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Fingerprinting is a process of identifying the remote network devices and services running on the devices, including operating systems (OS) of the devices, and hosts running different OSs. Several research proposals and commercial products are available in the market to defeat fingerprinting. However, they have performance limitations and expose themselves to attackers. In this paper, we utilize some real-time fault-tolerance concepts (viz. real-time/dynamic, detection/locating, confinement/localizing and masking/decoy) to propose a plug-and-play adaptive middleware architecture called Secure Dynamic Middleware (SDMw) with a view to defeat attackers fingerprinting the network, without exposing itself to the attackers. We verify that the proposed scheme works seamlessly and requires zero-configuration at the client side.

Anxiety disorders are common, debilitating, and begin early in life. Early intervention to prevent anxiety disorders in children who are at risk could have long-term impact. The ‘Cool Little Kids’ parenting group program has previously been shown to be efficacious in preventing anxiety disorders in temperamentally inhibited young children. Wider dissemination of the program could be achieved with an internet-based delivery platform, affording greater accessibility and convenience for parents. The aim of this study was to evaluate ‘Cool Little Kids Online’, a newly developed online version of the existing parenting group program. Fifty-one parents of children aged 3–6 years were recruited to evaluate the online program's acceptability and preliminary efficacy in reducing inhibited young children's anxiety problems. Parents were randomized to receive either a clinician-supported version or an unsupported version of the program. Parents had 10 weeks to access the program and completed questionnaires at baseline and post-intervention. Both groups showed medium-to-large reductions in children's anxiety symptoms, emotional symptoms, number of child anxiety diagnoses, and improvements in life interference from anxiety. The effect of clinician support was inconsistent and difficult to interpret. Parents reported high levels of satisfaction with the program. These encouraging results indicate that the online version is acceptable and useful for parents with temperamentally inhibited young children. Cool Little Kids Online may be a promising direction for improving access to an evidence-based prevention and early intervention program for child anxiety problems. A large randomized trial is warranted to further evaluate efficacy., Highlights • An online version of an existing parenting program for child anxiety was developed. • Most parents found the program useful, user-friendly, and would recommend it. • A clinician-supported format was not clearly superior to a self-guided format.

Problem and goal. In modern conditions, specialists in various subject areas who have an information culture and are able to solve complex professional problems using modern information and communication technologies are in demand. Currently, specialists in the field of applied mathematics are required, which plays an important role in the development of human civilization. Therefore, in the process of teaching various academic disciplines of applied mathematics at the university, including the discipline Equations of mathematical physics, attention should be paid to the development of students information culture. Methodology. When teaching students the discipline Equations of mathematical physics, it is extremely important that the teacher knows not only the content of teaching this discipline of applied mathematics, but also has practical experience in solving equations of mathematical physics by computer means. Such qualities of the teacher will allow him to successfully conduct training sessions in the conditions of informatization of teaching mentioned discipline. At the same time, it ought to be clearly understood that the use of computer technologies in teaching the discipline Equations of mathematical physics must be correct. The necessity to develop and implement in practice a variety of methodological approaches that allow students to develop an information culture in training sessions on that discipline is obvious. Results. The use of advanced pedagogical technologies in training sessions on the discipline Equations of mathematical physics, where computer technologies are used, will allow students to develop an information culture. Conclusion. Computer technologies that students use in the process of solving educational problems require them to have certain skills and abilities to identify their broad capabilities. Students are aware of the role of computer technologies in conducting applied scientific research, understand the role of computer modeling methodology and computational experiment in studying the world around them.

Problem and goal. The development of mass open online courses contributes to the increasing attention of students to them. At the moment, there are many large services that provide online training, but there are no clearly defined universal requirements for such courses. Also, along with this problem, there is a fairly high level of rejection of the course at various stages due to the loss of motivation to continue training. Methodology. A variant of solving these problems by using adaptive learning technologies on the example of a course on learning artificial neural network technologies was considered. Results. In the process of reviewing the issue, the topics of the online course sections were determined. As a result, a work plan was drafted and the most relevant ways to solve the identified problems were formulated. Conclusion. The developed strategy can help with further elaboration and testing of the designed course and can be applied to any mass open online course.

Problem and goal. In Russian society, the simultaneous and mass transition to distance learning of educational organizations in March 2020 in connection with a new coronavirus infection caused a sharp discussion about the effectiveness and consequences of this format of training, as well as about the prospects for its use after the COVID-19 pandemic. In the current conditions, the education system is faced with the task of training specialists in the face of the uncertainty of the future and the accelerated digitalization of the economy. The purpose of the research is to analyze the main factors influencing the development and spread of distance learning in the coming years, as well as the possible short and long-term consequences of switching to distance learning in higher education institutions. Methodology. The analysis of the scientific literature and practical activities, as well as experienced teaching, was used in the study. Results. The content and form of education will significantly transform in the long term. Today the necessary digital competencies cannot be acquired within the framework of the traditional educational process (lectures, seminars, exams in oral form), without the systematic use of information technologies in the educational process. Information technologies will be in high demand by graduates and will allow them to be prepared for the practical use of IT in the workplace. In addition, it can significantly improve the effectiveness of training because it allows to implement an individual learning trajectory, personalize training, remove restrictions on the time and place of training, and increase the visibility and interactivity of the educational process. Conclusion. Online education, e-learning using distance learning technologies in the long term will meet the demand of students and society for training in an uncertain future. Thanks to information technologies, conditions are created for active cognitive and educational activities of students, individualization of training is provided, turning the student into an active and equal participant in the educational process, including by refusing to provide ready-made differentiated knowledge, which leads to the formation of the reproductive nature of thinking in students.

