Home / Journals / CMC / Vol.72, No.2, 2022
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  • Open AccessOpen Access

    ARTICLE

    EACR-LEACH: Energy-Aware Cluster-based Routing Protocol for WSN Based IoT

    Sankar Sennan1, Kirubasri1, Youseef Alotaibi2, Digvijay Pandey3,*, Saleh Alghamdi4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2159-2174, 2022, DOI:10.32604/cmc.2022.025773
    Abstract Internet of Things (IoT) is a recent paradigm to improve human lifestyle. Nowadays, number devices are connected to the Internet drastically. Thus, the people can control and monitor the physical things in real-time without delay. The IoT plays a vital role in all kind of fields in our world such as agriculture, livestock, transport, and healthcare, grid system, connected home, elderly people carrying system, cypher physical system, retail, and intelligent systems. In IoT energy conservation is a challenging task, as the devices are made up of low-cost and low-power sensing devices and local processing. IoT networks have significant challenges in… More >

  • Open AccessOpen Access

    ARTICLE

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm

    Mustafa Musa Jaber1,2,*, Salman Yussof1, Amer S. Elameer3, Leong Yeng Weng1, Sura Khalil Abd2,6, Anand Nayyar4,5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2175-2190, 2022, DOI:10.32604/cmc.2022.023387
    Abstract Artificial intelligence plays an essential role in the medical and health industries. Deep convolution networks offer valuable services and help create automated systems to perform medical image analysis. However, convolution networks examine medical images effectively; such systems require high computational complexity when recognizing the same disease-affected region. Therefore, an optimized deep convolution network is utilized for analyzing disease-affected regions in this work. Different disease-related medical images are selected and examined pixel by pixel; this analysis uses the gray wolf optimized deep learning network. This method identifies affected pixels by the gray wolf hunting process. The convolution network uses an automatic… More >

  • Open AccessOpen Access

    ARTICLE

    Fuzzy MCDM Model for Selection of Infectious Waste Management Contractors

    Nguyen Van Thanh1, Nguyen Hoang Hai1,*, Nguyen Thi Kim Lan2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2191-2202, 2022, DOI:10.32604/cmc.2022.026357
    Abstract Healthcare supply chains are under pressure to drive down costs because of digital business, shifting customer needs and new competition. Medical waste generated from medical facilities includes medical activities and daily-life activities of patients and their family members. According to statistics of the Department of Health Environmental Management, Vietnam currently has more than 13,500 medical facilities, including hospitals from central to provincial and district levels and private hospitals and medical facilities. Preventive medicine generates about 590 tons of medical waste/day and is estimated to be about 800 tons/day. Medical waste includes ordinary medical waste and hazardous medical waste; in which… More >

  • Open AccessOpen Access

    ARTICLE

    An Efficient Scheme for Data Pattern Matching in IoT Networks

    Ashraf Ali*, Omar A. Saraereh
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2203-2219, 2022, DOI:10.32604/cmc.2022.025994
    Abstract The Internet has become an unavoidable trend of all things due to the rapid growth of networking technology, smart home technology encompasses a variety of sectors, including intelligent transportation, allowing users to communicate with anybody or any device at any time and from anywhere. However, most things are different now. Background: Structured data is a form of separated storage that slows down the rate at which everything is connected. Data pattern matching is commonly used in data connectivity and can help with the issues mentioned above. Aim: The present pattern matching system is ineffective due to the heterogeneity and rapid… More >

  • Open AccessOpen Access

    ARTICLE

    Feedline Separation for Independent Control of Simultaneously Different Tx/Rx Radiation Patterns

    Akarachai Inthanil, Monthippa Uthansakul*, Peerapong Uthansakul
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2221-2241, 2022, DOI:10.32604/cmc.2022.024390
    Abstract The shortcoming of Wi-Fi networks is that one user can access the router at a time. This drawback limits the system throughput and delay. This paper proposes a concept of Simultaneously Different Tx/Rx (SDTR) radiation patterns with only one antenna set at the router. Furthermore, these two patterns have to be simultaneously operated at the same time so that the system delay can be eased. An omni-directional pattern is employed at router for receiving mode so that the router can sense carrier signal from all directions. At the same time, the router launches a directional beam pointed to another user.… More >

  • Open AccessOpen Access

    ARTICLE

    Deep-piRNA: Bi-Layered Prediction Model for PIWI-Interacting RNA Using Discriminative Features

    Salman Khan1, Mukhtaj Khan1,2, Nadeem Iqbal1, Mohd Amiruddin Abd Rahman3,*, Muhammad Khalis Abdul Karim3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2243-2258, 2022, DOI:10.32604/cmc.2022.022901
    Abstract Piwi-interacting Ribonucleic acids (piRNAs) molecule is a well-known subclass of small non-coding RNA molecules that are mainly responsible for maintaining genome integrity, regulating gene expression, and germline stem cell maintenance by suppressing transposon elements. The piRNAs molecule can be used for the diagnosis of multiple tumor types and drug development. Due to the vital roles of the piRNA in computational biology, the identification of piRNAs has become an important area of research in computational biology. This paper proposes a two-layer predictor to improve the prediction of piRNAs and their function using deep learning methods. The proposed model applies various feature… More >

