Vol.67, No.3, 2021-Table of Contents
  • Time-Aware PolarisX: Auto-Growing Knowledge Graph
  • Abstract A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge. Research is being actively conducted to cover a wide variety of knowledge, as it can be applied to applications that help humans. However, existing researches are constructing knowledge graphs without the time information that knowledge implies. Knowledge stored without time information becomes outdated over time, and in the future, the possibility of knowledge being false or meaningful changes is excluded. As a result, they can’t reflect information that changes dynamically, and they can’t accept information that has newly… More
  •   Views:1207       Downloads:855        Download PDF
  • Time-Series Data and Analysis Software of Connected Vehicles
  • Abstract In this study, we developed software for vehicle big data analysis to analyze the time-series data of connected vehicles. We designed two software modules: The first to derive the Pearson correlation coefficients to analyze the collected data and the second to conduct exploratory data analysis of the collected vehicle data. In particular, we analyzed the dangerous driving patterns of motorists based on the safety standards of the Korea Transportation Safety Authority. We also analyzed seasonal fuel efficiency (four seasons) and mileage of vehicles, and identified rapid acceleration, rapid deceleration, sudden stopping (harsh braking), quick starting, sudden left turn, sudden right… More
  •   Views:862       Downloads:658        Download PDF
  • Efficient MCDM Model for Evaluating the Performance of Commercial Banks: A Case Study
  • Abstract Evaluation of commercial banks (CBs) performance has been a significant issue in the financial world and deemed as a multi-criteria decision making (MCDM) model. Numerous research assesses CB performance according to different metrics and standers. As a result of uncertainty in decision-making problems and large economic variations in Egypt, this research proposes a plithogenic based model to evaluate Egyptian commercial banks’ performance based on a set of criteria. The proposed model evaluates the top ten Egyptian commercial banks based on three main metrics including financial, customer satisfaction, and qualitative evaluation, and 19 sub-criteria. The proportional importance of the selected criteria… More
  •   Views:957       Downloads:743        Download PDF
  • ExpressionHash: Securing Telecare Medical Information Systems Using BioHashing
  • Abstract The COVID-19 outbreak and its medical distancing phenomenon have effectively turned the global healthcare challenge into an opportunity for Telecare Medical Information Systems. Such systems employ the latest mobile and digital technologies and provide several advantages like minimal physical contact between patient and healthcare provider, easy mobility, easy access, consistent patient engagement, and cost-effectiveness. Any leakage or unauthorized access to users’ medical data can have serious consequences for any medical information system. The majority of such systems thus rely on biometrics for authenticated access but biometric systems are also prone to a variety of attacks like spoofing, replay, Masquerade, and… More
  •   Views:793       Downloads:580        Download PDF
  • A Cell-Based Smoothed Finite Element Method for Modal Analysis of Non-Woven Fabrics
  • Abstract The combination of a 4-node quadrilateral mixed interpolation of tensorial components element (MITC4) and the cell-based smoothed finite element method (CSFEM) was formulated and implemented in this work for the analysis of free vibration and unidirectional buckling of shell structures. This formulation was applied to numerous numerical examples of non-woven fabrics. As CSFEM schemes do not require coordinate transformation, spurious modes and numerical instabilities are prevented using bilinear quadrilateral element subdivided into two, three and four smoothing cells. An improvement of the original CSFEM formulation was made regarding the calculation of outward unit normal vectors, which allowed to remove the… More
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  • Smart Dynamic Traffic Monitoring and Enforcement System
  • Abstract Enforcement of traffic rules and regulations involves a wide range of complex tasks, many of which demand the use of modern technologies. variable speed limits (VSL) control is to change the current speed limit according to the current traffic situation based on the observed traffic conditions. The aim of this study is to provide a simulation-based methodological framework to evaluate (VSL) as an effective Intelligent Transportation System (ITS) enforcement system. The focus of the study is on measuring the effectiveness of the dynamic traffic control strategy on traffic performance and safety considering various performance indicators such as total travel time,… More
  •   Views:775       Downloads:712        Download PDF
  • EP-Bot: Empathetic Chatbot Using Auto-Growing Knowledge Graph
  • Abstract People occasionally interact with each other through conversation. In particular, we communicate through dialogue and exchange emotions and information from it. Emotions are essential characteristics of natural language. Conversational artificial intelligence is an integral part of all the technologies that allow computers to communicate like humans. For a computer to interact like a human being, it must understand the emotions inherent in the conversation and generate the appropriate responses. However, existing dialogue systems focus only on improving the quality of understanding natural language or generating natural language, excluding emotions. We propose a chatbot based on emotion, which is an essential… More
  •   Views:741       Downloads:977        Download PDF
  • Computing the User Experience via Big Data Analysis: A Case of Uber Services
  • Abstract As of 2020, the issue of user satisfaction has generated a significant amount of interest. Therefore, we employ a big data approach for exploring user satisfaction among Uber users. We develop a research model of user satisfaction by expanding the list of user experience (UX) elements (i.e., pragmatic, expectation confirmation, hedonic, and burden) by including more elements, namely: risk, cost, promotion, anxiety, sadness, and anger. Subsequently, we collect 125,768 comments from online reviews of Uber services and perform a sentiment analysis to extract the UX elements. The results of a regression analysis reveal the following: hedonic, promotion, and pragmatic significantly… More
  •   Views:890       Downloads:506        Download PDF
  • Pashto Characters Recognition Using Multi-Class Enabled Support Vector Machine
  • Abstract During the last two decades significant work has been reported in the field of cursive language’s recognition especially, in the Arabic, the Urdu and the Persian languages. The unavailability of such work in the Pashto language is because of: the absence of a standard database and of significant research work that ultimately acts as a big barrier for the research community. The slight change in the Pashto characters’ shape is an additional challenge for researchers. This paper presents an efficient OCR system for the handwritten Pashto characters based on multi-class enabled support vector machine using manifold feature extraction techniques. These… More
  •   Views:741       Downloads:683        Download PDF
  • Feasibility-Guided Constraint-Handling Techniques for Engineering Optimization Problems