Problem and goal. Developed and tested solutions for building individual educational trajectories of students, focused on improving the educational process by forming a personalized set of recommendations from the optional disciplines. Methodology. Data mining and machine learning methods were used to process both numeric and textual data. The approaches based on collaborative and content filtering to generate recommendations for students were also used. Results. Testing of the developed system was carried out in the context of several periods of elective courses selection, in which 4,769 first- and second-year students took part. A set of recommendations was automatically generated for each student, and then the quality of the recommendations was evaluated based on the percentage of students who used these recommendations. According to the results of testing, the recommendations were used by 1,976 students, which was 41.43% of the total number of participants. Conclusion. In the study, a recommendation system was developed that performs automatic ranking of subjects of choice and forms a personalized set of recommendations for each student based on their interests for building individual educational trajectories.

Problem and goal. With the advent of the information age, Internet-based online learning has also become one of the learning methods chosen by many learners. They can use these online learning platforms to complete knowledge construction while learning offline. Methodology. Most studies of learning behaviors focus on the discovery of the best learning model and disregard the possible impact of different learning behaviors on knowledge construction. Therefore, based on the Felder - Silverman learning style model, this article uses the Solomon learning style scale to improve the design of the questionnaire and collect four-dimensional differential learning behaviors data. In order to further understand the influence of learning styles on the effectiveness of online learning, we also use online learning data on the Small Private Online Course platform and general cognitive intelligence knowledge integration theory to clarify the relation between learning modes and individuals differences. Results. This study observes and analyzes the learning behavior data of 46 students of Nankai University in the SPOC learning platform, also analyzes the differences in learning styles and knowledge construction of students in the SPOC environment. Compared with the traditional Basic Portuguese teaching method, the blended teaching model based on the Chaoxing Learning platform has unparalleled advantages. Interactions inside and outside the classroom, improving student participation and promoting teaching diagnosis. Conclusion. Through a comprehensive analysis of questionnaire data and online data, we found that some learning styles have different effects on the effectiveness of online learning, ignoring the individual differences of learners will still cause problems in knowledge construction.

Problem and purpose. The problem of improving the training of IT specialists in the field of electronic document management in the process of studying at a university is examined. Methodology . The study used an analysis of practical activities in working with electronic document management systems and training in working with these systems in the process of training IT specialists in the field of electronic document management. Results. A proposal has been put forward on the need to create a special educational system for electronic document management for use as an object of study and as a means of training in the education of IT specialists in the field of electronic document management, the requirements for it were formulated, and step-by-step models of its preparation are described. Conclusion. The proposed software and technological tools and organizational and methodological methods will allow solving the problem of improving the quality of training of IT specialists in the field of electronic document management.

Problem and goal. The practical (pedagogical) training sites based on Moscow schools in the context of effective development of the resources of the Moscow Electronic School by future computer science teachers are analyzed. The goal is to identify the correlation of the digital footprint obtained as a result of the development of the school network activity index based on data on the actions of teachers and students in e-learning environments and of educational organizations identification corresponding to this index, as well as the methodological activity of schools in Moscow - the bases of practical (pedagogical) training of future computer science teachers. Methodology. The analysis of regulatory documents and the database of Moscow schools, where the Moscow City University students of the Computer Science direction are engaged in practical (pedagogical) training, reflection on the content of the knowledge obtained, search for criteria for selecting basic schools for conducting practical (pedagogical) training of future computer science teachers, local pedagogical experiment were used. Results. It was found out that the activity of schools in the development and use of educational resources of the Moscow Electronic School is not a prerequisite for cooperation with these schools. At the same time, the knowledge of information technologies, including the technology of working with the resources of the Moscow Electronic School, by future subject teachers, is an integral part of the professional competence of a modern teacher, and especially a computer science teacher. Conclusion. The basic criteria for selecting sites for industrial practices of future computer science teachers, in particular students of the Moscow City University, are proposed. The formulated criteria for selecting basic schools for conducting practical (pedagogical) training of university students will allow them to successfully solve the tasks set for this type of educational activity, achieve their goals and form professional and pedagogical competencies.

Problem and goal. The active introduction of e-learning and distance learning technologies in the educational process, the reform of traditional models of learning and education have become priority areas of reforms and initiatives in various national education systems in the 21st century. Given that public spending is the main source of funding for education in the OECD countries, assessing the economic impact of implementing a digital educational environment at different levels of education under pressure on public budgets has become a key issue for national governments and educational organizations, as well as the subject of special research. In Russian practice assessment of the economic effect of the full-scale use of e-learning and distance learning technologies in the implementation of educational programs of secondary professional (training of middle-level specialists) and higher education have not yet been carried out. For these purposes, a methodology has been developed, which, however, needs to be tested. Results. The study identified a list of costs required to ensure the full use of e-learning and distance educational technologies in realization of educational programs of secondary vocational (training of mid-level professionals) and higher (including graduate school) education; the methodlogy for assessing the economic effect of these measures is justified, and calculations are made based on this methodology. Conclusion. The developed methodology has shown its effectiveness and needs further research and quantitative analysis.