  • Open AccessOpen Access

    ARTICLE

    Thermomechanical Behavior of Brake Drums Under Extreme Braking Conditions

    T. Khatir1,2, M. Bouchetara2, K. Derrar2, M. Djafri3, S. Khatir4, M. Abdel Wahab5,6,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2259-2273, 2022, DOI:10.32604/cmc.2022.020879
    Abstract Braking efficiency is characterized by reduced braking time and distance, and therefore passenger safety depends on the design of the braking system. During the braking of a vehicle, the braking system must dissipate the kinetic energy by transforming it into heat energy. A too high temperature can lead to an almost total loss of braking efficiency. An excessive rise in brake temperature can also cause surface cracks extending to the outside edge of the drum friction surface. Heat transfer and temperature gradient, not to forget the vehicle's travel environment (high speed, heavy load, and steeply sloping road conditions), must thus… More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Forensic Investigation Using Optimal Stacked Autoencoder for Critical Industrial Infrastructures

    Abdullah S. AL-Malaise AL-Ghamdi1, Mahmoud Ragab2,3,4,*, F. J. Alsolami5, Hani Choudhry3,6, Ibrahim Rizqallah Alzahrani7
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2275-2289, 2022, DOI:10.32604/cmc.2022.026226
    Abstract Industrial Control Systems (ICS) can be employed on the industrial processes in order to reduce the manual labor and handle the complicated industrial system processes as well as communicate effectively. Internet of Things (IoT) integrates numerous sets of sensors and devices via a data network enabling independent processes. The incorporation of the IoT in the industrial sector leads to the design of Industrial Internet of Things (IIoT), which find use in water distribution system, power plants, etc. Since the IIoT is susceptible to different kinds of attacks due to the utilization of Internet connection, an effective forensic investigation process becomes… More >

  • Open AccessOpen Access

    ARTICLE

    Supplier Selection Fuzzy Model in Supply Chain Management: Vietnamese Cafe Industry Case

    Chia-Nan Wang1, Hoang Tuyet Nhi Thai1,*, Nguyen Van Thanh2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2291-2304, 2022, DOI:10.32604/cmc.2022.025477
    Abstract Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization. Choosing the right supplier can help businesses increase productivity, competitiveness in the market, and profits without having to lower the quality of the products. However, choosing a supplier is not a simple matter, it requires businesses to consider many aspects about their suppliers. Therefore, the goal of this study is to propose an integrated model consisting of two models: Fuzzy Analytics Network Process (Fuzzy-ANP) model and Weighted Aggregated Sum Product… More >

  • Open AccessOpen Access

    ARTICLE

    Robust Prediction of the Bandwidth of Metamaterial Antenna Using Deep Learning

    Abdelaziz A. Abdelhamid1,3,*, Sultan R. Alotaibi2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2305-2321, 2022, DOI:10.32604/cmc.2022.025739
    Abstract The design of microstrip antennas is a complex and time-consuming process, especially the step of searching for the best design parameters. Meanwhile, the performance of microstrip antennas can be improved using metamaterial, which results in a new class of antennas called metamaterial antenna. Several parameters affect the radiation loss and quality factor of this class of antennas, such as the antenna size. Recently, the optimal values of the design parameters of metamaterial antennas can be predicted using machine learning, which presents a better alternative to simulation tools and trial-and-error processes. However, the prediction accuracy depends heavily on the quality of… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

    Sami Ullah1, Muhammad Ramzan Talib1,*, Toqir A. Rana2,3, Muhammad Kashif Hanif1, Muhammad Awais4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2323-2339, 2022, DOI:10.32604/cmc.2022.025543
    Abstract In the current era of the internet, people use online media for conversation, discussion, chatting, and other similar purposes. Analysis of such material where more than one person is involved has a spate challenge as compared to other text analysis tasks. There are several approaches to identify users’ emotions from the conversational text for the English language, however regional or low resource languages have been neglected. The Urdu language is one of them and despite being used by millions of users across the globe, with the best of our knowledge there exists no work on dialogue analysis in the Urdu… More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Dynamic Inversion Controller Design for Ball and Beam System

    Ibrahim M. Mehedi1,2,*, Abdulah Jeza Aljohani1,2, Md Mottahir Alam1, Mohamed Mahmoud3, Mohammed J. Abdulaal1, Muhammad Bilal1,2, Waleed Alasmary4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2341-2355, 2022, DOI:10.32604/cmc.2022.022993
    Abstract The Ball and beam system (BBS) is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable properties. Designing an effective ball and beam system controller is a real challenge for researchers and engineers. In this paper, the control design technique is investigated by using Intelligent Dynamic Inversion (IDI) method for this nonlinear and unstable system. The proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in it. The Moore-Penrose Generalized Inverse (MPGI) is used to invert the prescribed constraint dynamics to realize the baseline control law. A sliding… More >