  • Abstract The particle swarm optimization (PSO) algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and fish. PSO is essentially an unconstrained algorithm and requires constraint handling techniques (CHTs) to solve constrained optimization problems (COPs). For this purpose, we integrate two CHTs, the superiority of feasibility (SF) and the violation constraint-handling (VCH), with a PSO. These CHTs distinguish feasible solutions from infeasible ones. Moreover, in SF, the selection of infeasible solutions is based on their degree of constraint violations, whereas in VCH, the number of constraint violations by an infeasible solution is of more importance. Therefore,… More
  •   Views:819       Downloads:688        Download PDF
  • Identification of Antimicrobial Peptides Using Chou’s 5 Step Rule
  • Abstract With the advancement in cellular biology, the use of antimicrobial peptides (AMPs) against many drug-resistant pathogens has increased. AMPs have a broad range of activity and can work as antibacterial, antifungal, antiviral, and sometimes even as anticancer peptides. The traditional methods of distinguishing AMPs from non-AMPs are based only on wet-lab experiments. Such experiments are both time-consuming and expensive. With the recent development in bioinformatics more and more researchers are contributing their effort to apply computational models to such problems. This study proposes a prediction algorithm for classifying AMPs and distinguishing between AMPs and non-AMPs. The proposed methodology uses machine… More
  •   Views:874       Downloads:644        Download PDF
  • Minimum Error Entropy Based EKF for GPS Code Tracking Loop
  • Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error criterion is limited to the… More
  •   Views:584       Downloads:493        Download PDF
  • Model of Fractional Heat Conduction in a Thermoelastic Thin Slim Strip under Thermal Shock and Temperature-Dependent Thermal Conductivity
  • Abstract The present paper paper, we estimate the theory of thermoelasticity a thin slim strip under the variable thermal conductivity in the fractional-order form is solved. Thermal stress theory considering the equation of heat conduction based on the time-fractional derivative of Caputo of order α is applied to obtain a solution. We assumed that the strip surface is to be free from traction and impacted by a thermal shock. The transform of Laplace (LT) and numerical inversion techniques of Laplace were considered for solving the governing basic equations. The inverse of the LT was applied in a numerical manner considering the… More
  •   Views:579       Downloads:542        Download PDF
  • Analysis of Silver Nanoparticles in Engine Oil: Atangana–Baleanu Fractional Model
  • Abstract The present article aims to examine the heat and mass distribution in a free convection flow of electrically conducted, generalized Jeffrey nanofluid in a heated rotatory system. The flow analysis is considered in the presence of thermal radiation and the transverse magnetic field of strength B0. The medium is porous accepting generalized Darcy’s law. The motion of the fluid is due to the cosine oscillations of the plate. Nanofluid has been formed by the uniform dispersing of the Silver nanoparticles in regular engine oil. The problem has been modeled in the form of classical partial differential equations and then generalized… More
  •   Views:545       Downloads:425        Download PDF
  • Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection
  • Abstract Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics,… More
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  • Security Threats to Business Information Systems Using NFC Read/Write Mode
  • Abstract Radio Frequency IDentification (RFID) and related technologies such as Near Field Communication (NFC) are becoming essential in industrial contexts thanks to their ability to perform contactless data exchange, either device-to-device or tag-to-device. One of the three main operation modes of NFC, called read/write mode, makes use of the latter type of interaction. It is extensively used in business information systems that make use of NFC tags to provide the end-user with augmented information in one of several available NFC data exchange formats, such as plain text, simple URLs or enriched URLs. Using a wide variety of physical form factors, NFC-compatible… More
  •   Views:750       Downloads:707        Download PDF
  • Transmission and Reflection of Water-Wave on a Floating Ship in Vast Oceans
  • Abstract In this paper, we study the water-wave flow under a floating body of an incident wave in a fluid. This model simulates the phenomenon of waves abording a floating ship in a vast ocean. The same model, also simulates the phenomenon of fluid-structure interaction of a large ice sheet in waves. According to this method. We divide the region of the problem into three subregions. Solutions, satisfying the equation in the fluid mass and a part of the boundary conditions in each subregion, are given. We obtain such solutions as infinite series including unknown coefficients. We consider a limited number… More
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  • Energy-Efficient Transmission Range Optimization Model for WSN-Based Internet of Things
  • Abstract With the explosive advancements in wireless communications and digital electronics, some tiny devices, sensors, became a part of our daily life in numerous fields. Wireless sensor networks (WSNs) is composed of tiny sensor devices. WSNs have emerged as a key technology enabling the realization of the Internet of Things (IoT). In particular, the sensor-based revolution of WSN-based IoT has led to considerable technological growth in nearly all circles of our life such as smart cities, smart homes, smart healthcare, security applications, environmental monitoring, etc. However, the limitations of energy, communication range, and computational resources are bottlenecks to the widespread applications… More
  •   Views:859       Downloads:656        Download PDF
  • Prediction Models for COVID-19 Integrating Age Groups, Gender, and Underlying Conditions
  • Abstract The COVID-19 pandemic has caused hundreds of thousands of deaths, millions of infections worldwide, and the loss of trillions of dollars for many large economies. It poses a grave threat to the human population with an excessive number of patients constituting an unprecedented challenge with which health systems have to cope. Researchers from many domains have devised diverse approaches for the timely diagnosis of COVID-19 to facilitate medical responses. In the same vein, a wide variety of research studies have investigated underlying medical conditions for indicators suggesting the severity and mortality of, and role of age groups and gender on,… More
  •   Views:922       Downloads:669        Download PDF
  • Deep Learning-Based Hookworm Detection in Wireless Capsule Endoscopic Image Using AdaBoost Classifier
  • Abstract Hookworm is an illness caused by an internal sponger called a roundworm. Inferable from deprived cleanliness in the developing nations, hookworm infection is a primary source of concern for both motherly and baby grimness. The current framework for hookworm detection is composed of hybrid convolutional neural networks; explicitly an edge extraction framework alongside a hookworm classification framework is developed. To consolidate the cylindrical zones obtained from the edge extraction framework and the trait map acquired into the hookworm scientific categorization framework, pooling layers are proposed. The hookworms display different profiles, widths, and bend directions. These challenges make it difficult for… More
  •   Views:710       Downloads:542        Download PDF
  • Improved Hybrid Beamforming for mmWave Multi-User Massive MIMO