Front Matter and Back Matter

Wind energy is a good alternative to meet the energy requirements in some parts of the world; however the efficiency of wind farm depends on the optimized location of the wind turbines. Therefore a software tool that is capable of predicting the in-situ performance of multiple turbine installations in different operating conditions with reliable accuracy is needed. In present study wind farm layout design tool OffWindSolver is developed within the OpenFoam architecture. Unsteady PisoFoam solver is extended to account for wind turbines, where each turbine is modeled as a sink term in the momentum equation. Turbine modeling is based on actuator line concepts derived from SOWFA code, where each blade of the turbine is represented as a line. The loading on each line/blade of the turbine is estimated using the Blade Element Method (BEM). The inputs for the solver are tabulated airfoil aerodynamic data, dimension and height of the wind turbines, wind magnitude and direction. OffWindSolver is validated for a real wind farm – Lillgrund offshore facility in Sweden/Denmark operated by Vattenfall Vindkraft AB. Because of the scale of the computation, we only examine the effect of wind from one direction at one speed. In the absence of time dependent Marine Atmospheric Boundary Layer (MABL), a log wind profile with surface roughness of 0.04 is used at the inlet. The simulated power production of each turbine is compared to the field data and large-eddy simulation. The overall power of the wind farm is well predicted. The simulation shows the significant decreases of the power for those turbines that were in the wake.

Nowadays, the Internet of Things (IoT) is a common word for the people because of its increasing number of users. Statistical results show that the users of IoT devices are dramatically increasing, and in the future, it will be to an ever-increasing extent. Because of the increasing number of users, security experts are now concerned about its security. In this research, we would like to improve the security system of IoT devices, particularly in IoT botnet, by applying various machine learning (ML) techniques. In this paper, we have set up an approach to detect botnet of IoT devices using three one-class classifier ML algorithms. The algorithms are: one-class support vector machine (OCSVM), elliptic envelope (EE), and local outlier factor (LOF). Our method is a network flow-based botnet detection technique, and we use the input packet, protocol, source port, destination port, and time as features of our algorithms. After a number of preprocessing steps, we feed the preprocessed data to our algorithms that can achieve a good precision score that is approximately 77–99%. The one-class SVM achieves the best accuracy score, approximately 99% in every dataset, and EE’s accuracy score varies from 91% to 98%; however, the LOF factor achieves lowest accuracy score that is from 77% to 99%. Our algorithms are cost-effective and provide good accuracy in short execution time.

This research aims to develop the analysis model for diseases in water buffalo towards the application of the feature selection technique along with the Multi-Layer Perceptron neural network. The data used for analysis was collected from books and documents related to diseases in water buffalo and the official website of the Department of Livestock Development. The data consists of the characteristics of six diseases in water buffalo, including Anthrax disease, Hemorrhagic Septicemia, Brucellosis, Foot and Mouth disease, Parasitic disease, and Mastitis. Since the amount of the collected data was limited, the Synthetic Minority Over-sampling Technique was also employed to adjust the imbalance dataset. Afterward, the adjusted dataset was used to select the disease characteristics towards the application of two feature selection techniques, including Correlation-based Feature Selection and Information Gain. Subsequently, the selected features were then used for developing the analysis model for diseases in water buffalo towards the use of Multi-Layer Perceptron neural network. The evaluation results of the model’s effectiveness, given by the 10-fold cross-validation, showed that the analysis model for diseases in water buffalo developed by Correlation-based Feature Selection and Multi-Layer Perceptron neural network provided the highest level of effectiveness with the accuracy of 99.71%, the precision of 99.70%, and the recall of 99.72%. This implies that the analysis model is effectively applicable.

Drones are widely known for their mobility and ease of use and represent a significant technological breakthrough with various applications. In this paper, a novel inexpensive Search and Rescue (SAR)-based approach for application in indoor environments is presented. The usage of Bluetooth Low Energy (BLE) has been evaluated with respect to other technologies and a conceptual view of the complete setup has been presented. Besides the cost of the drone and the locator devices, the other hardware is relatively inexpensive costing only a fraction of a US dollar. The system is believed to cover a wide area in a small-time frame ranging a few minutes, for instance, a 3600m2 surface area could be scanned in less than 5 minutes. The system is tested by attaching a BLE device in the payload to evaluate the presence of target beacons. Potential upgrades in the system are also proposed, including design modifications for outdoor use and the application in locating missing objects. This system can confidently replace search parties dealing with missing children in public places or venues, with minimal human interaction while bearing the potential for complete automation.

The aim of the current study is to provide improvement evaluation practices in the educational process. A multiple choice test was developed, which was based on content analysis and the test specification table covered some of the vocabulary of the applied statistics course. The test in its final form consisted of 18 items that were reviewed by specialists in the field of statistics to determine their validity. The results determine the relationship between individual responses and the student ability. Most thresholds span the negative section of the ability. Item information curves show that the items provide a good amount of information about a student with lower or moderate ability compared to a student with high ability. In terms of precision, most items were more convenient with lower ability students. The test characteristic curve was plotted according to the change in the characteristics of the examinees. The information obtained by female students appeared to be more than the information obtained by male students and the test provided more information about students who were not studying statistics in an earlier stage compared with students who did. This test clearly indicated that, based on the level of the statistics course, there should be a periodic review of the tests in line with the nature and level of the course materials in order to have a logical judgment about the level of the students’ progress at the level of their ability.