  • Open AccessOpen Access

    ARTICLE

    Bio-Inspired Computational Methods for the Polio Virus Epidemic Model

    Fatimah Abdulrahman Alrawajeh1, F. M. Allehiany2, Ali Raza3,*, Shaimaa A. M. Abdelmohsen4, Tahir Nawaz Cheema5, Muhammad Rafiq6, Muhammad Mohsin7
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2357-2374, 2022, DOI:10.32604/cmc.2022.024604
    Abstract In 2021, most of the developing countries are fighting polio, and parents are concerned with the disabling of their children. Poliovirus transmits from person to person, which can infect the spinal cord, and paralyzes the parts of the body within a matter of hours. According to the World Health Organization (WHO), 18 million currently healthy people could have been paralyzed by the virus during 1988–2020. Almost all countries but Pakistan, Afghanistan, and a few more have been declared polio-free. The mathematical modeling of poliovirus is studied in the population by categorizing it as susceptible individuals (S), exposed individuals (E), infected… More >

  • Open AccessOpen Access

    ARTICLE

    A Modified-Simplified MPPT Technique for Three-Phase Single-State Grid-Connected PV Systems

    Anuchit Aurairat, Boonyang Plangklang*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2375-2395, 2022, DOI:10.32604/cmc.2022.025122
    Abstract Nowadays, the single state inverter for the grid-connected photovoltaic (PV) systems is becoming more and more popular as they can reduce circuit complexity resulting in less power losses of the inverter. This paper focuses on the use of model predictive control (MPC) to control a 3-phase and 2-level single-state grid-connected inverter in order to regulate the PV maximum power point (MPP). The algorithm of MPC scheme was done to measure the simultaneous current signal including predicting the next sampling current flow. The reference current (Id*) was used to control the distribution of electrical power from the solar cell to the… More >

  • Open AccessOpen Access

    ARTICLE

    Linearly Polarized Millimeter Wave Reflectarray with Mutual Coupling Optimization

    M. Inam1, M. H. Dahri2, M. R. Kamarudin3, A. Y. I. Ashyap3, M. H. Jamaluddin4, N. H. Sulaiman5, M. A. Khan6, Z. A. Shamsan7,*, K. Almuhanna7, F. Alorifi7
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2397-2410, 2022, DOI:10.32604/cmc.2022.025650
    Abstract This work provides the design and analysis of a single layer, linearly polarized millimeter wave reflectarray antenna with mutual coupling optimization. Detailed analysis was carried out at 26 GHz design frequency using the simulations of the reflectarray unit cells as well as the periodic reflectarray antenna. The simulated results were verified by the scattering parameter and far-field measurements of the unit cell and periodic arrays, respectively. A close agreement between the simulated and measured results was observed in all the cases. Apart from the unit cells and reflectarray, the waveguide and horn antenna were also fabricated to be used in the… More >

  • Open AccessOpen Access

    ARTICLE

    Machine Learning Based Psychotic Behaviors Prediction from Facebook Status Updates

    Mubashir Ali1, Anees Baqir2, Hafiz Husnain Raza Sherazi3,*, Asad Hussain4, Asma Hassan Alshehri5, Muhammad Ali Imran6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2411-2427, 2022, DOI:10.32604/cmc.2022.024704
    Abstract With the advent of technological advancements and the widespread Internet connectivity during the last couple of decades, social media platforms (such as Facebook, Twitter, and Instagram) have consumed a large proportion of time in our daily lives. People tend to stay alive on their social media with recent updates, as it has become the primary source of interaction within social circles. Although social media platforms offer several remarkable features but are simultaneously prone to various critical vulnerabilities. Recent studies have revealed a strong correlation between the usage of social media and associated mental health issues consequently leading to depression, anxiety,… More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

    Thavavel Vaiyapuri1, K. Priyadarshini2, A. Hemlathadhevi3, M. Dhamodaran4, Ashit Kumar Dutta5, Irina V. Pustokhina6,*, Denis A. Pustokhin7
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2429-2444, 2022, DOI:10.32604/cmc.2022.026204
    Abstract Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection (WSOA-FS) manner to… More >

  • Open AccessOpen Access

    ARTICLE

    Behavioral Intrusion Prediction Model on Bayesian Network over Healthcare Infrastructure

    Mohammad Hafiz Mohd Yusof1,*, Abdullah Mohd Zin2, Nurhizam Safie Mohd Satar2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2445-2466, 2022, DOI:10.32604/cmc.2022.023571
    Abstract Due to polymorphic nature of malware attack, a signature-based analysis is no longer sufficient to solve polymorphic and stealth nature of malware attacks. On the other hand, state-of-the-art methods like deep learning require labelled dataset as a target to train a supervised model. This is unlikely to be the case in production network as the dataset is unstructured and has no label. Hence an unsupervised learning is recommended. Behavioral study is one of the techniques to elicit traffic pattern. However, studies have shown that existing behavioral intrusion detection model had a few issues which had been parameterized into its common… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Sine Cosine and Stochastic Fractal Search for Hemoglobin Estimation

