Home / Journals / CMC / Vol.70, No.2, 2022
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  • Open AccessOpen Access

    ARTICLE

    Optimized Tuned Deep Learning Model for Chronic Kidney Disease Classification

    R. H. Aswathy1,*, P. Suresh1, Mohamed Yacin Sikkandar2, S. Abdel-Khalek3, Hesham Alhumyani4, Rashid A. Saeed4, Romany F. Mansour5
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2097-2111, 2022, DOI:10.32604/cmc.2022.019790
    Abstract In recent times, Internet of Things (IoT) and Cloud Computing (CC) paradigms are commonly employed in different healthcare applications. IoT gadgets generate huge volumes of patient data in healthcare domain, which can be examined on cloud over the available storage and computation resources in mobile gadgets. Chronic Kidney Disease (CKD) is one of the deadliest diseases that has high mortality rate across the globe. The current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm (FPA)-based Deep Neural Network (DNN) model abbreviated as FPA-DNN. The steps involved in the… More >

  • Open AccessOpen Access

    ARTICLE

    Human Gait Recognition Using Deep Learning and Improved Ant Colony Optimization

    Awais Khan1, Muhammad Attique Khan1, Muhammad Younus Javed1, Majed Alhaisoni2, Usman Tariq3, Seifedine Kadry4, Jung-In Choi5, Yunyoung Nam6,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2113-2130, 2022, DOI:10.32604/cmc.2022.018270
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract Human gait recognition (HGR) has received a lot of attention in the last decade as an alternative biometric technique. The main challenges in gait recognition are the change in in-person view angle and covariant factors. The major covariant factors are walking while carrying a bag and walking while wearing a coat. Deep learning is a new machine learning technique that is gaining popularity. Many techniques for HGR based on deep learning are presented in the literature. The requirement of an efficient framework is always required for correct and quick gait recognition. We proposed a fully… More >

  • Open AccessOpen Access

    ARTICLE

    Optimized Convolutional Neural Network Models for Skin Lesion Classification

    Juan Pablo Villa-Pulgarin1, Anderson Alberto Ruales-Torres1,2, Daniel Arias-Garzón1, Mario Alejandro Bravo-Ortiz1, Harold Brayan Arteaga-Arteaga1, Alejandro Mora-Rubio1, Jesus Alejandro Alzate-Grisales1, Esteban Mercado-Ruiz1, M. Hassaballah3, Simon Orozco-Arias4,5, Oscar Cardona-Morales1, Reinel Tabares-Soto1,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2131-2148, 2022, DOI:10.32604/cmc.2022.019529
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract Skin cancer is one of the most severe diseases, and medical imaging is among the main tools for cancer diagnosis. The images provide information on the evolutionary stage, size, and location of tumor lesions. This paper focuses on the classification of skin lesion images considering a framework of four experiments to analyze the classification performance of Convolutional Neural Networks (CNNs) in distinguishing different skin lesions. The CNNs are based on transfer learning, taking advantage of ImageNet weights. Accordingly, in each experiment, different workflow stages are tested, including data augmentation and fine-tuning optimization. Three CNN models More >

  • Open AccessOpen Access

    ARTICLE

    Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

    Abdullah Musaed Alkhiari1, Shailendra Mishra2,*, Mohammed AlShehri1
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2149-2169, 2022, DOI:10.32604/cmc.2022.019562
    Abstract Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based… More >

  • Open AccessOpen Access

    ARTICLE

    Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

    Altaf Hussain1,2, Khan Muhammad1, Hayat Ullah1, Amin Ullah1,4, Ali Shariq Imran3, Mi Young Lee1, Seungmin Rho1, Muhammad Sajjad2,3,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2171-2190, 2022, DOI:10.32604/cmc.2022.018181
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract Digital surveillance systems are ubiquitous and continuously generate massive amounts of data, and manual monitoring is required in order to recognise human activities in public areas. Intelligent surveillance systems that can automatically ide.pngy normal and abnormal activities are highly desirable, as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring. This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system. The proposed system addresses the limitations of existing manual… More >

  • Open AccessOpen Access

    ARTICLE

    Effectiveness Assessment of the Search-Based Statistical Structural Testing

    Yang Shi*, Xiaoyu Song, Marek Perkowski, Fu Li
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.018718
    Abstract Search-based statistical structural testing (SBSST) is a promising technique that uses automated search to construct input distributions for statistical structural testing. It has been proved that a simple search algorithm, for example, the hill-climber is able to optimize an input distribution. However, due to the noisy fitness estimation of the minimum triggering probability among all cover elements (Tri-Low-Bound), the existing approach does not show a satisfactory efficiency. Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time. Tri-Low-Bound is considered a strong criterion, and it is demonstrated to sustain a high fault-detecting… More >