  • Abstract Massive multiple input multiple output (MIMO) has become essential for the increase of capacity as the millimeter-wave (mmWave) communication is considered. Also, hybrid beamforming systems have been studied since full-digital beamforming is impractical due to high cost and power consumption of the radio frequency (RF) chains. This paper proposes a hybrid beamforming scheme to improve the spectral efficiency for multi-user MIMO (MU-MIMO) systems. In a frequency selective fading environment, hybrid beamforming schemes suffer from performance degradation since the analog precoder performs the same precoding for all subcarriers. To mitigate performance degradation, this paper uses the average channel covariance matrix for… More
  •   Views:561       Downloads:638        Download PDF
  • Formal Approach to Workflow Application Fragmentations Over Cloud Deployment Models
  • Abstract Workflow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments. Especially, such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workflow processes and applications with scalable on-demand services. In this paper, we focus on the distribution paradigm and its deployment formalism for such very large-scale workflow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments. We propose a formal approach to vertically as well as horizontally fragment very large-scale workflow processes and their applications and… More
  •   Views:903       Downloads:459        Download PDF
  • A New Optimized Wrapper Gene Selection Method for Breast Cancer Prediction
  • Abstract Machine-learning algorithms have been widely used in breast cancer diagnosis to help pathologists and physicians in the decision-making process. However, the high dimensionality of genetic data makes the classification process a challenging task. In this paper, we propose a new optimized wrapper gene selection method that is based on a nature-inspired algorithm (simulated annealing (SA)), which will help select the most informative genes for breast cancer prediction. These optimal genes will then be used to train the classifier to improve its accuracy and efficiency. Three supervised machine-learning algorithms, namely, the support vector machine, the decision tree, and the random forest… More
  •   Views:646       Downloads:658        Download PDF
  • Residual U-Network for Breast Tumor Segmentation from Magnetic Resonance Images
  • Abstract Breast cancer positions as the most well-known threat and the main source of malignant growth-related morbidity and mortality throughout the world. It is apical of all new cancer incidences analyzed among females. Two features substantially influence the classification accuracy of malignancy and benignity in automated cancer diagnostics. These are the precision of tumor segmentation and appropriateness of extracted attributes required for the diagnosis. In this research, the authors have proposed a ResU-Net (Residual U-Network) model for breast tumor segmentation. The proposed methodology renders augmented, and precise identification of tumor regions and produces accurate breast tumor segmentation in contrast-enhanced MR images.… More
  •   Views:821       Downloads:731        Download PDF
  • Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning
  • Abstract Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet. The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric. In a hyperconverged cloud ecosystem environment, building high-reliability cloud applications is a challenging job. The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings. The emergence of cloud computing is significantly reshaping the digital ecosystem, and the numerous services offered by cloud service providers are playing a vital role in this transformation. Hyperconverged… More
  •   Views:663       Downloads:452        Download PDF
  • Applying and Comparison of Chaotic-Based Permutation Algorithms for Audio Encryption
  • Abstract This research presents, and clarifies the application of two permutation algorithms, based on chaotic map systems, and applied to a file of speech signals. They are the Arnold cat map-based permutation algorithm, and the Baker’s chaotic map-based permutation algorithm. Both algorithms are implemented on the same speech signal sample. Then, both the premier and the encrypted file histograms are documented and plotted. The speech signal amplitude values with time signals of the original file are recorded and plotted against the encrypted and decrypted files. Furthermore, the original file is plotted against the encrypted file, using the spectrogram frequencies of speech… More
  •   Views:552       Downloads:538        Download PDF
  • Web Application Commercial Design for Financial Entities Based on Business Intelligence
  • Abstract Multiple customer data management has become a focus of attention in big organizations. Although much information is available, it does not translate into significant profitable value-added services. We present a design of a commercial web application based on business intelligence that generates information on social and financial behavior of clients in an organization; with the purpose of obtain additional information that allows to get more profits. This app will provide a broader perspective for making strategic decisions to increase profits and reduce internal investment costs. A case in point is the financial sector, a group of financial entities were used… More
  •   Views:966       Downloads:492        Download PDF
  • Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems
  • Abstract Energy efficiency (EE) is a critical design when taking into account circuit power consumption (CPC) in fifth-generation cellular networks. These problems arise because of the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, attributable to inter-cell interference for channel state information. Apart from that, a higher number of radio frequency (RF) chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers. Therefore, antenna selection, user selection, optimal transmission power, and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems. This work… More
  •   Views:892       Downloads:686        Download PDF
  • Epidemiological Analysis of the Coronavirus Disease Outbreak with Random Effects
  • Abstract Today, coronavirus appears as a serious challenge to the whole world. Epidemiological data of coronavirus is collected through media and web sources for the purpose of analysis. New data on COVID-19 are available daily, yet information about the biological aspects of SARS-CoV-2 and epidemiological characteristics of COVID-19 remains limited, and uncertainty remains around nearly all its parameters’ values. This research provides the scientific and public health communities better resources, knowledge, and tools to improve their ability to control the infectious diseases. Using the publicly available data on the ongoing pandemic, the present study investigates the incubation period and other time… More
  •   Views:705       Downloads:584        Download PDF
  • Analyzing Some Elements of Technological Singularity Using Regression Methods
  • Abstract Technological advancement has contributed immensely to human life and society. Technologies like industrial robots, artificial intelligence, and machine learning are advancing at a rapid pace. While the evolution of Artificial Intelligence has contributed significantly to the development of personal assistants, automated drones, smart home devices, etc., it has also raised questions about the much-anticipated point in the future where machines may develop intelligence that may be equal to or greater than humans, a term that is popularly known as Technological Singularity. Although technological singularity promises great benefits, past research works on Artificial Intelligence (AI) systems going rogue highlight the downside… More