Sentiment analysis plays an important role in obtaining speakers' opinions or feelings towards events, products, topics, or services, helping businesses to improve their products. Moreover, governments and organizations investigate and solve current social issues by analyzing perspectives and feelings. This study evaluated the habit of chewing Khat (qat) leaves among the Yemeni society. Chewing Khat plant leaves, is a common habit in Yemen and East Africa. This paper proposes a model to detect information about the Khat chewing habit, how people explore it, and the preference for Khat leaves among Arabic people. A dataset consisting of user comments on 18 youtube videos was prepared through several natural language processing techniques. Several experiments were conducted using six machine learning classifiers and four ensemble methods. Support Vector Machine and Linear Regression had almost 80% accuracy, whereas xgboot was the most accurate ensemble method reaching 77%.

In this paper, a new Maximum Power Point Tracking (MPPT) control for a Photovoltaic (PV) system is developed based on both backstepping and terminal sliding mode approaches. This system is composed of a solar array, a DC/DC boost converter, an MPPT controller, and an output load. The Backstepping Terminal Sliding Mode Controller (BTSMC) is used via a DC-DC boost converter to achieve maximum power output. The stability of the closed-loop system is guaranteed using the Lyapunov method. This novel approach provides good transient response, low tracking error, and very fast reaction against solar radiation and PV cell temperature variations. Furthermore, chattering, which constitutes the main disadvantage of the classic sliding mode technique is eliminated. To show the effectiveness and robustness of the proposed control, different simulations under different atmospheric conditions are conducted in Matlab/Simulink.

The current article discusses the use of the dependency graph method to design and analyze automatic transmissions. Different goals may be served by modeling an automatic transmission using graphs. The most important of them are: determining the gear ratios for gears and the analysis of speed and acceleration of the rotating elements. Game tree-structure methods can be used to analyze the functional schemes of the selected gears. This paper describes the method of generating a system of kinematics equations for signal dependency graphs. This allows the generalization and extension of the algorithmic approach, and also further analyses and syntheses, such as checking the isomorphism of the proposed solutions and determining the validity of the structure and the operational parameters of the analyzed gears.

In the current paper, numerical simulations of the combustion of turbulent CH4-H2 are presented employing the standard k-epsilon and the RNG k-epsilon for turbulence closure. The Fr-ED concept is carried out to account for chemistry/ turbulence interaction. The hydrogen content is varied in the fuel stream from 0% to 100%. The numerical solutions are validated by comparison with corresponding experimental data from the Combustion Laboratory of the University of Milan. The flow is directed radially outward. This method of fuel injection has been already been explored experimentally. The results show that the structure of the flame is described reasonably and both standard k-ɛ and RNG k- ɛ models can predict the flame shape. The general aspect of the temperature profiles is well predicted. The temperature profiles are indicating a different trend between CH4 and CH4/H2 fuel mixtures.

A Vehicular Ad-hoc Network (VANET) is a subclass of wireless ad-hoc networks, widely used in on-road vehicles and roadside equipment, having applications in various areas including passenger safety, smart traffic solutions, and connectivity on vehicles The VANET is the backbone of the Intelligent Transport System (ITS) that establishes connectivity between vehicles through a wireless medium. When it comes to the communication between high-speed vehicles there is the challenge of dynamic mobility. In order to provide a higher Packet Delivery Ratio (PDR) and increase the throughput, a new routing protocol called Dynamic Trilateral Enrolment (DyTE) is introduced which chooses a dynamic trilateral zone to find the destination vehicle by allowing only relevant nodes to participate in the communication process using the location coordinates of source and destination nodes. The proposed routing protocol is compared with Ad-hoc On-demand Distance Vector (AODV), Ad-hoc On-demand Multipath Distance Vector (AOMDV), and Dynamic Source Routing (DSR), and the results show remarkable improvement in reducing the Network Routing Load (NRL) and increasing the PDR and throughput of the network. DyTE has performed more efficiently in terms of PDR (23% approximately), throughput (26% approximately) and drastically minimized the NRL by a factor of almost 3.

The key issue of the voltage-sag propagation on the different types of winding connections for the low voltage transformer in the distribution power network is considered in this study. The issues of voltage sag propagation depend upon the type of asymmetrical fault and the connection of the transformer windings. In this paper, the double line to ground fault is adopted for the voltage sag characterization. The depiction of the sage propagation is an outcome of the zero sequence components. Voltage sag propagation detection can be used to improve the power quality of the system. The obtained results reveal the characteristics of the voltage drop propagation from the primary to the secondary winding of the transformer throughout different connection. The implemented method will help analyze the Power Quality (PQ) problem in terms of voltage sag of the distributed transmission networks of the power system.

This paper presents a new design of an adaptive fuzzy logic control by implementing the leader-follower approach. The principle is to modify the feedback control of non-holonomic Wheeled Mobile Robot (WMR) to be adaptive according to a fuzzy controller in the control loop, in order to adjust the feedback control gains according to the distance error between the reference path and the real position. The trajectory tracking control for a single WMR is extended to the formation control for two WMRs in which the first one is the leader and the second is the follower. Simulation results are presented to demonstrate the effectiveness of the proposed controller.