  • Open AccessOpen Access

    ARTICLE

    Diffusion Based Channel Gains Estimation in WSN Using Fractional Order Strategies

    Nasir Mahmud Khokhar1, Muhammad Nadeem Majeed2, Syed Muslim Shah3,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2209-2224, 2022, DOI:10.32604/cmc.2022.019120
    Abstract In this study, it is proposed that the diffusion least mean square (LMS) algorithm can be improved by applying the fractional order signal processing methodologies. Application of Caputo’s fractional derivatives are considered in the optimization of cost function. It is suggested to derive a fractional order variant of the diffusion LMS algorithm. The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium. The topology of the network is selected such that a smaller number of nodes are informed. In the network, a… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Resource Allocation in Fog Computing Using QTCS Model

    M. Iyapparaja1, Naif Khalaf Alshammari2,*, M. Sathish Kumar1, S. Siva Rama Krishnan1, Chiranji Lal Chowdhary1
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2225-2239, 2022, DOI:10.32604/cmc.2022.015707
    (This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
    Abstract Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared. The embedded devices deployed with the Internet of Things (IoT) technology have increased since the past few years, and these devices generate huge amount of data. The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay. Real time applications require high bandwidth with reduced latency to ensure Quality of Service (QoS). To achieve this, fog computing plays a vital role in processing the request More >

  • Open AccessOpen Access

    ARTICLE

    New Modified Controlled Bat Algorithm for Numerical Optimization Problem

    Waqas Haider Bangyal1, Abdul Hameed1, Jamil Ahmad2, Kashif Nisar3,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Joel J. P. C. Rodrigues5,6, M. Adil Khan7, Danda B. Rawat8, Richard Etengu4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2241-2259, 2022, DOI:10.32604/cmc.2022.017789
    Abstract Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been… More >

  • Open AccessOpen Access

    ARTICLE

    A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

    Farrukh Zia1, Isma Irum1, Nadia Nawaz Qadri1, Yunyoung Nam2,*, Kiran Khurshid3, Muhammad Ali1, Imran Ashraf4, Muhammad Attique Khan4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2261-2276, 2022, DOI:10.32604/cmc.2022.017820
    (This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
    Abstract Diabetes or Diabetes Mellitus (DM) is the upset that happens due to high glucose level within the body. With the passage of time, this polygenic disease creates eye deficiency referred to as Diabetic Retinopathy (DR) which can cause a major loss of vision. The symptoms typically originate within the retinal space square in the form of enlarged veins, liquid dribble, exudates, haemorrhages and small scale aneurysms. In current therapeutic science, pictures are the key device for an exact finding of patients’ illness. Meanwhile, an assessment of new medicinal symbolisms stays complex. Recently, Computer Vision (CV)… More >

  • Open AccessOpen Access

    ARTICLE

    Deterministic and Stochastic Fractional-Order Hastings-Powell Food Chain Model

    Moustafa El-Shahed1,*, Asmaa M. Al-Dububan2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2277-2296, 2022, DOI:10.32604/cmc.2022.019314
    Abstract In this paper, a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed. The interaction between prey, middle predator and top predator population is investigated. In order to clarify the characteristics of the proposed model, the analysis of existence, uniqueness, non-negativity and boundedness of the solutions of the proposed model are examined. Some sufficient conditions that ensure the local and global stability of equilibrium points are obtained. By using stability analysis of the fractional-order system, it is proved that if the basic reproduction number , the predator More >

  • Open AccessOpen Access

    ARTICLE

    Hesitant Fuzzy-Sets Based Decision-Making Model for Security Risk Assessment

    Ahmed S. Alfakeeh1, Abdulmohsen Almalawi2, Fawaz Jaber Alsolami2, Yoosef B. Abushark2, Asif Irshad Khan2,*, Adel Aboud S. Bahaddad1, Alka Agrawal3, Rajeev Kumar4, Raees Ahmad Khan3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2297-2317, 2022, DOI:10.32604/cmc.2022.020146
    (This article belongs to the Special Issue: Emerging Trends and Real-World Applications of Intelligent Computing Techniques)
    Abstract Security is an important component in the process of developing healthcare web applications. We need to ensure security maintenance; therefore the analysis of healthcare web application's security risk is of utmost importance. Properties must be considered to minimise the security risk. Additionally, security risk management activities are revised, prepared, implemented, tracked, and regularly set up efficiently to design the security of healthcare web applications. Managing the security risk of a healthcare web application must be considered as the key component. Security is, in specific, seen as an add-on during the development process of healthcare web… More >

