used for Human Resource purposes. Because we want this database to be accessible anywhere at any time, it is safe to conclude that an internet-based (web-based) database would work best, therefore we chose MySQL as the database management system. Before diving deep into the making of the database itself, it is important to understand certain basics of database design and the phases of the database life cycle itself. This paper will conclude on a few of the basic things to understand before designing a database for Human Resource Management on MySQL.

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

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

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

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

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

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

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The present paper details a queueing model with two kinds of repair facilities and server timeout. Here the customer arrives in compound Poisson process into the system and the lifetime of the server follows exponential distribution. At the point when the system is vacant, the server waits for customers for a settled time ‘c’. If nobody enters into the system amid this time, the server takes vacation otherwise the server commences the service to the arrived customers exhaustively. If the server fails, repair process will be initiated immediately. Here broken-down server is facilitated with two kinds of repair facilities. Type –I repair is done if the customer service is interrupted due to server failure and the customer stays back in the system with a probability of 1-q to receive the remaining service whereas Type-II repair is initiated if the customer whose service is interrupted due to server failure quits the service zone and joins head of the queue with a probability of q. Explicit expressions are derived for various constants of queueing System and also numerical results are illustrated with various batch size distributions.

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Over the past decades, huge efforts have been devoted for image enhancement under uncontrolled scene such as fog and haze. This work proposes Multi-stage de-hazing approach for improving the quality of hazy images. Four main stages are introduced, in our approach, to achieve an automated, efficient and robust de-hazy processing. The first two stages are utilized to diminish the blurring noise and enhance the contrast using Wiener filter and contrast scattering in the RGB color, respectively. In contrast, the last two stages are utilized for luminance and quality enhancement using luminance spreading and color correction. It is obvious from the experimental that the proposed approach significantly improves the prominence of the hazy images and outperforms the performance of conventional methods, such as multi-scale fusion and histogram equalization. In addition, it is also found that our approach exhibits low complexity compared to existing works.

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This article presents the development of an automatism by means of a Programmable Logic Controller (PLC), for the Fire System of an Electric Substation; For this, the areas belonging to the electrical substation are initially described, where the automatism is developed, these being three; Patio area (Transformer location), Distribution board area and Control room. Then the components to be used in the automatism are identified, which are; 16 sensors (input elements), as well as 5 solenoid valves, 3 electro-pumps and 3 frequency inverters (output elements). Then the programming of the S71200 PLC is developed, through the contact scheme language, the automatic control guarantees the optimal operation of the system components. Once the system has been developed, the Cronbach Alpha test is carried out in the statistical program SPSS (Startical Product and Service Solutions), which determines that the reliability is 0.794. Finally, the normality of the data was verified through the Shapiro Wilk test, obtaining as a result a significance of 0.60 for the pressure and 0.166 for the flow rate; being these data greater than the level of significance ? = 0.05, we can conclude that the variable pressure and flow follow a normal distribution, which is reflected in the normal QQ graph, in this way the correct operation of the fire system would be guaranteed. of the Electrical Substation..

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This article presents the experimental analysis of a rotary machine, Universal Motor Analysis; analysis that obeys the purpose of obtaining the almost perfect understanding of the electromechanical behavior of said unit of analysis; It should be noted that the variables to be analyzed were: voltage, current, power, torque, rpm, and power factor; specifically said data will lead to determine the regression model for each of the parameters measured, through the modification of its determination factor. Thus, an analysis of the correlational type was also performed among the variables collected above; finally, through a comparative analysis between engine efficiency during the alternative and continuous signal admission, the fuel efficiency of 91.03% will be determined in the first case, while in the second case, an efficiency of 96.66% was found; being able in this way to determine that the efficiency is greater in 5.63%, in Direct current (DC) compared to the application of Alternating current (AC).

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In this paper, we present a broadband frequency tunable antenna embedding varactor diodes. The reference antenna structure is a square antenna of patch dimensions [39,2 × 39,2] mm², operating at a single resonance frequency 2.45GHz. The recommended procedure to achieve the frequency shifting is to etch rectangular slots on the patch and to embed two varactor diodes with different values in the etched slots. When the integrated diodes have the same values, the simulated results of the proposed structure show good frequency flexibility by covering the [2.5 – 2.88] GHz band with reflection coefficient value (-36 dB). To improve the frequency agility of the proposed antenna and its performances, the embedding varactor diodes are separately optimized. The optimized antenna geometry and the integration of the varactor diodes positions enhance the performances of the proposed antenna and thus exploit the frequency band which is not covered by the reference antenna. Therefore, the obtained results indicate an improved tuning frequency behavior of the designed antenna which will be adopted to the dynamic changes of the environment allowing a good exploitation of the frequency spectrum.

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

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

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Treatment plants have been developed in many countries to handle wastewater, therefore, many pieces of researches have been conducted in order to optimize the outcomes. In this article, a mathematical optimization model was developed using quadratic programming approach to optimize the pollutant degradation at the domestic wastewater facultative stabilization ponds. The data used in this research were obtained from Sewon, Bantul wastewater treatment plant (WWTP) located in Yogyakarta, Indonesia. The proposed mathematical optimization model was formulated by maximizing the total amount of domestic wastewater processed in four facultative ponds along with the efficiency index value of the biological oxygen demand (BOD) degradation. The corresponding quadratic programming problem was solved in LINGO 18.0 optimization tool by using the generalized reduced gradient algorithm. The result led to the optimal decision which is the value of the domestic wastewater processed in each facultative pond.

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Recently, opportunistic networks are considered as one of the most attractive developments of ad hoc mobile networks (MANETs) that have emerged thanks to the development of intelligent devices. Due to the mobility-related instability of the paths between nodes and due to the limited buffer and energy resources, the ultimate objective of routing protocols in opportunistic networks is to enable the exchange of information between users. In such harsh environments, it is difficult to exactly pin down the services provided by these networks. To this end, we present in this paper a study on the performance analysis of six of the most popular routing protocols in opportunistic networks, namely, epidemic, PRoPHET, MaxProp, Spray and Wait, Spray and Focus, and Encounter-Based Routing (EBR). We firstly described these protocols and presented their algorithms. Thereafter, we carried out a comparative study of these protocols using exhaustive performance testing experiments with different numbers of nodes, traffic loads, message lifetime, and buffer size. The results of this investigation are with an important role in helping network designers to improve performance in such challenging networks.

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Recently, opportunistic networks are considered as one of the most attractive developments of ad hoc mobile networks (MANETs) that have emerged thanks to the development of intelligent devices. Due to the mobility-related instability of the paths between nodes and due to the limited buffer and energy resources, the ultimate objective of routing protocols in opportunistic networks is to enable the exchange of information between users. In such harsh environments, it is difficult to exactly pin down the services provided by these networks. To this end, we present in this paper a study on the performance analysis of six of the most popular routing protocols in opportunistic networks, namely, epidemic, PRoPHET, MaxProp, Spray and Wait, Spray and Focus, and Encounter-Based Routing (EBR). We firstly described these protocols and presented their algorithms. Thereafter, we carried out a comparative study of these protocols using exhaustive performance testing experiments with different numbers of nodes, traffic loads, message lifetime, and buffer size. The results of this investigation are with an important role in helping network designers to improve performance in such challenging networks.

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

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

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

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