The aim of this study is to provide an empirical evaluation of the influence of different aspects of design in the context of factor analysis in terms of model stability. The overall model stability of factor solutions was evaluated by the examination of the order for testing three levels of Measurement Invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (Δx2) between two groups, and Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI). Factorial invariance results revealed that the stability of the models was varying over increasing levels of measurement as a function of Variable-To-Factor (VTF) ratio, Subject-To-Variable (STV) ratio, and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratios 4:1, 7:1, and 10:1, the models started to show stability over the levels of measurement when the STV ratio was 4:1. Yet, the frequency of stability models over 1000 replications increased (from 77% to 91%) as the STV ratio increased. The models showed more stability at or above 32:1 STV.

Multipath (MP) and/or Non Line-Of-Sight (NLOS) reception remains a potential vulnerability to satellite-based positioning and navigation systems in high multipath environments, such as an urban canyon. In such an environment, satellite signals are reflected, scattered or faded, and sometimes completely blocked by roofs and walls of high-rise buildings, fly-over bridges, complex road structures, etc. making positioning and navigation information inaccurate, unreliable, and largely unavailable. The magnitude of the positioning error depends on the satellite visibility, geometric distribution of satellites in the sky, and received signal quality and characteristics. The quality of the received signal (i.e. its statistical characteristics) can significantly vary in different environments and these variations can reflect in signal strength or power, range measurements (i.e. path delay and phase difference), and frequency, all of which distort the correlation curve between the received signal and receiver-generated replicas, resulting in range errors of tens of meters. Therefore, in order to meet stringent requirements defined for the Standard Positioning Service (SPS), the characterization of distortions that could significantly affect a Global Navigation Satellite System (GNSS) signal is essentially important. The scope of this paper is to detect possible imperfections/deviations in the GNSS signal characteristics that can occur due to MP or NLOS reception and analyze its effects. For this purpose, analysis of fading patterns in received signal strength (i.e. Carrier-to-Noise Ratio and strength fluctuations) is carried out in both clear LOS and high MP environment and then its impact on satellite lock state (i.e. tracking) is assessed. Furthermore, phase fluctuations and range residuals are computed to analyze the effects of path delays. The results show that significant variations can occur in GNSS signal characteristics in the MP environment that may result in loss of lock event and inaccurate/faulty range measurements.

In this paper, a variable-volume Continuously Stirred Tank Reactor (CSTR) deterministic exothermic model has been formulated based on the Reynold Transport Theorem. The numerical analysis of the formulated model and the identifiability of its physical parameters are done by using the least squares and the Delayed-Rejection Adaptive Metropolis (DRAM) method. The least square estimates provide the prior information for the DRAM method. The overall numerical results show that the model gives an insight in describing the dynamics of CSTR processes, and 14 parameters of the CSTR are well identified through DRAM convergence diagnostic tests, such as trace, scatter, autocorrelation, histograms, and marginal density plots. Global sensitivity analysis was further performed, by using the partial rank correlation coefficients obtained from the Latin hypercube sampling method, in order to study and quantify the impact of estimated parameters, uncertainties on the model outputs. The results showed that 7 among the 14 estimated model parameters are very sensitive to the model outcomes and so those parameters need to be handled and treated carefully.

Worldwide, concrete is the most preferred construction material. The steam curing method is favored when there is a need for accelerating strength. This paper presents the study of the compressive and flexural tensile strength of concrete subjected to eight different steam cures. In addition, the stress-strain curve and the modulus of elasticity were determined at the age of 28 days. The compressive strength test results show that after treatment, strength increases with concrete maturity. A cycle with a pre-heating period gives better results than a cycle without a pre-heating period. The longer the duration of the maximum temperature period, the lower the strength drop compared to the control concrete. The best results were obtained for concrete treated according to the following cycle: a 3-hour pre-heating period at 20oC, a 2-hour increase of temperature from 20 to 70oC, and a 3 hour of maximum temperature of 70oC.

This paper proposes a novel control design for a Current-Fed Dual Active Bridge (CFDAB) converter in boost mode. The Double PWM plus Double Phase Shifted (DPDPS) modulation is applied to the converter due to its considerable merits. A small-signal model is developed to control the output voltage stably in boost mode. Simulations of the control design for the CFDAB converter were conducted to verify the proposed model. The results show that the system can achieve high performance, not only in the dynamic response but also in the steady-state.

Microgrids (MGs) are the emergent solution to overcome the current electricity demand. The MGs provide the facility to operate in both isolated and grid-connected modes. For both operating modes, Distributed Generation (DG) inverters are operating under grid forming or grid following control modes. During mode switching, the MG experiences enormous fluctuations, which occur due to the unidirectional islanding event. This paper presents a control strategy by using the modified power control scheme, current controller, and DC linked voltage controller scheme to ensure the operational mode transfer smoothly from the grid-connected to the islanded mode and vice versa. The proposed control scheme is applied to a three-phase distributed energy resource-based MG system with fixed loads. The simulation results validate the effectiveness of the control technique while tested at the point of common coupling and also at the time of mode transfer.

The Molten Salt Reactor (MSR) is the most important system suggested by Generation IV for the future direction in the nuclear reactor field. For more development of the MSR reactor, the core system inside the tube is proposed by naturally circulating molten fuel salt. The nonlinear kinetic equations form a linearized function and are obtained in state-space form. Reactivity feedback and delayed neutrons are extremely important for reactor control. In this paper, a thermal-hydraulic system for the commercial computation dynamic model is proposed. Currently, there is no commercial software to simulate the natural circulation flow. The proposed method can be easily employed to detect faults and can provide a feasible overall system performance.

