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Keyword: PerformancePower Management and Control of a Grid-Connected PV/Battery Hybrid Renewable Energy System
This paper presents novel Energy Management Strategies (EMSs), and the control of a Grid-Connected Hybrid Renewable Energy System (GCHRES). The GCHRES describes a Photovoltaic Generator (PVG) and a Battery-Based Storage System. Both are tied to the Common Coupling Point (CCP) through a reversible three-phase inverter. The CCP combines the Utility Grid (UG) and an AC…
Read MoreAutomated Hydroponic System using Wireless Sensor Networks
Researchers have associated agriculture and food processing with adverse environmental impacts like; falls in the underground freshwater table, energy consumption, and high carbon emission. These factors have the worst effect on developing countries. Therefore, there is a need for on-demand food production techniques that require minimum resource utilization. For these reasons, scientists are now focusing…
Read MoreOptimization of the Sliding Mode Control (SMC) with the Particle Swarm Optimization (PSO) Algorithm for Photovoltaic Systems Based on MPPT
Photovoltaic systems are classified as non-linear systems. On the other hand, the characteristics of photovoltaic cells are non-linear. For this reason, researchers use several methods of maximum power monitoring (MPPT) to improve the performance of photovoltaic system. It is therefore necessary to use an adaptation stage between the photovoltaic generator (GPV) and the load to…
Read MoreThermoelectric Generators (TEGs) and Thermoelectric Coolers (TECs) Modeling and Optimal Operation Points Investigation
Sustainable energy is gradually becoming the norm today due to greenhouse warming effects; as a result, the quests for different renewable energy sources such as photovoltaic cells as well as energy efficient electrical appliances are becoming popular. Therefore, this article explores the alternative energy case for thermoelectricity with focus on the steady-state mathematics, mixed modelings…
Read MoreValue Trace Problems for Code Reading Study in C Programming
C programming is taught in a lot of universities across the world as the first computer programming language. Then, for novice students, it is important to read many simple C source codes and understand their behaviors to be familiar to the programming paradigm. Unfortunately, effective tools to support independent code reading study at home have…
Read MoreSelf-Regulated Learning and Academic Achievement of Physics Students in Selected Secondary Schools in Aguata Local Government Area of Anambra State, Nigeria
The research investigated the consequence of self-regulated learning on students’ academic performance in physics, using selected public co-education schools in Aguata Educational Zone, Anambra State as the research area. The study became necessary as a result of the observed persistent poor performance of the student in Physics in external examinations over the years. The study…
Read MoreAntecedents to Learners’ Satisfaction with Serious Games: An Investigation Using Partial Least Square
Serious games are at the forefront of discussions about the future of learning. Research shows that they can help improve student motivation and knowledge transfer by making learning experiences more pleasurable. Teaching practices are increasingly enhanced or complemented by serious games; skills and knowledge are developed by recreating realistic situations allowing learners to enhance their…
Read MoreLight Modulation Enhancement by using an Impedance Matching Scheme for a Subcarrier Multiplexed Light Transmitter
We propose and analyze new impedance matching schemes to enhance applied voltage to an optical modulator and light modulation for a subcarrier multiplexed light transmitter or a radio-on-fiber transmitter that carries radio-frequency signal through an optical fiber. Our proposal includes two methods using a quarter-wavelength impedance transformer and a tapered microstrip line for impedance matching…
Read MoreNeural Network for 2D Range Scanner Navigation System
Navigation of a moving object (drone, vehicle, robot, and so on) and related localization in unknown scenes is nowadays a challenging subject to be addressed. Typically, different source devices, such as image sensor, Inertial Measurement Unit (IMU), Time of Flight (TOF), or a combination of them can be used to reach this goal. Recently, due…
Read MoreEnhancing Decision Trees for Data Stream Mining
Data stream gained obvious attention by research for years. Mining this type of data generates special challenges because of their unusual nature. Data streams flows are continuous, infinite and with unbounded size. Because of its accuracy, decision tree is one of the most common methods in classifying data streams. The aim of classification is to…
Read MoreTETRA™ Techniques to Assess and Manage the Software Technical Debt
The paper examines the company’s proprietary means for determining the quality of a software product and measuring its technical debt. The paper’s authors explain how a software product’s quality is directly correlated with the amount of varying technical debts that the end-users receive. All debts can be paid, and technical debt is no exception: one…
Read MoreEnsemble Learning of Deep URL Features based on Convolutional Neural Network for Phishing Attack Detection
The deep learning-based URL classification approach using massive observations has been verified especially in the field of phishing attack detection. Various improvements have been achieved through the modeling of character and word sequence of URL based on convolutional and recurrent neural networks, and it has been proven that an ensemble approach of each model has…
Read MoreA Task-based Paradigm for Promoting an Alternative Thinking Style in Teaching Mathematics