  • Open AccessOpen Access

    ARTICLE

    Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

    Buddhadeva Sahoo1,*, Sangram Keshari Routray2, Pravat Kumar Rout2, Mohammed M. Alhaider3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2319-2346, 2022, DOI:10.32604/cmc.2022.019559
    Abstract This paper presents a combined control and modulation technique to enhance the power quality (PQ) and power reliability (PR) of a hybrid energy system (HES) through a single-phase 11-level cascaded H-bridge inverter (11-CHBI). The controller and inverter specifically regulate the HES and meet the load demand. To track optimum power, a Modified Perturb and Observe (MP&O) technique is used for HES. Ultra-capacitor (UCAP) based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell conditions. For an improved PQ and PR, a… More >

  • Open AccessOpen Access

    ARTICLE

    Dorsal-Ventral Visual Pathways and Object Characteristics: Beamformer Source Analysis of EEG

    Akanksha Tiwari1, Ram Bilas Pachori1,2, Premjit Khanganba Sanjram1,3,4,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2347-2363, 2022, DOI:10.32604/cmc.2022.020299
    (This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
    Abstract In performing a gaming task, mental rotation (MR) is one of the important aspects of visuospatial processing. MR involves dorsal-ventral pathways of the brain. Visual objects/models used in computer-games play a crucial role in gaming experience of the users. The visuospatial characteristics of the objects used in the computer-game influence the engagement of dorsal-ventral visual pathways. The current study investigates how the objects’ visuospatial characteristics (i.e., angular disparity and dimensionality) in an MR-based computer-game influence the cortical activities in dorsal-ventral visual pathways. Both the factors have two levels, angular disparity: convex angle (CA) vs. reflex angle… More >

  • Open AccessOpen Access

    ARTICLE

    A Monte Carlo Based COVID-19 Detection Framework for Smart Healthcare

    Tallat Jabeen1,2, Ishrat Jabeen1, Humaira Ashraf2, Nz Jhanjhi3,*, Mamoona Humayun4, Mehedi Masud5, Sultan Aljahdali5
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2365-2380, 2022, DOI:10.32604/cmc.2022.020016
    Abstract COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through person-to-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors… More >

  • Open AccessOpen Access

    ARTICLE

    Proxy-Based Hierarchical Distributed Mobility Management for Tactical Networks

    Myoung-hun Han1,2, Bong-Soo Roh1, Kyungwoo Kim1, Dae-Hoon Kwon1, Jae-Hyun Ham1, KyungHyun Yoon2, Sanghyun Seo3,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2381-2399, 2022, DOI:10.32604/cmc.2022.020029
    Abstract An important requirement in a military domain is a highly reliable mobility management method, especially when components of the networks are moving in tactical network environments. To increase reliability, the mobility management technology of the tactical network should be able to reflect the characteristics of the tactical network, such as a limited environment, failure, and hierarchical unit structure. In this paper, we propose a proxy-based hierarchical distributed mobility management scheme, which is highly focused on tactical networks. Considering the characteristics of tactical networks, the proposed scheme is composed of the following: 1) a proxy-based method, More >

  • Open AccessOpen Access

    ARTICLE

    A New Reward System Based on Human Demonstrations for Hard Exploration Games

    Wadhah Zeyad Tareq*, Mehmet Fatih Amasyali
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2401-2414, 2022, DOI:10.32604/cmc.2022.020036
    (This article belongs to the Special Issue: Application of Big Data Analytics in the Management of Business)
    Abstract The main idea of reinforcement learning is evaluating the chosen action depending on the current reward. According to this concept, many algorithms achieved proper performance on classic Atari 2600 games. The main challenge is when the reward is sparse or missing. Such environments are complex exploration environments like Montezuma’s Revenge, Pitfall, and Private Eye games. Approaches built to deal with such challenges were very demanding. This work introduced a different reward system that enables the simple classical algorithm to learn fast and achieve high performance in hard exploration environments. Moreover, we added some simple enhancements… More >

  • Open AccessOpen Access

    ARTICLE

    Process Modelling and Experimental Analysis of Optimal Specimen Selection in Organic CMCs