  •   Views:714       Downloads:755        Download PDF
  • Effect of Poly-Alkylene-Glycol Quenchant on the Distortion, Hardness, and Microstructure of 65Mn Steel
  • Abstract Currently, the 65Mn steel is quenched mainly by oil media. Even though the lower cooling rate of oil compared to water reduces the hardness of steel post quenching, the deforming and cracking of parts are often minimized. On the other hand, the oil media also has the disadvantage of being flammable, creating smoke that adversely affects the media. The poly alkylene glycol (PAG) polymer quenchant is commonly used for quenching a variety of steels based on its advantages such as non-flammability and flexible cooling rate subjected to varying concentration and stirring speed. This article examines the effect of PAG polymer… More
  •   Views:651       Downloads:443        Download PDF
  • A Heuristics-Based Cost Model for Scientific Workflow Scheduling in Cloud
  • Abstract Scientific Workflow Applications (SWFAs) can deliver collaborative tools useful to researchers in executing large and complex scientific processes. Particularly, Scientific Workflow Scheduling (SWFS) accelerates the computational procedures between the available computational resources and the dependent workflow jobs based on the researchers’ requirements. However, cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate (near-optimal) solution within polynomial computational time. Motivated by this, current work proposes a novel SWFS cost optimization model effective in solving this challenge. The proposed model contains three main stages: (i) scientific workflow application, (ii) targeted computational environment,… More
  •   Views:664       Downloads:456        Download PDF
  • An Efficient Genetic Hybrid PAPR Technique for 5G Waveforms
  • Abstract Non-orthogonal multiple access (NOMA) is a strong contender multicarrier waveform technique for the fifth generation (5G) communication system. The high peak-to-average power ratio (PAPR) is a serious concern in designing the NOMA waveform. However, the arrangement of NOMA is different from the orthogonal frequency division multiplexing. Thus, traditional reduction methods cannot be applied to NOMA. A partial transmission sequence (PTS) is commonly utilized to minimize the PAPR of the transmitting NOMA symbol. The choice phase aspect in the PTS is the only non-linear optimization obstacle that creates a huge computational complication due to the respective non-carrying sub-blocks in the unitary… More
  •   Views:602       Downloads:535        Download PDF
  • Parallel Optimization of Program Instructions Using Genetic Algorithms
  • Abstract This paper describes an efficient solution to parallelize software program instructions, regardless of the programming language in which they are written. We solve the problem of the optimal distribution of a set of instructions on available processors. We propose a genetic algorithm to parallelize computations, using evolution to search the solution space. The stages of our proposed genetic algorithm are: The choice of the initial population and its representation in chromosomes, the crossover, and the mutation operations customized to the problem being dealt with. In this paper, genetic algorithms are applied to the entire search space of the parallelization of… More
  •   Views:953       Downloads:900        Download PDF
  • Epidemic Spreading–Information Dissemination Coupling Mechanism in Heterogeneous Areas
  • Abstract With COVID-19 continuing to rage around the world, there is a spread of epidemic-related information on social networking platforms. This phenomenon may inhibit or promote the scale of epidemic transmission. This study constructed a double-layer epidemic spreading–information dissemination network based on the movements of individuals across regions to analyze the dynamic evolution and coupling mechanism of information dissemination and epidemic transmission. We also proposed measures to control the spread of the epidemic by analyzing the factors affecting dynamic transmission. We constructed a state probability equation based on Markov chain theory and performed Monte Carlo simulations to demonstrate the interaction between… More
  •   Views:595       Downloads:432        Download PDF
  • A Novel Anonymous Authentication Scheme Based on Edge Computing in Internet of Vehicles
  • Abstract The vehicular cloud computing is an emerging technology that changes vehicle communication and underlying traffic management applications. However, cloud computing has disadvantages such as high delay, low privacy and high communication cost, which can not meet the needs of real-time interactive information of Internet of vehicles. Ensuring security and privacy in Internet of Vehicles is also regarded as one of its most important challenges. Therefore, in order to ensure the user information security and improve the real-time of vehicle information interaction, this paper proposes an anonymous authentication scheme based on edge computing. In this scheme, the concept of edge computing… More
  •   Views:673       Downloads:478        Download PDF
  • COVID19: Forecasting Air Quality Index and Particulate Matter (PM2.5)
  • Abstract Urbanization affects the quality of the air, which has drastically degraded in the past decades. Air quality level is determined by measures of several air pollutant concentrations. To create awareness among people, an automation system that forecasts the quality is needed. The COVID-19 pandemic and the restrictions it has imposed on anthropogenic activities have resulted in a drop in air pollution in various cities in India. The overall air quality index (AQI) at any particular time is given as the maximum band for any pollutant. PM2.5 is a fine particulate matter of a size less than 2.5 micrometers, the inhalation… More
  •   Views:1437       Downloads:1413        Download PDF
  • Multiclass Stomach Diseases Classification Using Deep Learning Features Optimization
  • Abstract In the area of medical image processing, stomach cancer is one of the most important cancers which need to be diagnose at the early stage. In this paper, an optimized deep learning method is presented for multiple stomach disease classification. The proposed method work in few important steps—preprocessing using the fusion of filtering images along with Ant Colony Optimization (ACO), deep transfer learning-based features extraction, optimization of deep extracted features using nature-inspired algorithms, and finally fusion of optimal vectors and classification using Multi-Layered Perceptron Neural Network (MLNN). In the feature extraction step, pre-trained Inception V3 is utilized and retrained on… More
  •   Views:786       Downloads:835        Download PDF
  • On Network Designs with Coding Error Detection and Correction Application
  • Abstract The detection of error and its correction is an important area of mathematics that is vastly constructed in all communication systems. Furthermore, combinatorial design theory has several applications like detecting or correcting errors in communication systems. Network (graph) designs (GDs) are introduced as a generalization of the symmetric balanced incomplete block designs (BIBDs) that are utilized directly in the above mentioned application. The networks (graphs) have been represented by vectors whose entries are the labels of the vertices related to the lengths of edges linked to it. Here, a general method is proposed and applied to construct new networks designs.… More
  •   Views:675       Downloads:506        Download PDF
  • An Energy-Efficient Mobile-Sink Path-Finding Strategy for UAV WSNs
