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Keyword: ModelAn Interdisciplinary Approach to Fracture of Solids from the Standpoint of Condensed Matter Physics
Instead of approaches of solid mechanics or a formal description of experimental data an interdisciplinary approach is proposed to consider failure and deformation as thermodynamic processes. Mathematical modeling of the processes is carried out using rheological models of the material. One fracture criterion is used, that formally corresponds to the achievement of a threshold concentration…
Read MoreA Study on Novel Hand Hygiene Evaluation System using pix2pix
The novel coronavirus infection (COVID-19), which appeared at the end of 2019 has developed into a global pandemic with numerous deaths, and has also become a serious social concern. The most important and basic measure for preventing infection is hand hygiene. In this study, by photographing palm images of nursing students after hand-washing, using fluorescent…
Read MoreStability Analysis of a DC Microgrid with Constant Power Load
DC Microgrids (DCMGs) aggregate and integrate various distribution generation (DG) units through the use of power electronic converters (PECs) that are present on both the source side and the load side of the DCMGs. Tightly regulated PECs at the load side behave as constant power loads (CPLs) and may promote instability in the entire DCMG.…
Read MoreTaxonomy of Security Techniques for Routing Protocols in Mobile Ad-hoc Networks
The Nodes equipped with wireless technology cooperate in an autonomous and instantaneous way to form a mobile ad hoc network. It turns out that several factors make this type of network vulnerable to various security threats. Considering the sensitivity of user data routed through nodes, routing security should be a priority in mobile ad hoc…
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 MoreEstimation of Non-homogeneous Thermal Conductivity using Fourier Heat Equation Considering Uncertainty and Error Propagation
The present work develops an estimator for thermal conductivity using a simple exper- iment implemented in a simulated solid metallic bar. The bar is sectioned in a finite number of segments, lately called nodes, and a discretization of the Fourier heat equation is applied in each node to generate a timed-spaced model of the temperature…
Read MoreDiscretisation of Second Order Generalized Integrator to Design the Control Algorithm of Unified Power Quality Conditioner
In this paper, second order generalized integrator (SOGI) is discretized to design the control algorithm of unified power quality conditioner (UPQC). A UPQC is combination two voltage source converter (VSC) and VSC are connected with back to back DC link. The first one VSC is in series to maintain the desire voltage at point of…
Read MoreInnovations in Recruitment—Social Media
The main objective and contribution of the paper is to describe the creation of a model to support recruitment using social media information and its deployment in practice. The model includes the design of an automated solution for downloading social media data and a proposal for the subsequent analysis and creation of a predictive model…
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 MoreAssessment of Transformer Cellulose Insulation Life Expectancy Based on Oil Furan Analysis (Case Study: South African Transformers)
The ageing of oil-immersed power transformers triggers several defects and damages in the insulating materials, particularly in the cellulose insulation. The decomposition of the cellulose paper produces dissolved gases into the insulating oil, in which the Dissolved Gas Analysis (DGA) of the oil samples can provide insights to incipient faults sustained by the transformer as…
Read MoreImpact Assessment of the Renewable Energy Sources Implementation in Bulgarian Single-Family Houses on the Greenhouse Gas by HOMER Pro Software
It is widely known that cities now house more than half of the world’s population. Within this framework, this study presents the possibilities for real-world application of renewable energy sources (RES) in urban areas, as well as their contribution to the urban deployment of the new energy paradigm. A comparison is made between hybrid power…
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 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 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 MoreMachine Learning Algorithms for Real Time Blind Audio Source Separation with Natural Language Detection
The Conv-TasNet and Demucs algorithms, can differentiate between two mixed signals, such as music and speech, the mixing operation proceed without any support information. The network of convolutional time-domain audio separations is used in Conv-TasNet algorithm, while there is a new waveform-to-waveform model in Demucs algorithm. The Demucs algorithm utilizes a procedure like the audio…
Read MoreA Summary of Canonical Multivariate Permutation Entropies on Multivariate Fractional Brownian Motion
Real-world applications modelled by time-dependent dynamical systems with specific properties such as long-range dependence or self-similarity are usually described by fractional Brownian motion. The investigation of the qualitative behaviour of its realisations is an important topic. For this purpose, efficient mappings from realisations of the dynamical system, i.e., time series, to a set of scalar-valued…
Read MoreA Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern
The ocean surface temperatures or sea surface temperatures have a significant influence on local and global weather. The change in sea surface temperatures will lead to the change in rainfall patterns. In this paper, the long-term rainfall forecasting is developed for planning and decision making in water resource management. The similarity of sea surface temperature…
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 MoreSurvey on Novelty Detection using Machine Learning Techniques
Novelty detection affords to identify data patterns that stray strikingly from the normal behavior. it allows a good identification and classification of objects which were not known during the learning phase of the model. In this article, we will introduce an organized and comprehensive review of the study on novelty detection. We have grouped existing…
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 MoreThe Design and Implementation of Intelligent English Learning Chabot based on Transfer Learning Technology
Chatbot operates task-oriented customer services in special and open domains at different mobile devices. Its related products such as knowledge base Question-Answer System also benefit daily activities. Chatbot functions generally include automatic speech recognition (ASR), natural language understanding (NLU), dialogue management (DM), natural language generation (NLG) and speech synthesis (SS). In this paper, we proposed…
Read MorePredicting School Children Academic Performance Using Machine Learning Techniques
The study aims to assess the machine learning techniques in predicting students’ associated factors that affect their academic performance. The study sample consisted of 5084 middle and high school students between the ages of 10 and 17, attending public and UNRWA schools in the West Bank. The ‘Health Behaviors School Children’ questionnaire for the 2013-2014…
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 MorePersonalized Clinical Treatment Selection Using Genetic Algorithm and Analytic Hierarchy Process
The development of Machine Learning methods and approaches offers enormous growth opportunities in the Healthcare field. One of the most exciting challenges in this field is the automation of clinical treatment selection for patient state optimization. Using necessary medical data and the application of Machine Learning methods (like the Genetic Algorithm and the Analytic Hierarchy…
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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