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Keyword: BoostParticle Swarm Optimization, Genetic Algorithm and Grey Wolf Optimizer Algorithms Performance Comparative for a DC-DC Boost Converter PID Controller
Power converters are electronic devices widely applied in industry, and in recent years, for renewable energy electronic systems, they can regulate voltage levels and actuate as interfaces, however, to do so, is needed a controller. Proportional-Integral-Derivative (PID) are applied to power converters comparing output voltage versus a reference voltage to reduce and anticipate error. Using…
Read MoreMalware Classification Using XGboost-Gradient Boosted Decision Tree
In this industry 4.0 and digital era, we are more dependent on the use of communication and various transaction such as financial, exchange of information by various means. These transaction needs to be secure. Differentiation between the use of benign and malware is one way to make these transactions secure. We propose in this work…
Read MorePerformance Investigation of Semiconductor Devices using Commutation-speed based methodology for the application of Boost Power Factor Correction
In this paper, behavioral approach has been adopted for the calculation of total power losses that has been further used to derive an analytical model for the conduction and switching losses in a boost Power Factor Correction (PFC) stage of an On-board Charger (OBC). Detailed investigation of power losses can help in finding out ways…
Read MoreMachine Learning Methods for University Student Performance Prediction in Basic Skills based on Psychometric Profile
Ensuring the quality of higher education in Brazil presents a complex challenge, intensified by factors that directly affect students’ academic performance. The pervasive influence of social media and the overconsumption of superficial digital content undermine students’ ability to engage in deep comprehension, critical thinking, and the practical application of knowledge. Furthermore, inadequate preparation during the…
Read MoreUtilizing 3D models for the Prediction of Work Man-Hour in Complex Industrial Products using Machine Learning
The integration of machine learning techniques in industrial production has the potential to revolutionize traditional manufacturing processes. In this study, we examine the efficacy of gradient-boosting machine learning models, specifically focusing on feature engineering techniques, applied to a novel dataset with 3D product models pertaining to work moan-hours in metal sheet stamping projects, framed as…
Read MoreLeveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…
Read MoreTree-Based Ensemble Models, Algorithms and Performance Measures for Classification
An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…
Read MoreMobility Intelligence: Machine Learning Methods for Received Signal Strength Indicator-based Passive Outdoor Localization
Knowledge of pedestrian and vehicle movement patterns can provide valuable insights for city planning. Such knowledge can be acquired via passive outdoor localization of WiFi-enabled devices using measurements of Received Signal Strength Indicator (RSSI) from WiFi probe requests. In this paper, which is an extension of the work initially presented in WiMob 2021, we continue…
Read MoreEnsemble Extreme Learning Algorithms for Alzheimer’s Disease Detection
Alzheimer’s disease has proven to be the major cause of dementia in adults, making its early detection an important research goal. We have used Ensemble ELMs (Extreme Learning Models) on the OASIS (Open Access Series of Imaging Studies) data set for Alzheimer’s detection. We have explored various single layered light-weight ELM networks. This is an…
Read MoreCOVIDFREE App: The User-Enabling Contact Prevention Application: A Review
The use of Covid-19 contact tracing applications has become almost irrelevant now that several flavors of Covid-19 vaccine have been developed and are constantly being distributed to people during the pandemic to help alleviate the need for lockdowns. Also, the availability of at-home testing kits and testing sites means that people do not need to…
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 MoreStudy and Implementation of LEDs Drivers with Dimming Capability
Nowadays, LED lights take an important place in our daily lives and they have known a great growth in indoor as well as in outdoor lighting applications. LED (Light Emitting Diode) light sources including their own drivers have excluded many systems fitted with both inefficient light sources. In this paper we present, a LED driver…
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 MoreLeveraging Energy Efficiency Investments: An Innovative Web-based Benchmarking Tool