  • Abstract Data collection using a mobile sink in a Wireless Sensor Network (WSN) has received much attention in recent years owing to its potential to reduce the energy consumption of sensor nodes and thus enhancing the lifetime of the WSN. However, a critical issue of this approach is the latency of data to reach the base station. Although many data collection algorithms have been introduced in the literature to reduce delays in data delivery, their performances are affected by the flight trajectory taken by the mobile sink, which might not be optimized yet. This paper proposes a new path-finding strategy, called… More
  •   Views:532       Downloads:379        Download PDF
  • Intelligent Real-Time IoT Traffic Steering in 5G Edge Networks
  • Abstract In the Next Generation Radio Networks (NGRN), there will be extreme massive connectivity with the Heterogeneous Internet of Things (HetIoT) devices. The millimeter-Wave (mmWave) communications will become a potential core technology to increase the capacity of Radio Networks (RN) and enable Multiple-Input and Multiple-Output (MIMO) of Radio Remote Head (RRH) technology. However, the challenging key issues in unfair radio resource handling remain unsolved when massive requests are occurring concurrently. The imbalance of resource utilization is one of the main issues occurs when there is overloaded connectivity to the closest RRH receiving exceeding requests. To handle this issue effectively, Machine Learning… More
  •   Views:885       Downloads:578        Download PDF
  • Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data
  • Abstract This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter (called tweets). A dataset of the exchange rates between the United States Dollar (USD) and the Pakistani Rupee (PKR) was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related words. The dataset was collected in raw form, and was subjected to natural language processing by way of data preprocessing. Response variable labeling was then applied to the standardized dataset, where the response variables were… More
  •   Views:1860       Downloads:881        Download PDF
  • Optimal and Memristor-Based Control of A Nonlinear Fractional Tumor-Immune Model
  • Abstract In this article, the reduced differential transform method is introduced to solve the nonlinear fractional model of Tumor-Immune. The fractional derivatives are described in the Caputo sense. The solutions derived using this method are easy and very accurate. The model is given by its signal flow diagram. Moreover, a simulation of the system by the Simulink of MATLAB is given. The disease-free equilibrium and stability of the equilibrium point are calculated. Formulation of a fractional optimal control for the cancer model is calculated. In addition, to control the system, we propose a novel modification of its model. This modification is… More
  •   Views:614       Downloads:626        Download PDF
  • A Novel Design of Octal-Valued Logic Full Adder Using Light Color State Model
  • Abstract Due to the demand of high computational speed for processing big data that requires complex data manipulations in a timely manner, the need for extending classical logic to construct new multi-valued optical models becomes a challenging and promising research area. This paper establishes a novel octal-valued logic design model with new optical gates construction based on the hypothesis of Light Color State Model to provide an efficient solution to the limitations of computational processing inherent in the electronics computing. We provide new mathematical definitions for both of the binary OR function and the PLUS operation in multi valued logic that… More
  •   Views:668       Downloads:614        Download PDF
  • Robust Cluster-Based Routing Protocol for IoT-Assisted Smart Devices in WSN
  • Abstract The Internet of Things (IoT) is gaining attention because of its broad applicability, especially by integrating smart devices for massive communication during sensing tasks. IoT-assisted Wireless Sensor Networks (WSN) are suitable for various applications like industrial monitoring, agriculture, and transportation. In this regard, routing is challenging to find an efficient path using smart devices for transmitting the packets towards big data repositories while ensuring efficient energy utilization. This paper presents the Robust Cluster Based Routing Protocol (RCBRP) to identify the routing paths where less energy is consumed to enhances the network lifespan. The scheme is presented in six phases to… More
  •   Views:754       Downloads:729        Download PDF
  • A Novel Green IoT-Based Pay-As-You-Go Smart Parking System
  • Abstract The better management of resources and the potential improvement in traffic congestion via reducing the orbiting time for parking spaces is crucial in a smart city, particularly those with an uneven correlation between the increase in vehicles and infrastructure. This paper proposes and analyses a novel green IoT-based Pay-As-You-Go (PAYG) smart parking system by utilizing unused garage parking spaces. The article also presents an intelligent system that offers the most favorable prices to its users by matching private garages’ pricing portfolio with a garage’s current demand. Malta, the world’s fourth-most densely populated country, is considered as a case of a… More
  •   Views:856       Downloads:953        Download PDF
  • Social Distancing and Isolation Management Using Machine-to-Machine Technologies to Prevent Pandemics
  • Abstract Social distancing and self-isolation management are crucial preventive measures that can save millions of lives during challenging pandemics of diseases such as the Spanish flu, swine flu, and coronavirus disease 2019 (COVID-19). This study describes the comprehensive and effective implementation of the Industrial Internet of Things and machine-to-machine technologies for social distancing and smart self-isolation management. These technologies can help prevent outbreaks of any disease that can disperse widely and develop into a pandemic. Initially, a smart wristband is proposed that incorporates Bluetooth beacon technology to facilitate the tracing and tracking of Bluetooth Low Energy beacon packets for smart contact… More
  •   Views:972       Downloads:490        Download PDF
  • LBC-IoT: Lightweight Block Cipher for IoT Constraint Devices
  • Abstract With the new era of the Internet of Things (IoT) technology, many devices with limited resources are utilized. Those devices are susceptible to a significant number of new malware and other risks emerging rapidly. One of the most appropriate methods for securing those IoT applications is cryptographic algorithms, as cryptography masks information by eliminating the risk of collecting any meaningful information patterns. This ensures that all data communications are private, accurate, authenticated, authorized, or non-repudiated. Since conventional cryptographic algorithms have been developed specifically for devices with limited resources; however, it turns out that such algorithms are not ideal for IoT… More
  •   Views:856       Downloads:809        Download PDF
  • CNN Ensemble Approach to Detect COVID-19 from Computed Tomography Chest Images
  • Abstract In January 2020, the World Health Organization declared a global health emergency concerning the spread of a new coronavirus disease, which was later named COVID-19. Early and fast diagnosis and isolation of COVID-19 patients have proven to be instrumental in limiting the spread of the disease. Computed tomography (CT) is a promising imaging method for fast diagnosis of COVID-19. In this study, we develop a unique preprocessing step to resize CT chest images to a fixed size (256 × 256 pixels) that preserves the aspect ratio and reduces image loss. Then, we present a deep learning (DL) method to classify… More