The article identifies an alternative style of thinking as one of the important components of human intellectual development. It is shown that it can be effectively implemented in mathematics lessons at school. The purpose of this study is to develop and substantiate a strategy for the formation of an alternative style of thinking among students…
Read MoreExtraction of Psychological Symptoms and Instantaneous Respiratory Frequency as Indicators of Internet Addiction Using Rule-Based Machine Learning
Internet addiction (IA) has adverse effects on psychophysiological responses, interpersonal relationships, and academic and occupational performance. IA detection has received increasing attention. Although questionnaires enable long-term assessment (over 6 months) and physiological measurements to aid the short-term evaluation (over 2 min) of IA, the lack of algorithms results in an inability to detect IA in…
Read MoreiDRP Framework: An Intelligent Malware Exploration Framework for Big Data and Internet of Things (IoT) Ecosystem
The Internet of Things (IoT) is at a face paced growth in the advanced Industrial Revolution (IR) 4.0 in the modern digital world. Considering the current network security challenges and sophistication of attacks in the heavily computerized and interconnected systems, such as an IoT ecosystem, the need for an innovative, robust, intelligent and adaptive malware…
Read MoreAcoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation
The data distribution used in model training is assumed to be similar with that when the model is applied. However, in some applications, data distributions may change over time. This situation is called the concept drift, which might decrease the model performance because the model is trained and evaluated in different distributions. To solve this…
Read MoreCoupled Apodization Functions Applied to Enhance Image Quality in Ultrasound Imaging using Phased Arrays
The remarkable presence of side lobes levels in ultrasound B-mode imaging significantly decreases the image quality. Therefore, the use of an apodization function is of great importance. Linear windowing functions are among the most efficient techniques used to optimize antenna directivity by suppression of the side lobes. However, the apodization causes the degradation of lateral…
Read MoreEmotion Mining from Speech in Collaborative Learning
Affective states, a dimension of attitude, have a critical role in the learning process. In the educational setting, affective states are commonly captured by self-report tools or based on sentiment analysis on asynchronous textual chats, discussions, or students’ journals. Drawbacks of such tools include: distracting the learning process, demanding time and commitment from students to…
Read MoreThe Effect of Myocardial Fat’s Thickness and Myocardial Impedance on Bipolar Radiofrequency Catheter Ablation Using Computer Simulation
Radiofrequency catheter ablation is routinely used for the therapy of cardiac arrhythmias. Compared with the traditional unipolar ablation, bipolar ablation may improve the controllability of treatment, and prevent side effects and complications caused by catheter ablation. In addition, the variations of myocardial fat’s thickness and myocardial impedance may have significant influence on the performance of…
Read MoreAnalysis of Grid Events Influenced by Different Levels of Renewable Integration on Extra-large Power Systems
In this work, the impact of implementing a large amount of decentralized renewable energy sources (RES) of different scales on an extra-large power grid is investigated. Three scenarios are created, substituting 10%, 20%, and 30% of the conventional energy production by RES. For this purpose, the initial dynamic model of Continental Europe in combination with…
Read MoreTraditional and Deep Learning Approaches for Sentiment Analysis: A Survey
Presently, individuals generate tremendous volumes of information on the internet. As a result, sentiment analysis is a critical tool for automating a deep understanding of user-generated information. Of late, deep learning algorithms have shown endless promises for a variety of sentiment analysis. The purpose of sentiment analysis is to categorize different descriptions as good, bad,…
Read MoreA Design of Anthropomorphic Hand based on Human Finger Anatomy
In the past decade, multiple anthropomorphic prosthetic hands have been developed to replace the role of human hands. Prostheses should not only replace the functions of human hands in functionality but also replicate human hands in appearance and sense of body-belonging intuitively. Human fingers have very delicate and complex structures, and it is these complex…
Read MoreQuantum Secure Lightweight Cryptography with Quantum Permutation Pad
Quantum logic gates represent certain quantum operations to perform quantum computations. Of those quantum gates, there is a category of classical behavior gates called quantum permutation gates. As a quantum algorithm, quantum permutation pad or QPP consists of multiple quantum permutation gates to be implemented both in a quantum computing system as a quantum circuit…
Read MoreA Scheduling Algorithm with RTiK+ for MIL-STD-1553B Based on Windows for Real-Time Operation System
In devices using Windows operating system based on x86 system, the real-time performance is not guaranteed by Windows. It is because Windows is not a real-time operating system. Users who develop applications in such a Windows environment generally use commercial solutions such as the RTX or the INtime to provide real-time performance to the system.…
Read MoreAutomated Agriculture Commodity Price Prediction System with Machine Learning Techniques
The intention of this research is to study and design an automated agriculture commodity price prediction system with novel machine learning techniques. Due to the increasing large amounts historical data of agricultural commodity prices and the need of performing accurate prediction of price fluctuations, the solution has largely shifted from statistical methods to machine learning…
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