An amendment to this paper has been published and can be accessed via the original article.

Nowadays this concept has been widely assessed due to its complexity and sensitivity for the beneficiaries, including passengers, airlines, regulatory agencies, and other organizations. To date, various methods (e.g., statistical and fuzzy techniques) and data mining algorithms (e.g., neural network) have been used to solve the issues of air traffic management (ATM) and delay the minimization problems. However, each of these techniques has some disadvantages, such as overlooking the data, computational complexities, and uncertainty. In this paper, to increase the air traffic management accuracy and legitimacy we used the bidirectional long short-term memory (Bi-LSTMs) and extreme learning machines (ELM) to design the structure of a deep learning network method. The Kaggle data set and different performance parameters and statistical criteria have been used in MATLAB to validate the proposed method. Using the proposed method has improved the criteria factors of this study. The proposed method has had a % increase in air traffic management in comparison to other papers. Therefore, it can be said that the proposed method has a much higher air traffic management capacity in comparison to the previous methods.

Tremendous efforts have been devoted to preparing the ultrathin two‐dimensional (2D) transition‐metal dichalcogenides (TMDCs) and TMDCs‐based heterojunctions owing to their unique properties and great potential applications in next generation electronics and optoelectronics over the past decade. However, to fulfill the demands for practical applications, the batch production of 2D TMDCs with high quality and large area at the mild conditions is still a challenge. This feature article reviews the state‐of‐the‐art research progresses that focus on the preparation and the applications in electronics and optoelectronics of 2D TMDCs and their van der Waals heterojunctions. First, the preparation methods including chemical and physical vapor deposition growth are comprehensively outlined. Then, recent progress on the application of fabricated 2D TMDCs‐based materials is revealed with particular attention to electronic (eg, field effect transistors and logic circuits) and optoelectronic (eg, photodetectors, photovoltaics, and light emitting diodes) devices. Finally, the challenges and future prospects are considered based on the current advance of 2D TMDCs and related heterojunctions.

Blockchain technology has been a buzzword globally especially among financial industrial players. It can be observed that most developed countries had begun to legalise the implementation of blockchain technology including European Union as well as the member states of G20 in order to secure their leading position in supporting the Fourth Industrial Revolution. Be that as it may, scholars admitted that Malaysia had been a bit desolated primarily in terms of its legalisation on the blockchain’s adoption in the country despite various initiatives that had been taken initially. Hence, this study was conducted to investigate the behavioural intention to adopt blockchain technology specifically among bankers in Malaysia Islamic financial system. A combination of theories, mainly the Unified Theory of Acceptance and Use of Technology 1 (UTAUT 1) as well as Technology-Organization-Environment (TOE) Framework had been chosen to be used in the study. This research implemented the quantitative method in which more than 200 questionnaires were distributed to 12 domestic banks in Malaysia through both self-administered method and online survey. Multiple regression analysis was applied to further verify the hypothesis made. Based on this study, it had been proven that effort expectancy, social influence and facilitating condition are the only factors that affect the behavioural intention to adopt blockchain technology with effort expectancy being the most significant factor among all. However, the results had also proven that the non-factors of the variables strengthened the fact that Malaysia is still at the primitive stage in respect to blockchain adoption. Thus, it signifies the importance for the industry to begin adopting instead of attempting by considering the best initiatives recommended in accordance to Malaysia’s mould in which the banks could opt to start working on the institution voluntary regulation whereas for the government, perhaps they could commence a consortium which consists of Islamic financial institutions in the country to develop their experience before implementing on their own. It is hopeful that the initiatives could help to secure the position of Malaysia as the world Islamic financial hub in the coming years.

In order to obtain a metasurface structure capable of filtering light of a specific wavelength range in the visible band, the traditional methods usually traverse the space consisting of possible designs, searching for a potentially satisfactory structure by performing iterative calculations to solve Maxwell's equations. In this article, we propose a systematic method based on neural networks that can complete an inverse design process to solve the problem. Compared with the traditional methods, our method is much faster while competent to encompass a high degree of freedom to generate device structures, which can ensure that the spectra of generated structures resemble the desired ones.

Help-seeking is an essential self-regulatory and metacognitive skill. In the online learning environment, much of the learning is self-directed and there are generally less opportunities to receive help in real time. The uses of email and discussion boards are the most common method of seeking help in these environments. The current study explored students’ perceptions of the use of live chat technology for online academic help-seeking within higher education, with a focus on comparing online and blended learners’ perspectives. Participants were 246 students who were studying psychology online (n = 91) or in blended learning (n = 155) environments. The live chat technology was well received by both groups, especially for its ability to provide instant, real-time, and convenient help. Live chat was particularly well received by online learners, who were more satisfied, felt more cared about by the teaching team, and would be more likely to recommend it to others than blended learners. Further, online learners reported that live chat gave them better access to staff, and felt that this feature was a good approximation for more traditional face-to-face conversations. As an online, synchronous, private help-seeking tool between student and teacher, these findings provide a strong endorsement for the use of live chat in higher education, particularly for online learners.