    P. V. Rajesh1, Kanak Kalita2,*, Xiao-Zhi Gao3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2415-2433, 2022, DOI:10.32604/cmc.2022.018247
    Abstract Bone grafting is a surgical restructuring procedure of replacing broken bones and reconstructing missing bone pieces so that complex bone fractures can be repaired to avoid any serious health risk as well as permanent bone disfiguration. Normally, human bones tend to regenerate and heal completely from fracture. But it needs a small scaffold to provide the necessary space to grow. Bone implants allow a broken bone to grow seamlessly. Traditionally, non-corrosive metal alloys are used for fixing broken bones. A metal plate is fastened between two ends of broken bones to join them. However, issues… More >

  • Open AccessOpen Access

    ARTICLE

    Multi-Objective Grey Wolf Optimization Algorithm for Solving Real-World BLDC Motor Design Problem

    M. Premkumar1, Pradeep Jangir2, B. Santhosh Kumar3, Mohammad A. Alqudah4, Kottakkaran Sooppy Nisar5,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2435-2452, 2022, DOI:10.32604/cmc.2022.016488
    (This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract The first step in the design phase of the Brushless Direct Current (BLDC) motor is the formulation of the mathematical framework and is often used due to its analytical structure. Therefore, the BLDC motor design problem is considered to be an optimization problem. In this paper, the analytical model of the BLDC motor is presented, and it is considered to be a basis for emphasizing the optimization methods. The analytical model used for the experimentation has 78 non-linear equations, two objective functions, five design variables, and six non-linear constraints, so the BLDC motor design problem… More >

  • Open AccessOpen Access

    ARTICLE

    Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging

    Oday A. Hassen1,*, Nur Azman Abu1, Zaheera Zainal Abidin1, Saad M. Darwish2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2453-2469, 2022, DOI:10.32604/cmc.2022.019125
    Abstract A robust smile recognition system could be widely used for many real-world applications. Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images. In this paper, an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers. Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. The features are extracted taking into account to exclude… More >

  • Open AccessOpen Access

    ARTICLE

    A Real-Time Automatic Translation of Text to Sign Language

    Muhammad Sanaullah1,*, Babar Ahmad2, Muhammad Kashif2, Tauqeer Safdar2, Mehdi Hassan3, Mohd Hilmi Hasan4, Norshakirah Aziz4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2471-2488, 2022, DOI:10.32604/cmc.2022.019420
    (This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This… More >

  • Open AccessOpen Access

    ARTICLE

    Cross Intelligence Evaluation for Effective Emotional Intelligence Estimation

    Ibrahim Alsukayti1, Aman Singh2,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2489-2505, 2022, DOI:10.32604/cmc.2022.020264
    Abstract A famous psychologist or researcher, Daniel Goleman, gave a theory on the importance of Emotional Intelligence for the success of an individual’s life. Daniel Goleman quoted in the research that “The contribution of an individual’s Intelligence Quotient (IQ) is only 20% for their success, the remaining 80% is due to Emotional Intelligence (EQ)”. However, in the absence of a reliable technique for EQ evaluation, this factor of overall intelligence is ignored in most of the intelligence evaluation mechanisms. This research presented an analysis based on basic statistical tools along with more sophisticated deep learning tools.… More >

  • Open AccessOpen Access

    ARTICLE

    COVID19 Outbreak: A Hierarchical Framework for User Sentiment Analysis

    Ahmed F. Ibrahim1, M. Hassaballah2, Abdelmgeid A. Ali3, Yunyoung Nam4,*, Ibrahim A. Ibrahim3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2507-2524, 2022, DOI:10.32604/cmc.2022.018131
    (This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
    Abstract Social networking sites in the most modernized world are flooded with large data volumes. Extracting the sentiment polarity of important aspects is necessary; as it helps to determine people’s opinions through what they write. The Coronavirus pandemic has invaded the world and been given a mention in the social media on a large scale. In a very short period of time, tweets indicate unpredicted increase of coronavirus. They reflect people’s opinions and thoughts with regard to coronavirus and its impact on society. The research community has been interested in discovering the hidden relationships from short… More >