  •   Views:785       Downloads:708        Download PDF
  • The Hyperbolic Two Temperature Semiconducting Thermoelastic Waves by Laser Pulses
  • Abstract A novel model of a hyperbolic two-temperature theory is investigated to study the propagation the thermoelastic waves on semiconductor materials. The governing equations are studied during the photo-excitation processes in the context of the photothermal theory. The outer surface of o semiconductor medium is illuminated by a laser pulse. The generalized photo-thermoelasticity theory in two dimensions (2D) deformation is used in many models (Lord–Shulman (LS), Green–Lindsay (GL) and the classical dynamical coupled theory (CD)). The combinations processes between the hyperbolic two-temperature theory and photo-thermoelasticity theory under the effect of laser pulses are obtained analytically. The harmonic wave technique is used… More
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  • Integrity Assessment of Medical Devices for Improving Hospital Services
  • Abstract The present study examines the various techniques being used to maintain the integrity of the medical devices, and develops a quantitative framework to list these in the sequence of priority. To achieve the intended objective, the study employs the combined procedure of Fuzzy Analytic Network Process (ANP) and Fuzzy Technical for Order Preference by Similarities to Ideal Solution (TOPSIS). We selected fuzzy based decision making techniques for assessing the integrity of medical devices. The suggested methodology was then used for classifying the suitable techniques used to evaluate the integrity of medical devices. Different techniques or the procedures of integrity assessment… More
  •   Views:526       Downloads:424        Download PDF
  • Entropy-Based Watermarking Approach for Sensitive Tamper Detection of Arabic Text
  • Abstract The digital text media is the most common media transferred via the internet for various purposes and is very sensitive to transfer online with the possibility to be tampered illegally by the tampering attacks. Therefore, improving the security and authenticity of the text when it is transferred via the internet has become one of the most difficult challenges that researchers face today. Arabic text is more sensitive than other languages due to Harakat’s existence in Arabic diacritics such as Kasra, and Damma in which making basic changes such as modifying diacritic arrangements can lead to change the text meaning. In… More
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  • Service-Aware Access Control Procedure for Blockchain Assisted Real-Time Applications
  • Abstract The design of distributed ledger, Asymmetric Key Algorithm (AKA) blockchain systems, is prominent in administering security and access control in various real-time services and applications. The assimilation of blockchain systems leverages the reliable access and secure service provisioning of the services. However, the distributed ledger technology’s access control and chained decisions are defaced by pervasive and service unawareness. It results in degrading security through unattended access control for limited-service users. In this article, a service-aware access control procedure (SACP) is introduced to address the afore-mentioned issue. The proposed SACP defines attended access control for all the service session by identifying… More
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  • Implementation of a Subjective Visual Vertical and Horizontal Testing System Using Virtual Reality
  • Abstract Subjective visual vertical (SVV) and subjective visual horizontal (SVH) tests can be used to evaluate the perception of verticality and horizontality, respectively, and can aid the diagnosis of otolith dysfunction in clinical practice. In this study, SVV and SVH screen version tests are implemented using virtual reality (VR) equipment; the proposed test method promotes a more immersive feeling for the subject while using a simple equipment configuration and possessing excellent mobility. To verify the performance of the proposed VR-based SVV and SVH tests, a reliable comparison was made between the traditional screen-based SVV and SVH tests and the proposed method,… More
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  • Reconstructing the Time-Dependent Thermal Coefficient in 2D Free Boundary Problems
  • Abstract The inverse problem of reconstructing the time-dependent thermal conductivity and free boundary coefficients along with the temperature in a two-dimensional parabolic equation with initial and boundary conditions and additional measurements is, for the first time, numerically investigated. This inverse problem appears extensively in the modelling of various phenomena in engineering and physics. For instance, steel annealing, vacuum-arc welding, fusion welding, continuous casting, metallurgy, aircraft, oil and gas production during drilling and operation of wells. From literature we already know that this inverse problem has a unique solution. However, the problem is still ill-posed by being unstable to noise in the… More
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  • Text Analysis-Based Watermarking Approach for Tampering Detection of English Text
  • Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and the reliability of digital content have become a major research issue. The main challenges faced by researchers are authentication, integrity verification, and tampering detection of the digital contents. In this paper, text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text contents. The proposed approach embeds and detects the watermark logically without altering the original English text document. Based on hidden Markov model (HMM), the fourth level order of the word mechanism is used to analyze… More
  •   Views:470       Downloads:374        Download PDF
  • State-Based Offloading Model for Improving Response Rate of IoT Services
  • Abstract The Internet of Things (IoT) is a heterogeneous information sharing and access platform that provides services in a pervasive manner. Task and computation offloading in the IoT helps to improve the response rate and the availability of resources. Task offloading in a service-centric IoT environment mitigates the complexity in response delivery and request processing. In this paper, the state-based task offloading method (STOM) is introduced with a view to maximize the service response rate and reduce the response time of the varying request densities. The proposed method is designed using the Markov decision-making model to improve the rate of requests… More
  •   Views:634       Downloads:391        Download PDF
  • Analyzing COVID-2019 Impact on Mental Health Through Social Media Forum
  • Abstract This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic. COVID-19 brings a lot of challenges to government globally. Among the different strategies the most extensively adopted ones were lockdown, social distancing, and isolation among others. Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus. Panic among people due to COVID-19 spread faster than the disease itself. The misinformation and excessive usage of social media in this pandemic era have adversely… More
  •   Views:1205       Downloads:560        Download PDF
  • Intelligent Approach for Traffic Orchestration in SDVN Based on CMPR