    Marwa M. Eid1,*, Fawaz Alassery2, Abdelhameed Ibrahim3, Bandar Abdullah Aloyaydi4, Hesham Arafat Ali1,3, Shady Y. El-Mashad5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2467-2482, 2022, DOI:10.32604/cmc.2022.025220
    Abstract The sample's hemoglobin and glucose levels can be determined by obtaining a blood sample from the human body using a needle and analyzing it. Hemoglobin (HGB) is a critical component of the human body because it transports oxygen from the lungs to the body's tissues and returns carbon dioxide from the tissues to the lungs. Calculating the HGB level is a critical step in any blood analysis job. The HGB levels often indicate whether a person is anemic or polycythemia vera. Constructing ensemble models by combining two or more base machine learning (ML) models can help create a more improved… More >

  • Open AccessOpen Access

    ARTICLE

    QoS Aware Multicast Routing Protocol for Video Transmission in Smart Cities

    Khaled Mohamad Almustafa1, Taiseer Abdalla Elfadil Eisa2, Amani Abdulrahman Albraikan3, Mesfer Al Duhayyim4,*, Manar Ahmed Hamza5, Abdelwahed Motwakel5, Ishfaq Yaseen5, Muhammad Imran Babar6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2483-2499, 2022, DOI:10.32604/cmc.2022.024688
    Abstract In recent years, Software Defined Networking (SDN) has become an important candidate for communication infrastructure in smart cities. It produces a drastic increase in the need for delivery of video services that are of high resolution, multiview, and large-scale in nature. However, this entity gets easily influenced by heterogeneous behaviour of the user's wireless link features that might reduce the quality of video stream for few or all clients. The development of SDN allows the emergence of new possibilities for complicated controlling of video conferences. Besides, multicast routing protocol with multiple constraints in terms of Quality of Service (QoS) is… More >

  • Open AccessOpen Access

    ARTICLE

    Sign Language to Sentence Formation: A Real Time Solution for Deaf People

    Muhammad Sanaullah1,*, Muhammad Kashif2, Babar Ahmad2, Tauqeer Safdar2, Mehdi Hassan3, Mohd Hilmi Hasan4, Amir Haider5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2501-2519, 2022, DOI:10.32604/cmc.2022.021990
    Abstract Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular… More >

  • Open AccessOpen Access

    ARTICLE

    Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors

    P. Arunachalam1, N. Janakiraman1, Junaid Rashid2, Jungeun Kim2,*, Sovan Samanta3, Usman Naseem4, Arun Kumar Sivaraman5, A. Balasundaram6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2521-2543, 2022, DOI:10.32604/cmc.2022.025339
    Abstract In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA + SVM, ICA + SVM,… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Deep Learning Modalities for Object Detection from Infrared Images

    Naglaa F. Soliman1,2, E. A. Alabdulkreem3, Abeer D. Algarni1,*, Ghada M. El Banby4, Fathi E. Abd El-Samie1,5, Ahmed Sedik6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2545-2563, 2022, DOI:10.32604/cmc.2022.020107
    Abstract For military warfare purposes, it is necessary to identify the type of a certain weapon through video stream tracking based on infrared (IR) video frames. Computer vision is a visual search trend that is used to identify objects in images or video frames. For military applications, drones take a main role in surveillance tasks, but they cannot be confident for long-time missions. So, there is a need for such a system, which provides a continuous surveillance task to support the drone mission. Such a system can be called a Hybrid Surveillance System (HSS). This system is based on a distributed… More >

  • Open AccessOpen Access

    ARTICLE

    Technologically Advanced Reusable 3D Face Shield for Health Workers Confronting COVID19

    Rajesh Kumar Kaushal1, Naveen Kumar1, Vinay Kukreja1, Fahd S. Alharithi2, Ahmed H. Almulihi2, Arturo Ortega Mansilla3,4, Shikha Rani5,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2565-2579, 2022, DOI:10.32604/cmc.2022.025049
    Abstract The probability of medical staff to get affected from COVID19 is much higher due to their working environment which is more exposed to infectious diseases. So, as a preventive measure the body temperature monitoring of medical staff at regular intervals is highly recommended. Infrared temperature sensing guns have proved its effectiveness and therefore such devices are used to monitor the body temperature. These devices are either used on hands or forehead. As a result, there are many issues in monitoring the temperature of frontline healthcare professionals. Firstly, these healthcare professionals keep wearing PPE (Personal Protective Equipment) kits during working hours… More >

  • Open AccessOpen Access

    ARTICLE

    Feature Selection with Optimal Stacked Sparse Autoencoder for Data Mining

    Manar Ahmed Hamza1,*, Siwar Ben Haj Hassine2, Ibrahim Abunadi3, Fahd N. Al-Wesabi2,4, Hadeel Alsolai5, Anwer Mustafa Hilal1, Ishfaq Yaseen1, Abdelwahed Motwakel1
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2581-2596, 2022, DOI:10.32604/cmc.2022.024764
    Abstract Data mining in the educational field can be used to optimize the teaching and learning performance among the students. The recently developed machine learning (ML) and deep learning (DL) approaches can be utilized to mine the data effectively. This study proposes an Improved Sailfish Optimizer-based Feature Selection with Optimal Stacked Sparse Autoencoder (ISOFS-OSSAE) for data mining and pattern recognition in the educational sector. The proposed ISOFS-OSSAE model aims to mine the educational data and derive decisions based on the feature selection and classification process. Moreover, the ISOFS-OSSAE model involves the design of the ISOFS technique to choose an optimal subset… More >