This study investigates the importance and need to apply the concept of retail halal control points (RHCP) in the food industry, specifically the supermarket which operates a complex supply chain system. The examination of the application of the RHCP on the supermarket is also to facilitate the business entity in obtaining halal or Shariah-compliant status. The RHCP method can assist the supermarket management to control for prohibited or illegal elements from infesting the supermarket supply chain process. In this way, the process of food safety and food products in supermarkets would comply with the Islamic teaching on halal principles. Unfortunately, it appears that up to now, there is no study in that direction. There are few studies though, that study halal control points but not in the field of retailing. For this reason, this study was conducted to fill the gap by examining the use of RHCP in the supermarket. By using the purposive sampling technique, four supermarkets located in the Klang Valley were cross-examined. Quality assurance managers and halal executives from each supermarket were interviewed extensively by using open ended questions. The interview transcripts were then analyzed by using thematic analysis. The results showed that the management team of all the selected supermarkets agrees to use a standard operating guideline for ensuring halal or shariah-compliance status in the supermarkets. Additionally, to achieve an optimum level of effectiveness with the RHCP method, the use of digitalisation is recommended. Difficulties in getting information and support from the supermarket management were among the main drawbacks of this study. Nonetheless, this study is significant for both the retail industry and academicia at least in terms of discussing the issues of the RHCP concept. This would certainly help the supermarket management in planning their supermarket business effectively and thus able to sustain competitiveness.

Over the last decade, the issue of work-life balance has gained visibility internationally due to ongoing usage of ICT that creates technostress on employee. Work-life balance should be a key concept to all employers today, especially to those with an increasing number of people in the organization and due to the additional demand for work that they imply. The best work-life balance situation is when an employer can manage work timetables and schedules for some leisure activities in a way that suits the employees. Managing both work and life aspects by ensuring a good relationship between them should be the primary objective. It creates a quality of life for each individual. Therefore, work stress is undoubtedly one of the employees' most significant problems, especially involving computer technology such as mobile phone technology, car alarms, emails, calls, and voicemails. That is called technostress. Technostress is the term used to describe the stress phenomenon induced by the inability to manage, due to using computer technology. A range of literature exists that shows the relationship between technostress creator and worklife balance either based on online data, google scholar, and PhD theses. This systematic literature review had been conducted by using PICO criteria. The four elements included in the PICO used to formulating these research questions are population, intervention, comparison, and outcome. This paper presents a systematic literature review using PRISMA collection method, to provide collective evidence on their implementation and how important work-life balance is for employees. The review reports on 120 sources from 1300 articles, providing insights into the range of technostress creator and work-life balance in existence. It also highlights the benefits and challenges encountered through work-life balance policy implementation for future research.

In the current situation, operation and control of power system is a greater challenge. The most significant situation in power system control is load frequency control. In the present work, a hybrid differential evolution and pattern search (hDE-PS) method has been suggested for frequency regulation of electrical power systems. Fractional-order proportional integral derivative (FOPID) controller is implemented for design and analysis purpose. The suggested control method has been applied for two electrical power systems model, i.e., 2-area diverse source power system with/without HVDC linkage and 2-area thermal system. The performances of the suggested controller have been evaluated with PID and optimal controller. The simulation results indicate that system performances are enhanced with the suggested approach for identical structure. Robustness of the suggested approach has been analyzed by variation in random load and the system parameters. The suggested method (hDE-PS tuned FOPID) is further investigated with a 2-area thermal system. The performance of the recommended approach is analyzed by equating the results with other newly available approaches, like Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Particle Swarm Optimization (PSO), hybrid BFOA and PSO (hBFOA-PSO), multi-objective Non-dominated Sorting Genetic Algorithm (NSGA)-II and Firefly Algorithm for the similar structure.

Industrial Revolution 4.0 (IR 4.0) adoptions have a positive effect on many facets of human life, including the economy and culture, such as income growth and living standards. Nevertheless, it will also have a negative effect on society, especially the social well-being that needs to be studied and explored. Thus, the purpose of this study is to develop a conceptual framework for an evaluation method to assess the degree of readiness of employees for IR 4.0 from a social well-being perspective. This paper used a search engine optimization (SEO) approach using related keywords from google suggest results as a guidelines and content analysis strategy based on the first three pages of results accessed during the identification phase based on PRISMA systematic methodology to review existing model. The review identifies 59 social wellbeing models with different dimensions. This study proposes five dimensions as the most important social well-being perspectives for organizations namely social integration, social acceptance, social contribution, social actualization and social coherence. It is expected that the establishment of the assessment tool can be used to measure the readiness of employees to face challenges of IR 4.0.

The advertising preferences have changed, putting massive pressure on marketers to bring forward impactful advertising sources. In a previous study, the endorsers such as social media influencers were found to be the most effective strategy at this time. Relatively, the endorsers' attributes, namely source credibility and source attractiveness, increase the advertisement's success rate by influencing people's attitudes and intentions. The millennial is reported as the most relevant generation to embrace the more substantial concern of interacting with social media, which is also seen as a generic group that emphasizes the environmental issue. According to Google's report, the internet searches for 'How to live a sustainable lifestyle' have increased 4,550 per cent in the first quarter of 2020. This study is aimed to scrutinize the effect of social media influencer attributes towards attitude and pro-environmental intention. The data collection method was distributed using a purposive convenience sampling of 300 datasets and analyzed using IBM SPSS 25 and Smart PLS 3.0. The result of this study confirmed the attitude to mediate between exogenous and endogenous variables. An in-depth review of the implications, limitations, and future study are further discussed.

