This article is part of the field of Multi-Criteria Decision Aid (MCDA), where several criteria must be considered in decision making. All criteria are generally as varied as possible and express different dimensions, and aspects of the decision problem posed. For more than four decades, several MCDA methods have emerged and have been applied perfectly…

This paper addresses essential features/issues and proposes solutions that would improve the overall performance of a multi-phase buck converter. Low efficiency at light load is addressed with phase shedding, load fast transient and regulated output voltage spiking/dipping is addressed with novel helper technique at the point of load (output node). An Integrated current sensing is…

Novel ionic polymers were synthesized by crosslinking of poly (vinylalcohol) (PVA) with sulfosuccinic acid (SSA) and silicotungstic acid (SiWA) with or without silica. The polymer electrolyte membrane fuel cell (PEMFC) was developed using solution casting method. Infrared (IR) spectra revealed that the Keggin structure was insered in the PVA films. The thermal decomposition of the…

Several challenges like changes in brightness, dynamic background, occlusion and inconsistency of camera position make the recognition of hand gestures difficult in any vision-based method. Diversity in finger shape, size, distribution and motion dynamics is also a big constraint. This leads to the motivation in developing a dense Scale Invariant Feature Transform (SIFT) flow based…

In recent years, the transport of large packages with super weight from 100 tons to several thousand tons is no longer a difficult problem due to the continuous development of technology. Experienced transport companies, specializing in transporting heavy goods in Vietnam, have invested in very modern equipment and machinery such as self-propelled trailers of Cometto…

Estimation of displacement is an information required for daily operation monitoring systems to monitor human health or to locate users in buildings, basements, tunnels and similar places which under the same conditions that the global positioning signal (GPS) level is from very weak to completely absent; and is the measurement technique by using multimetric data…

This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…

Electrical and optical properties of polymer nanocomposite thin films have been analyzed to study their reliability and competency as a component for optoelectronic devices such as LED and solar cells. Polymer nanocomposite encounters various challenges, such as the dispersion of nanoparticles in the matrix that hinders their efficiency for potential devices. In this paper, two…

The crisis linked to the COVID-19 and the uncertainty it generates in the unprecedented health, societal, economic and financial fields have had a strong impact on the stock markets. Indeed, in such a climate of very high uncertainty, it is to be expected that the excessive stock market price movements will continue, with both declines…

Dynamic modeling has been a crucial study in many areas of the engineering field. In this paper, we apply the Newton-Euler equation of motion to a two-DOF parallel mechanism solar tracker which is a close loop mechanism. The aim of this study is to show a simulation of the dynamical model with feedback control using…

The insulation condition of a transformer decides the longevity of the equipment. The unpredicted failure of power transformer will lead to major disaster in the distribution network and it affects both environment and public safety. Nowadays synthetic oil and natural esters are alternatives to transformer oil because of the biodegradable nature. In this paper, investigations…

Storage-Class Memory (SCM) like OptaneTM has advanced as a fast storage medium, and conventional memory management systems designed for the hard disk storage need to be reconsidered. In this article, we revisit the memory management system that adopts SCM as the underlying storage medium and discuss the issues in two layers: file caching and virtual…

Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…

Increased recycling of PVC has become a requirement in industrial and scientific research level. Several studies will be realized. To confirm and check the recycled materials performance, it will be important to go through numerical modeling, which consists not only in validating the results of the experiments, but also in predicting what happens when the…

ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring…

Modern digitalized cyber domains are extremely complex ensemble. Cyber attacks or incidents against system may affect capricious effects for another system or even for physical devices. For understanding and training to encounter those effects requires an effective and complex simulation capability. Cyber Security Exercises are an effective expedient for training and learning measures and operations…

In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…

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…

This paper deals with a multi closed-loop adaptive neuro-fuzzy inference system (ANFIS) design for the under-actuated quadrotor systems. First, the training data set for the fuzzy inference system is obtained using a proportional integral derivative controller. Then, an initial ANFIS controller is designed, where the integral control action is preserved in the multi-closed-cloop ANFIS for…

Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…

Nigerian power utility companies particularly the distribution and generation aspects were recently in the process of national power reform converted from public to private service by privatization. Prior to these development, power utility companies’ performance is low due to poor operational style that leads to inadequate revenue generation. Thus, the task before the privatized companies…

In this article, we concentrate on the use of a metaheuristic technique based on an Evolutionary Algorithm (EA) for determining the optimal geometrical parameters of spiral inductors for RF circuits. For this purpose, we have opted for an optimization procedure through an enhanced Differential Evolution (DE) algorithm. The proposed tool allows the design of optimized…

The ability to verify the critical risk factors related to an effective diagnosis is very crucial for improving accuracy on coronary heart disease prediction. The objective of this research is to find the best predictive model for coronary heart disease diagnosis. Three approaches are set up to achieve the goals (1) investigating the classifier algorithms…

Application in the field of medical development has always been one of the most important research areas. One of these medical applications is the early prediction system for heart diseases especially; coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support system is to detect atherosclerosis at the earlier stages to…

With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…