Energy Efficiency (EE) plays a key role in decreasing energy consumption at a European level, while it is considered as one of the most cost-efficient means to achieve carbon reduction and reinforce energy sufficiency and security. EE financing is imperative to implement measures that will lead to achieving the desired carbon neutrality and, thus, avert…
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…
Read MorePower Converters and EMS for Fuel Cells CCHP Applications: A Structural and Extended Review
Fuel Cells (FCs) and Combined Cooling, Heating and Power (CCHP) systems are becoming very popular due to their environmental friendliness and immense applications. This extended review paper commenced by introducing the rampant South Africa’s electricity crisis as the basis for the study, followed by some structural analyses of up to forty-four miscellaneous power electronics converters…
Read MoreConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
Read MoreComparative Study of Control Algorithms Through Different Converters to Improve the Performance of a Solar Panel
This article aims at comparing two controls to follow the maximum power point, making use of DC-DC converters for PV uses. All transformers operate continuously. To fulfil maximum power, we will exploit two MPPT controls: a traditional perturb – observe ‘P&O’ and a smart one – the fuzzy logic ‘FL’. The goal of this article…
Read MoreNeural Networks and Fuzzy Logic Based Maximum Power Point Tracking Control for Wind Energy Conversion System
In grid connected wind turbine (WT) systems, the maximum power point tracking (MPPT) approach has a crucial role in optimizing the wind energy efficiency. To search for the maximum power value of the wind turbine, this contribution proposes a new Maximum Power Point Tracking System (MPPT) for wind turbine related to a permanent magnet synchronous…
Read MoreGreen Blocks Made of Recycled Construction Waste using Recycled Wastewater
This study tests the feasibility of manufacturing concrete blocks made of recycled materials. The paper is an extension of work originally presented in ASET conference in Dubai. The paper, depicts and analyzes how the characteristics of the blocks (strength/durability) are affected by the presence of recycled concrete ingredients (recycled aggregate (RA)) and recycled water (RW).…
Read MoreOpen Energy Distribution System-Based on Photo-voltaic with Interconnected- Modified DC-Nanogrids
This manuscript exhibits a perfect design for a flexible number of modified DC nanogrids within an open energy distribution network (OEDN) that interconnected via a DC bus. Each modified nanogrid implies a single-input multi-output switched boost inverter (SIMO-SBI). The DC-output for each inverter is robustly controlled to keep the DC-bus interconnected voltage constant. The proposed…
Read MoreMultiple Machine Learning Algorithms Comparison for Modulation Type Classification Based on Instantaneous Values of the Time Domain Signal and Time Series Statistics Derived from Wavelet Transform
Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…
Read MoreUpdated Analysis of Business Continuity Issues Underlying the Certification of Invoicing Software, Considering a Pandemic Scenario
Portuguese organizations that have invoicing software, certified by the Tax and Customs Authority, need to comply with technical requirements that involve business continuity and disaster recovery. The recent tax legislative changes created conditions for the dematerialization of documents, allowing waiving invoice printing, encouraging the adoption of an electronic invoicing and document archiving system. The pandemic…
Read MorePerformance Analysis and Enhancement of Spline Adaptive Filtering based on Adaptive Step-size Variable Leaky Least Mean Square Algorithm
This paper presents an adaptive step-size and variable leaky least mean square algorithm based on nonlinear adaptive filter with the adaptive lookup table using spline interpolation. An adaptive step-size approach is proposed with the energy of squared previous and present errors to boost up the convergence rate. A modified variable leaky mechanism is proposed with…
Read MoreFast and Efficient Maximum Power Point Tracking Controller for Photovoltaic Modules
This paper presents an efficient Maximum Power Point Tracking (MPPT) controller for photovoltaic modules. The MPPT technique consists of a combination between backstepping controller and artificial neural network (ANN).The (ANN) has been employed to generate the optimum voltage, which corresponds to the maximum power voltage delivered by photovoltaic modules, while the backstepping controller is developed…
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