  • Abstract The vehicle ad hoc network that has emerged in recent years was originally a branch of the mobile ad hoc network. With the drafting and gradual establishment of standards such as IEEE802.11p and IEEE1609, the vehicle ad hoc network has gradually become independent of the mobile ad hoc network. The Internet of Vehicles (Vehicular Ad Hoc Network, VANET) is a vehicle-mounted network that comprises vehicles and roadside basic units. This multi-hop hybrid wireless network is based on a vehicle-mounted self-organizing network. As compared to other wireless networks, such as mobile ad hoc networks, wireless sensor networks, wireless mesh networks, etc.,… More
  •   Views:520       Downloads:348        Download PDF
  • Multi-Span and Multiple Relevant Time Series Prediction Based on Neighborhood Rough Set
  • Abstract Rough set theory has been widely researched for time series prediction problems such as rainfall runoff. Accurate forecasting of rainfall runoff is a long standing but still mostly significant problem for water resource planning and management, reservoir and river regulation. Most research is focused on constructing the better model for improving prediction accuracy. In this paper, a rainfall runoff forecast model based on the variable-precision fuzzy neighborhood rough set (VPFNRS) is constructed to predict Watershed runoff value. Fuzzy neighborhood rough set define the fuzzy decision of a sample by using the concept of fuzzy neighborhood. The fuzzy neighborhood rough set… More
  •   Views:461       Downloads:370        Download PDF
  • Time Series Facebook Prophet Model and Python for COVID-19 Outbreak Prediction
  • Abstract COVID-19 comes from a large family of viruses identified in 1965; to date, seven groups have been recorded which have been found to affect humans. In the healthcare industry, there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict confirmed cases, recovered cases, and deaths. Many researchers and scientists in the field of machine learning are also involved in solving this dilemma, seeking to understand the patterns and characteristics of virus attacks, so scientists may make the right decisions and take specific actions. Furthermore, many models have been considered… More
  •   Views:2938       Downloads:1294        Download PDF
  • An Intelligent Cluster Optimization Algorithm for Smart Body Area Networks
  • Abstract Body Area Networks (BODYNETs) or Wireless Body Area Networks (WBAN), being an important type of ad-hoc network, plays a vital role in multimedia, safety, and traffic management applications. In BODYNETs, rapid topology changes occur due to high node mobility, which affects the scalability of the network. Node clustering is one mechanism among many others, which is used to overcome this issue in BODYNETs. There are many clustering algorithms used in this domain to overcome this issue. However, these algorithms generate a large number of Cluster Heads (CHs), which results in scarce resource utilization and degraded performance. In this research, an… More
  •   Views:813       Downloads:605        Download PDF
  • Novel Adaptive Binarization Method for Degraded Document Images
  • Abstract Achieving a good recognition rate for degraded document images is difficult as degraded document images suffer from low contrast, bleed-through, and nonuniform illumination effects. Unlike the existing baseline thresholding techniques that use fixed thresholds and windows, the proposed method introduces a concept for obtaining dynamic windows according to the image content to achieve better binarization. To enhance a low-contrast image, we proposed a new mean histogram stretching method for suppressing noisy pixels in the background and, simultaneously, increasing pixel contrast at edges or near edges, which results in an enhanced image. For the enhanced image, we propose a new method… More
  •   Views:662       Downloads:479        Download PDF
  • A User-friendly Model for Ransomware Analysis Using Sandboxing
  • Abstract Ransomware is a type of malicious software that blocks access to a computer by encrypting user’s files until a ransom is paid to the attacker. There have been several reported high-profile ransomware attacks including WannaCry, Petya, and Bad Rabbit resulting in losses of over a billion dollars to various individuals and businesses in the world. The analysis of ransomware is often carried out via sandbox environments; however, the initial setup and configuration of such environments is a challenging task. Also, it is difficult for an ordinary computer user to correctly interpret the complex results presented in the reports generated by… More
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  • A Deep Learning-Based Recognition Approach for the Conversion of Multilingual Braille Images
  • Abstract Braille-assistive technologies have helped blind people to write, read, learn, and communicate with sighted individuals for many years. These technologies enable blind people to engage with society and help break down communication barriers in their lives. The Optical Braille Recognition (OBR) system is one example of these technologies. It plays an important role in facilitating communication between sighted and blind people and assists sighted individuals in the reading and understanding of the documents of Braille cells. However, a clear gap exists in current OBR systems regarding asymmetric multilingual conversion of Braille documents. Few systems allow sighted people to read and… More
  •   Views:548       Downloads:710        Download PDF
  • Payload Capacity Scheme for Quran Text Watermarking Based on Vowels with Kashida
  • Abstract The most sensitive Arabic text available online is the digital Holy Quran. This sacred Islamic religious book is recited by all Muslims worldwide including non-Arabs as part of their worship needs. Thus, it should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of Arabic letters like the vowels (), Kashida (extended letters), and other symbols in the Holy Quran must be secured from alterations. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR) and Embedding Ratio (ER).… More
  •   Views:717       Downloads:612        Download PDF
  • A Reliable and Scalable Internet of Military Things Architecture
  • Abstract Recently, Internet of Things (IoT) technology has provided logistics services to many disciplines such as agriculture, industry, and medicine. Thus, it has become one of the most important scientific research fields. Applying IoT to military domain has many challenges such as fault tolerance and QoS. In this paper, IoT technology is applied on the military field to create an Internet of Military Things (IoMT) system. Here, the architecture of the aforementioned IoMT system is proposed. This architecture consists of four main layers: Communication, information, application, and decision support. These layers provided a fault tolerant coverage communication system for IoMT things.… More
  •   Views:864       Downloads:686        Download PDF
  • Joint Frequency and DOA Estimation with Automatic Pairing Using the Rayleigh–Ritz Theorem
  • Abstract This paper presents a novel scheme for joint frequency and direction of arrival (DOA) estimation, that pairs frequencies and DOAs automatically without additional computations. First, when the property of the Kronecker product is used in the received array signal of the multiple-delay output model, the frequency-angle steering vector can be reconstructed as the product of the frequency steering vector and the angle steering vector. The frequency of the incoming signal is then obtained by searching for the minimal eigenvalue among the smallest eigenvalues that depend on the frequency parameters but are irrelevant to the DOAs. Subsequently, the DOA related to… More
  •   Views:478       Downloads:387        Download PDF
  • Improving Language Translation Using the Hidden Markov Model