  • Open AccessOpen Access

    ARTICLE

    An Intelligent HealthCare Monitoring Framework for Daily Assistant Living

    Yazeed Yasin Ghadi1, Nida Khalid2, Suliman A. Alsuhibany3, Tamara al Shloul4, Ahmad Jalal2, Jeongmin Park5,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2597-2615, 2022, DOI:10.32604/cmc.2022.024422
    Abstract Human Activity Recognition (HAR) plays an important role in life care and health monitoring since it involves examining various activities of patients at homes, hospitals, or offices. Hence, the proposed system integrates Human-Human Interaction (HHI) and Human-Object Interaction (HOI) recognition to provide in-depth monitoring of the daily routine of patients. We propose a robust system comprising both RGB (red, green, blue) and depth information. In particular, humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency map. To track the movement of humans, we proposed… More >

  • Open AccessOpen Access

    ARTICLE

    A Robust Emergency Messages Routing Scheme for Urban VANETs

    Mumtaz Ali Shah1,2,*, Farrukh Zeeshan Khan1, Ghulam Abbas2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2617-2632, 2022, DOI:10.32604/cmc.2022.025981
    Abstract Vehicular ad-hoc networks (VANETs) play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities. Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages (EMs) depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach. Nevertheless, such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously. Due to the high number of vehicles, it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions. A cluster-based… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning with Image Classification Based Secure CPS for Healthcare Sector

    Ahmed S. Almasoud1, Abdelzahir Abdelmaboud2, Faisal S. Alsubaei3, Manar Ahmed Hamza4,*, Ishfaq Yaseen4, Mohammed Abaker5, Abdelwahed Motwakel4, Mohammed Rizwanullah4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2633-2648, 2022, DOI:10.32604/cmc.2022.024619
    Abstract Cyber-Physical System (CPS) involves the combination of physical processes with computation and communication systems. The recent advancements made in cloud computing, Wireless Sensor Network (WSN), healthcare sensors, etc. tend to develop CPS as a proficient model for healthcare applications especially, home patient care. Though several techniques have been proposed earlier related to CPS structures, only a handful of studies has focused on the design of CPS models for health care sector. So, the proposal for a dedicated CPS model for healthcare sector necessitates a significant interest to ensure data privacy. To overcome the challenges, the current research paper designs a… More >

  • Open AccessOpen Access

    ARTICLE

    A Deep Learning Hierarchical Ensemble for Remote Sensing Image Classification

    Seung-Yeon Hwang1, Jeong-Joon Kim2,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2649-2663, 2022, DOI:10.32604/cmc.2022.022593
    Abstract Artificial intelligence, which has recently emerged with the rapid development of information technology, is drawing attention as a tool for solving various problems demanded by society and industry. In particular, convolutional neural networks (CNNs), a type of deep learning technology, are highlighted in computer vision fields, such as image classification and recognition and object tracking. Training these CNN models requires a large amount of data, and a lack of data can lead to performance degradation problems due to overfitting. As CNN architecture development and optimization studies become active, ensemble techniques have emerged to perform image classification by combining features extracted… More >

  • Open AccessOpen Access

    ARTICLE

    Machine Learning with Dimensionality Reduction for DDoS Attack Detection

    Shaveta Gupta1, Dinesh Grover2, Ahmad Ali AlZubi3,*, Nimit Sachdeva4, Mirza Waqar Baig5, Jimmy Singla6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2665-2682, 2022, DOI:10.32604/cmc.2022.025048
    Abstract With the advancement of internet, there is also a rise in cybercrimes and digital attacks. DDoS (Distributed Denial of Service) attack is the most dominant weapon to breach the vulnerabilities of internet and pose a significant threat in the digital environment. These cyber-attacks are generated deliberately and consciously by the hacker to overwhelm the target with heavy traffic that genuine users are unable to use the target resources. As a result, targeted services are inaccessible by the legitimate user. To prevent these attacks, researchers are making use of advanced Machine Learning classifiers which can accurately detect the DDoS attacks. However,… More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Satin Bowerbird Optimizer Based Compression Technique for Remote Sensing Images

    M. Saravanan1, J. Jayanthi2, U. Sakthi3, R. Rajkumar4, Gyanendra Prasad Joshi5, L. Minh Dang5, Hyeonjoon Moon5,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2683-2696, 2022, DOI:10.32604/cmc.2022.025642
    Abstract Due to latest advancements in the field of remote sensing, it becomes easier to acquire high quality images by the use of various satellites along with the sensing components. But the massive quantity of data poses a challenging issue to store and effectively transmit the remote sensing images. Therefore, image compression techniques can be utilized to process remote sensing images. In this aspect, vector quantization (VQ) can be employed for image compression and the widely applied VQ approach is Linde–Buzo–Gray (LBG) which creates a local optimum codebook for image construction. The process of constructing the codebook can be treated as… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Machine Learning Model for Face Recognition Using SVM