Selenium cathode has been demonstrated as a promising candidate of cathode material for low‐cost and high‐energy density potassium ion batteries (PIBs). Nevertheless, their applications are prevented by poor electrochemical performance due to the shuttle effect of high‐order polyselenides, the sluggish diffusion of bigger K+, and the huge volumetric expansion during cycling. In this work, we design a multifunctional Se host (N‐HCNS) by grafting ZIF‐8‐derived microporous carbon onto the surface of N‐doped porous carbon nanosheets. The obtained N‐HCNS carbon matrix integrates conductivity, captivity, and immobility abilities, which inhibits the polyselenides shuttle, improves the Se utilization, and buffers the volume change during cycling. The 3D hollow carbon skeleton enhances the infiltration of electrolytes. As an cathode for PIBs, the Se@N‐HCNS electrode delivers an unprecedented life‐span (260 mAh g−1 at 1.0 A g−1 after 2000 cycles) and exhibits a remarkable rate capacity (339 mAh g−1 at 5.0 A g−1). Density functional theory (DFT) calculation reveals the effective adsorption of K2Se with pyridine and pyrrole nitrogen doping in carbon matrix. The unique synergetic design of electrode not only gives insight into the reaction mechanism but also highly emphasizes the potential capabilities of N‐doped carbon in K‐Se batteries.

The role of technology in an institution is beneficial for any activities, especially in managing documents administration, which is now most of the company used digital archive systems. That's because the manual archive system is considered less effective and efficient, where it takes a lot of space and time to search for document archives. Microsoft Access is a windows-based database processing program with Visual Basic for Application (VBA), commonly used to create a windows-based application. The purpose of this paper is to make an administration letter and archives system based on Microsoft Access. The results of this design have passed the trial process for approximately two weeks and received a positive response. The system design can be run well, and its functions correctly without errors. So it can help the secretary or other employees to manage all documents (letters and archives) more accessible and faster.

Weeding rice in paddy fields is mostly done by female farmers, as it is done by farmers in Kebon Bantiran village, Bajera, Tabanan. The body position of the female farmers when weeding the rice in the paddy field is bent and both feet are buried in the mud. The purpose of this study was to find out and describe the workload of female farmers when weeding rice plants in the rice fields. The sample for this study is 10 female farmers. The method of this research is the measurement of pulse with the 10 pulse-method. Data collection is done twice, after-work and after a short break. The data obtained are analysed by a t-paired test. The calculation results obtained the mean after-work pulse rate of 115.25 pulse per minute, while the resting pulse rate was 95.50 pulse per minute, decreased pulse rate was 19.75 pulse per minute or decreased by 20.68 percent. In the statistical test, the t-paired test decreased significantly (p is less than 0.05). The workload of female farmers to weed rice is a mild category. The percentage of cardiovascular load (CVL) for female farmers when weeding rice was 19.99 percent which indicates the category required for work improvement. The percentage of CVL value is calculated from the level of workload classification based on the increase of work pulse compared to the Vanwonteghem maximum pulse and categorized it into the classification of light or moderate workloads, so this need improvement by taking a short break.

The Search Engine has a critical role in presenting the correct pages to the user because of the availability of a huge number of websites, Search Engines such as Google use the Page Ranking Algorithm to rate web pages according to the nature of their content and their existence on the world wide web. SEO can be characterized as methodology used to elevate site keeping in mind the end goal to have a high rank i.e., top outcome. In this paper the authors present the most search engine optimization like (Google, Bing, MSN, Yahoo, etc.), and compare by the performance of the search engine optimization. The authors also present the benefits, limitation, challenges, and the search engine optimization application in business.

Information technologies allow for improving production systems functioning especially thanks to a possibility of solving complex production problems in a very short time. The production system designing is increasingly based on virtual reality, and more specifically on the concept of a digital factory. It enables to create virtual models of real objects and use them for visualization of products and manufacturing processes. The presented examples of new information technologies, which are used in production practice, are the main object of this paper.

This article presents a proportional relationship between Shutter and the value of the resolution scanning system that allows decision making for modeling 3D parts used in reverse engineering and additive manufacturing. As a first step, the object of interest is treated to dim excessive brightness, then the object is scanned (by point cloud or mesh) with the use of a Handyscan 700 scanner. The point cloud is processed with the Geomagic software Desing X to generate a CAD image and a “.stl” file for 3D printing.

This paper provides analysis of WiMAX systems from its background to their architectures highlighting merits and demerits, topologies, structures and looks deep into transceiver systems architecture, then specializes on the radio frequency (RF) front-end part of the WiMAX transceiver system in which a model is designed. Thereafter, the model is implemented in MATLAB Simulink and the results are investigated and analyzed.

This work shows the possibility of using spectral analysis in order to detect characteristic points in recorded images. The specific point is a marker in the form of a diode that flashes at a certain frequency. Main assumptions of the processing algorithm are the recording of a sequence of images and treatment change of level of brightness for each pixel as a time signal. The amplitude spectrum is determined for each time signal. The result of data processing is an amplitude image whose pixels brightness corresponding to the intensity of source of pulsating light emitting specific frequency. This new data representation is used to detect position of markers. The algorithm was re¬searched in order to select optimal marker colors and pulsation frequency. The results are described in a summary.