  • Abstract Translation software has become an important tool for communication between different languages. People’s requirements for translation are higher and higher, mainly reflected in people’s desire for barrier free cultural exchange. With a large corpus, the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units. Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation, ignoring context. To support the ongoing improvement of translation methods built upon deep learning, we propose a translation algorithm based on the Hidden Markov… More
  •   Views:743       Downloads:533        Download PDF
  • Vehicle Re-Identification Model Based on Optimized DenseNet121 with Joint Loss
  • Abstract With the increasing application of surveillance cameras, vehicle re-identification (Re-ID) has attracted more attention in the field of public security. Vehicle Re-ID meets challenge attributable to the large intra-class differences caused by different views of vehicles in the traveling process and obvious inter-class similarities caused by similar appearances. Plentiful existing methods focus on local attributes by marking local locations. However, these methods require additional annotations, resulting in complex algorithms and insufferable computation time. To cope with these challenges, this paper proposes a vehicle Re-ID model based on optimized DenseNet121 with joint loss. This model applies the SE block to automatically… More
  •   Views:541       Downloads:505        Download PDF
  • Quality of Service Aware Cluster Routing in Vehicular Ad Hoc Networks
  • Abstract In vehicular ad hoc networks (VANETs), the topology information (TI) is updated frequently due to vehicle mobility. These frequent changes in topology increase the topology maintenance overhead. To reduce the control message overhead, cluster-based routing schemes are proposed. In cluster-based routing schemes, the nodes are divided into different virtual groups, and each group (logical node) is considered a cluster. The topology changes are accommodated within each cluster, and broadcasting TI to the whole VANET is not required. The cluster head (CH) is responsible for managing the communication of a node with other nodes outside the cluster. However, transmitting real-time data… More
  •   Views:749       Downloads:681        Download PDF
  • Brain Tumor Classification Based on Fine-Tuned Models and the Ensemble Method
  • Abstract Brain tumors are life-threatening for adults and children. However, accurate and timely detection can save lives. This study focuses on three different types of brain tumors: Glioma, meningioma, and pituitary tumors. Many studies describe the analysis and classification of brain tumors, but few have looked at the problem of feature engineering. Methods are needed to overcome the drawbacks of manual diagnosis and conventional feature-engineering techniques. An automatic diagnostic system is thus necessary to extract features and classify brain tumors accurately. While progress continues to be made, the automatic diagnoses of brain tumors still face challenges of low accuracy and high… More
  •   Views:507       Downloads:636        Download PDF
  • Windowing Techniques, the Welch Method for Improvement of Power Spectrum Estimation
  • Abstract This paper revisits the characteristics of windowing techniques with various window functions involved, and successively investigates spectral leakage mitigation utilizing the Welch method. The discrete Fourier transform (DFT) is ubiquitous in digital signal processing (DSP) for the spectrum analysis and can be efficiently realized by the fast Fourier transform (FFT). The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed. Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out. Therefore,… More
  •   Views:820       Downloads:1790        Download PDF
  • Secure Localization Based Authentication (SLA) Strategy for Data Integrity in WNS
  • Abstract Wireless Sensor Networks (WSN) has been extensively utilized as a communication model in Internet of Things (IoT). As well, to offer service, numerous IoT based applications need effective transmission over unstable locations. To ensure reliability, prevailing investigations exploit multiple candidate forwarders over geographic opportunistic routing in WSNs. Moreover, these models are affected by crucial denial of service (DoS) attacks, where huge amount of invalid data are delivered intentionally to the receivers to disturb the functionality of WSNs. Here, secure localization based authentication (SLA) is presented to fight against DoS attack, and to fulfil the need of reliability and authentication. By… More
  •   Views:594       Downloads:419        Download PDF
  • Enhanced KOCED Routing Protocol with K-means Algorithm
  • Abstract Replacing or recharging batteries in the sensor nodes of a wireless sensor network (WSN) is a significant challenge. Therefore, efficient power utilization by sensors is a critical requirement, and it is closely related to the life span of the network. Once a sensor node consumes all its energy, it will no longer function properly. Therefore, various protocols have been proposed to minimize the energy consumption of sensors and thus prolong the network operation. Recently, clustering algorithms combined with artificial intelligence have been proposed for this purpose. In particular, various protocols employ the K-means clustering algorithm, which is a machine learning… More
  •   Views:607       Downloads:534        Download PDF
  • 1D-CNN: Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features
  • Abstract Emotion recognition from speech data is an active and emerging area of research that plays an important role in numerous applications, such as robotics, virtual reality, behavior assessments, and emergency call centers. Recently, researchers have developed many techniques in this field in order to ensure an improvement in the accuracy by utilizing several deep learning approaches, but the recognition rate is still not convincing. Our main aim is to develop a new technique that increases the recognition rate with reasonable cost computations. In this paper, we suggested a new technique, which is a one-dimensional dilated convolutional neural network (1D-DCNN) for… More
  •   Views:1253       Downloads:657        Download PDF
  • Mechanical Properties of a Wood Flour-PET Composite Through Computational Homogenisation
  • Abstract This work proposes to study the effective elastic properties (EEP) of a wood-plastic composite (WPC) made from polyethylene terephthalate (PET) and Chilean Radiate pine’s wood flour, using finite element simulations of a representative volume element (RVE) with periodic boundary conditions. Simulations are validated through a static 3-point bending test, with specimens obtained by extruding and injection. The effect of different weight fractions, space orientations and sizes of particles are here examined. Numerical predictions are empirically confirmed in the sense that composites with more wood flour content and bigger size, have higher elastic modulus. However, these results are very sensitive to… More
  •   Views:603       Downloads:568        Download PDF
  • Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm
  • Abstract This work presents a memetic Shuffled Frog Leaping Algorithm (SFLA) based tuning approach of an Integral Sliding Mode Controller (ISMC) for a quadrotor type of Unmanned Aerial Vehicles (UAV). Based on the Newton–Euler formalism, a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes. Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law, which are usually selected by repetitive and time-consuming trials-errors based procedures, a constrained optimization problem is formulated for the systematically tuning of these unknown variables. Under time-domain operating… More
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