    Anil Kumar Yadav1, R. K. Pateriya2, Nirmal Kumar Gupta3, Punit Gupta4,*, Dinesh Kumar Saini4, Mohammad Alahmadi5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052
    Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN. PCA-SVM, however,… More >

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    ARTICLE

    Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection System

    Ala Saleh Alluhaidan1, Masoud Alajmi2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2713-2727, 2022, DOI:10.32604/cmc.2022.025202
    Abstract Human fall detection (FD) acts as an important part in creating sensor based alarm system, enabling physical therapists to minimize the effect of fall events and save human lives. Generally, elderly people suffer from several diseases, and fall action is a common situation which can occur at any time. In this view, this paper presents an Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection (IAOA-DLFD) model to identify the fall/non-fall events. The proposed IAOA-DLFD technique comprises different levels of pre-processing to improve the input image quality. Besides, the IAOA with Capsule Network based feature extractor is derived to… More >

  • Open AccessOpen Access

    ARTICLE

    Embedded Coded Relay System for Molecular Communications

    Eman S. Attia1, Ashraf A. M. Khalaf1, Fathi E. Abd El-Samie2, Saied M. Abd El-atty2, Konstantinos A. Lizos3, Osama Alfarraj4, Farid Shawki2, Imran Khan5, Ki-Il Kim6,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2729-2748, 2022, DOI:10.32604/cmc.2022.026197
    Abstract With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or… More >

  • Open AccessOpen Access

    ARTICLE

    A Post-Processing Algorithm for Boosting Contrast of MRI Images

    B. Priestly Shan1, O. Jeba Shiney1, Sharzeel Saleem2, V. Rajinikanth3, Atef Zaguia4, Dilbag Singh5,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2749-2763, 2022, DOI:10.32604/cmc.2022.023057
    Abstract Low contrast of Magnetic Resonance (MR) images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis. State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images. Drastic changes in brightness features, induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings. To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well. This method termed as Power-law and Logarithmic Modification-based Histogram Equalization (PLMHE) partitions the histogram of the image into two… More >

  • Open AccessOpen Access

    ARTICLE

    Vision-based Recognition Algorithm for Up-To-Date Indoor Digital Map Generations at Damaged Buildings

    Dahyeon Kim1, Chulsu Kim2, Junho Ahn1,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2765-2781, 2022, DOI:10.32604/cmc.2022.025116
    Abstract When firefighters are engaged in search and rescue missions inside a building at a risk of collapse, they have difficulty in field command and rescue because they can only simply monitor the situation inside the building utilizing old building drawings or robots. To propose an efficient solution for fast search and rescue work of firefighters, this study investigates the generation of up-to-date digital maps for disaster sites by tracking the collapse situation, and identifying the information of obstacles which are risk factors, using an artificial intelligence algorithm based on low-cost robots. Our research separates the floor by using the mask… More >

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    ARTICLE

    Artificial Intelligence Based Data Offloading Technique for Secure MEC Systems

    Fadwa Alrowais1, Ahmed S. Almasoud2, Radwa Marzouk3, Fahd N. Al-Wesabi4,5, Anwer Mustafa Hilal6,*, Mohammed Rizwanullah6, Abdelwahed Motwakel6, Ishfaq Yaseen6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2783-2795, 2022, DOI:10.32604/cmc.2022.025204
    Abstract Mobile edge computing (MEC) provides effective cloud services and functionality at the edge device, to improve the quality of service (QoS) of end users by offloading the high computation tasks. Currently, the introduction of deep learning (DL) and hardware technologies paves a method in detecting the current traffic status, data offloading, and cyberattacks in MEC. This study introduces an artificial intelligence with metaheuristic based data offloading technique for Secure MEC (AIMDO-SMEC) systems. The proposed AIMDO-SMEC technique incorporates an effective traffic prediction module using Siamese Neural Networks (SNN) to determine the traffic status in the MEC system. Also, an adaptive sampling… More >

  • Open AccessOpen Access

    ARTICLE

    A Sparse Optimization Approach for Beyond 5G mmWave Massive MIMO Networks

    Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Imran Khan1, Nor Samsiah Sani2, Ki-Il Kim3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2797-2810, 2022, DOI:10.32604/cmc.2022.026185
    Abstract Millimeter-Wave (mmWave) Massive MIMO is one of the most effective technology for the fifth-generation (5G) wireless networks. It improves both the spectral and energy efficiency by utilizing the 30–300 GHz millimeter-wave bandwidth and a large number of antennas at the base station. However, increasing the number of antennas requires a large number of radio frequency (RF) chains which results in high power consumption. In order to reduce the RF chain's energy, cost and provide desirable quality-of-service (QoS) to the subscribers, this paper proposes an energy-efficient hybrid precoding algorithm for mmWave massive MIMO networks based on the idea of RF chains… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Control for Autonomous Robot