  • Open AccessOpen Access

    ARTICLE

    Secure Watermarking Scheme for Color DICOM Images in Telemedicine Applications

    Kamred Udham Singh1, Hatem Salem Abu-Hamatta2, Abhishek Kumar3, Achintya Singhal4, Mamoon Rashid5,*, A. K. Bashir6
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2525-2542, 2022, DOI:10.32604/cmc.2022.019302
    Abstract Teleradiology plays a vital role in the medical field, which permits transmitting medical and imaging data over a communication network. It ensures data reliability and provides convenient communication for clinical interpretation and diagnostic purposes. The transmission of this medical data over a network raises the problems of legal, ethical issues, privacy, and copyright authenticity. The copyright protection of medical images is a significant issue in the medical field. Watermarking schemes are used to address these issues. A gray-level or binary image is used as a watermark frequently in color image watermarking schemes. In this paper,… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Energy Optimized Faithful Adder with Parallel Carry Generation

    K. N. Vijeyakumar1, S. Maragatharaj2,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2543-2561, 2022, DOI:10.32604/cmc.2022.019789
    Abstract Approximate computing has received significant attention in the design of portable CMOS hardware for error-tolerant applications. This work proposes an approximate adder that to optimize area delay and achieve energy efficiency using Parallel Carry (PC) generation logic. For ‘n’ bits in input, the proposed algorithm use approximate addition for least n/2 significant bits and exact addition for most n/2 significant bits. A simple OR logic with no carry propagation is used to implement the approximate part. In the exact part, addition is performed using 4-bit adder blocks that implement PC at block level to reduce node capacitance… More >

  • Open AccessOpen Access

    ARTICLE

    Enhanced Detection of Glaucoma on Ensemble Convolutional Neural Network for Clinical Informatics

    D. Stalin David1,*, S. Arun Mozhi Selvi2, S. Sivaprakash3, P. Vishnu Raja4, Dilip Kumar Sharma5, Pankaj Dadheech6, Sudhakar Sengan7
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2563-2579, 2022, DOI:10.32604/cmc.2022.020059
    Abstract Irretrievable loss of vision is the predominant result of Glaucoma in the retina. Recently, multiple approaches have paid attention to the automatic detection of glaucoma on fundus images. Due to the interlace of blood vessels and the herculean task involved in glaucoma detection, the exactly affected site of the optic disc of whether small or big size cup, is deemed challenging. Spatially Based Ellipse Fitting Curve Model (SBEFCM) classification is suggested based on the Ensemble for a reliable diagnosis of Glaucoma in the Optic Cup (OC) and Optic Disc (OD) boundary correspondingly. This research deploys… More >

  • Open AccessOpen Access

    ARTICLE

    Cloud Security Service for Identifying Unauthorized User Behaviour

    D. Stalin David1, Mamoona Anam2, Chandraprabha Kaliappan3, S. Arun Mozhi Selvi4, Dilip Kumar Sharma5, Pankaj Dadheech6, Sudhakar Sengan7,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2581-2600, 2022, DOI:10.32604/cmc.2022.020213
    Abstract Recently, an innovative trend like cloud computing has progressed quickly in Information Technology. For a background of distributed networks, the extensive sprawl of internet resources on the Web and the increasing number of service providers helped cloud computing technologies grow into a substantial scaled Information Technology service model. The cloud computing environment extracts the execution details of services and systems from end-users and developers. Additionally, through the system’s virtualization accomplished using resource pooling, cloud computing resources become more accessible. The attempt to design and develop a solution that assures reliable and protected authentication and authorization More >

  • Open AccessOpen Access

    ARTICLE

    Data-Driven Self-Learning Controller for Power-Aware Mobile Monitoring IoT Devices

    Michal Prauzek*, Tereza Paterova, Jaromir Konecny, Radek Martinek
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2601-2618, 2022, DOI:10.32604/cmc.2022.019705
    Abstract Nowadays, there is a significant need for maintenance free modern Internet of things (IoT) devices which can monitor an environment. IoT devices such as these are mobile embedded devices which provide data to the internet via Low Power Wide Area Network (LPWAN). LPWAN is a promising communications technology which allows machine to machine (M2M) communication and is suitable for small mobile embedded devices. The paper presents a novel data-driven self-learning (DDSL) controller algorithm which is dedicated to controlling small mobile maintenance-free embedded IoT devices. The DDSL algorithm is based on a modified Q-learning algorithm which… More >