    Rihem Farkh1,2, Saad Alhuwaimel3,*, Sultan Alzahrani3, Khaled Al Jaloud1, Mohammad Tabrez Quasim4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2811-2824, 2022, DOI:10.32604/cmc.2022.020259
    Abstract Several applications of machine learning and artificial intelligence, have acquired importance and come to the fore as a result of recent advances and improvements in these approaches. Autonomous cars are one such application. This is expected to have a significant and revolutionary influence on society. Integration with smart cities, new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving automobiles. The autonomous automobile, often known as self-driving systems or driverless vehicles, is a vehicle that can perceive its surroundings and navigate predetermined routes without human involvement. Cars are on the verge of evolving into… More >

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    ARTICLE

    Dynamic Intelligent Supply-Demand Adaptation Model Towards Intelligent Cloud Manufacturing

    Yanfei Sun1, Feng Qiao2, Wei Wang1, Bin Xu1, Jianming Zhu1, Romany Fouad Mansour3, Jin Qi1,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2825-2843, 2022, DOI:10.32604/cmc.2022.026574
    Abstract As a new mode and means of smart manufacturing, smart cloud manufacturing (SCM) faces great challenges in massive supply and demand, dynamic resource collaboration and intelligent adaptation. To address the problem, this paper proposes an SCM-oriented dynamic supply-demand (S-D) intelligent adaptation model for massive manufacturing services. In this model, a collaborative network model is established based on the properties of both the supply-demand and their relationships; in addition, an algorithm based on deep graph clustering (DGC) and aligned sampling (AS) is used to divide and conquer the large adaptation domain to solve the problem of the slow computational speed caused… More >

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    ARTICLE

    Blockchain-based Distributed Power Market Trading Mechanism

    Dongjun Cui1,*, Jinghan He2, Guofang Zhang3, Zihan Hou4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2845-2858, 2022, DOI:10.32604/cmc.2022.026568
    Abstract Distributed power market trading has the characteristics of large number of participants, scattered locations, small single trading scale, and point-to-point trading. The traditional centralized power trading model has the problems of large load, low efficiency, high cost, reliance on third parties and unreliable data. With the characteristics of decentralization and non-tampering, blockchain can establish a point-to-point trusted trading environment and provide effective solutions to the above problems. Therefore, this paper proposed a distributed power market trading framework based on blockchain. In this framework, the distributed power supply characteristics and trading needs of each participant are analyzed, a complete distributed trading… More >

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    ARTICLE

    Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

    Areej A. Malibari1, Siwar Ben Haj Hassine2, Abdelwahed Motwakel3, Manar Ahmed Hamza3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2859-2875, 2022, DOI:10.32604/cmc.2022.026338
    Abstract Atherosclerosis diagnosis is an inarticulate and complicated cognitive process. Researches on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical decisions. Since the medical diagnostic outcomes need to be prompt and accurate, the recently developed artificial intelligence (AI) and deep learning (DL) models have received considerable attention among research communities. This study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification (MDL-BADDC) model. The proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing, feature selection, classification, and parameter tuning. Besides, the proposed MDL-BADDC technique designs a novel Quasi-Oppositional Barnacles Mating Optimizer… More >

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    ARTICLE

    Modified Bat Algorithm for Optimal VM's in Cloud Computing

    Amit Sundas1, Sumit Badotra1,*, Youseef Alotaibi2, Saleh Alghamdi3, Osamah Ibrahim Khalaf4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2877-2894, 2022, DOI:10.32604/cmc.2022.025658
    Abstract All task scheduling applications need to ensure that resources are optimally used, performance is enhanced, and costs are minimized. The purpose of this paper is to discuss how to Fitness Calculate Values (FCVs) to provide application software with a reliable solution during the initial stages of load balancing. The cloud computing environment is the subject of this study. It consists of both physical and logical components (most notably cloud infrastructure and cloud storage) (in particular cloud services and cloud platforms). This intricate structure is interconnected to provide services to users and improve the overall system's performance. This case study is… More >

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    ARTICLE

    Enhanced Artificial Intelligence-based Cybersecurity Intrusion Detection for Higher Education Institutions

    Abdullah S. AL-Malaise AL-Ghamdi1, Mahmoud Ragab2,3,4,*, Maha Farouk S. Sabir1
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2895-2907, 2022, DOI:10.32604/cmc.2022.026405
    Abstract As higher education institutions (HEIs) go online, several benefits are attained, and also it is vulnerable to several kinds of attacks. To accomplish security, this paper presents artificial intelligence based cybersecurity intrusion detection models to accomplish security. The incorporation of the strategies into business is a tendency among several distinct industries, comprising education, have recognized as game changer. Consequently, the HEIs are highly related to the requirement and knowledge of the learner, making the education procedure highly effective. Thus, artificial intelligence (AI) and machine learning (ML) models have shown significant interest in HEIs. This study designs a novel Artificial Intelligence… More >

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    ARTICLE

    Internal Validity Index for Fuzzy Clustering Based on Relative Uncertainty

    Refik Tanju Sirmen1,*, Burak Berk Üstündağ2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2909-2926, 2022, DOI:10.32604/cmc.2022.023947
    Abstract Unsupervised clustering and clustering validity are used as essential instruments of data analytics. Despite clustering being realized under uncertainty, validity indices do not deliver any quantitative evaluation of the uncertainties in the suggested partitionings. Also, validity measures may be biased towards the underlying clustering method. Moreover, neglecting a confidence requirement may result in over-partitioning. In the absence of an error estimate or a confidence parameter, probable clustering errors are forwarded to the later stages of the system. Whereas, having an uncertainty margin of the projected labeling can be very fruitful for many applications such as machine learning. Herein, the validity… More >

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    ARTICLE

    Vehicle Positioning Based on Optical Camera Communication in V2I Environments

    Pankaj Singh1, Huijin Jeon2, Sookeun Yun2, Byung Wook Kim3, Sung-Yoon Jung1,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2927-2945, 2022, DOI:10.32604/cmc.2022.024180
    Abstract Demand for precise vehicle positioning (VP) increases as autonomous vehicles have recently been drawing attention. This paper proposes a scheme for positioning vehicles on the move based on optical camera communication (OCC) technology in the vehicle-to-infrastructure (V2I) environment. Light-emitting diode (LED) streetlights and vehicle cameras are used as transmitters and receivers respectively. Regions of streetlights are detected and traced by examining images that are obtained from cameras of vehicles. Then, a scheme for analyzing visible light data extracted from the images is proposed. The proposed vehicle positioning scheme uses information on angles between vectors that are formed under the collinearity… More >

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    ARTICLE

    Optimized Hybrid Block Adams Method for Solving First Order Ordinary Differential Equations

    Hira Soomro1,*, Nooraini Zainuddin1, Hanita Daud1, Joshua Sunday2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2947-2961, 2022, DOI:10.32604/cmc.2022.025933
    Abstract Multistep integration methods are being extensively used in the simulations of high dimensional systems due to their lower computational cost. The block methods were developed with the intent of obtaining numerical results on numerous points at a time and improving computational efficiency. Hybrid block methods for instance are specifically used in numerical integration of initial value problems. In this paper, an optimized hybrid block Adams block method is designed for the solutions of linear and nonlinear first-order initial value problems in ordinary differential equations (ODEs). In deriving the method, the Lagrange interpolation polynomial was employed based on some data points… More >

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    ARTICLE

    Hybrid Chaotic Salp Swarm with Crossover Algorithm for Underground Wireless Sensor Networks

    Mariem Ayedi1,2,*, Walaa H. ElAshmawi3,4, Esraa Eldesouky1,3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2963-2980, 2022, DOI:10.32604/cmc.2022.025741
    Abstract Resource management in Underground Wireless Sensor Networks (UWSNs) is one of the pillars to extend the network lifetime. An intriguing design goal for such networks is to achieve balanced energy and spectral resource utilization. This paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data, received from the buried source nodes through a lossy soil medium, to the aboveground base station. A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover (HCSSC) algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource efficiency. The… More >

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    ARTICLE

    Your CAPTCHA Recognition Method Based on DEEP Learning Using MSER Descriptor

    Deepak Kumar1, Ramandeep Singh2, Sukhvinder Singh Bamber3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2981-2996, 2022, DOI:10.32604/cmc.2022.024221
    Abstract Individuals and PCs (personal computers) can be recognized using CAPTCHAs (Completely Automated Public Turing test to distinguish Computers and Humans) which are mechanized for distinguishing them. Further, CAPTCHAs are intended to be solved by the people, but are unsolvable by the machines. As a result, using Convolutional Neural Networks (CNNs) these tests can similarly be unraveled. Moreover, the CNNs quality depends majorly on: the size of preparation set and the information that the classifier is found out on. Next, it is almost unmanageable to handle issue with CNNs. A new method of detecting CAPTCHA has been proposed, which simultaneously solves… More >

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    ARTICLE

    Multi-Stream CNN-Based Personal Recognition Method Using Surface Electromyogram for 5G Security

    Jin Su Kim1, Min-Gu Kim1, Jae Myung Kim1,2, Sung Bum Pan1,2,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2997-3007, 2022, DOI:10.32604/cmc.2022.026572
    Abstract As fifth generation technology standard (5G) technology develops, the possibility of being exposed to the risk of cyber-attacks that exploits vulnerabilities in the 5G environment is increasing. The existing personal recognition method used for granting permission is a password-based method, which causes security problems. Therefore, personal recognition studies using bio-signals are being conducted as a method to access control to devices. Among bio-signal, surface electromyogram (sEMG) can solve the existing personal recognition problem that was unable to the modification of registered information owing to the characteristic changes in its signal according to the performed operation. Furthermore, as an advantage, sEMG… More >

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