  • Open AccessOpen Access

    ARTICLE

    Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

    Mukhtar Ghaleb1,*, Yahya Almurtadha2, Fahad Algarni3, Monir Abdullah3, Emad Felemban4, Ali M. Alsharafi3, Mohamed Othman5, Khaled Ghilan6
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2619-2638, 2022, DOI:10.32604/cmc.2022.020358
    Abstract People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased responses. However, chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their scope. Chatbots employ Natural Language Understanding (NLU) to infer their responses. There is a need for a chatbot that can learn from inquiries and expand its area of experience with time. This chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast retrieval. This study proposes a methodology to… More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Deep Reinforcement Learning for Intrusion Detection in UAVs

    V. Praveena1, A. Vijayaraj2, P. Chinnasamy3, Ihsan Ali4,*, Roobaea Alroobaea5, Saleh Yahya Alyahyan6, Muhammad Ahsan Raza7
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2639-2653, 2022, DOI:10.32604/cmc.2022.020066
    Abstract In recent years, progressive developments have been observed in recent technologies and the production cost has been continuously decreasing. In such scenario, Internet of Things (IoT) network which is comprised of a set of Unmanned Aerial Vehicles (UAV), has received more attention from civilian to military applications. But network security poses a serious challenge to UAV networks whereas the intrusion detection system (IDS) is found to be an effective process to secure the UAV networks. Classical IDSs are not adequate to handle the latest computer networks that possess maximum bandwidth and data traffic. In order… More >

  • Open AccessOpen Access

    ARTICLE

    Engagement Detection Based on Analyzing Micro Body Gestures Using 3D CNN

    Shoroog Khenkar1,*, Salma Kammoun Jarraya1,2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2655-2677, 2022, DOI:10.32604/cmc.2022.019152
    (This article belongs to the Special Issue: Machine Learning Applications in Medical, Finance, Education and Cyber Security)
    Abstract This paper proposes a novel, efficient and affordable approach to detect the students’ engagement levels in an e-learning environment by using webcams. Our method analyzes spatiotemporal features of e-learners’ micro body gestures, which will be mapped to emotions and appropriate engagement states. The proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video frames. We follow a transfer learning approach by using the C3D model that was trained on the Sports-1M dataset. The adopted C3D model was used based on two different approaches; as a feature More >

  • Open AccessOpen Access

    ARTICLE

    User Behavior Traffic Analysis Using a Simplified Memory-Prediction Framework

    Rahmat Budiarto1,*, Ahmad A. Alqarni1, Mohammed Y. Alzahrani1, Muhammad Fermi Pasha2, Mohamed Fazil Mohamed Firdhous3, Deris Stiawan4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2679-2698, 2022, DOI:10.32604/cmc.2022.019847
    (This article belongs to the Special Issue: Machine Learning Applications in Medical, Finance, Education and Cyber Security)
    Abstract As nearly half of the incidents in enterprise security have been triggered by insiders, it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software (malware) in real-time. Failing to do so may cause a serious loss of reputation as well as business. At the same time, modern network traffic has dynamic patterns, high complexity, and large volumes that make it more difficult to detect malware early. The ability to learn tasks sequentially is crucial to the development of artificial intelligence.… More >

  • Open AccessOpen Access

    REVIEW

    Reconfigurable Pattern Patch Antenna for Mid-Band 5G: A Review

    Siti Rahena Isa1,2, Muzammil Jusoh2,*, Thennarasan Sabapathy2, Jamel Nebhen3, Muhammad Ramlee Kamarudin4, Mohamed Nasrun Osman2, Qammer Hussain Abbasi5, Hasliza A. Rahim2, Mohd Najib Mohd Yasin2, Ping Jack Soh2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2699-2725, 2022, DOI:10.32604/cmc.2022.019769
    (This article belongs to the Special Issue: Advances in 5G Antenna Designs and Systems)
    Abstract New requirements in communication technologies make it imperative to rehash conventional features such as reconfigurable antennas to adapt with the future adaptability advancements. This paper presents a comprehensive review of reconfigurable antennas, specifically in terms of radiation patterns for adaptation in the upcoming Fifth Generation (5G) New Radio frequency bands. They represent the key of antenna technology for materializing a high rate transmission, increased spectral and energy efficiency, reduced interference, and improved the beam steering and beam shaping, thereby land a great promise for planar antennas to boost the mid-band 5G. This review begins with… More >

  • Open AccessOpen Access

    ARTICLE

    SIMAD: Secure Intelligent Method for IoT-Fog Environments Attacks Detection

    Wided Ben Daoud1, Sami Mahfoudhi2,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2727-2742, 2022, DOI:10.32604/cmc.2022.020141
    Abstract The Internet of Thing IoT paradigm has emerged in numerous domains and it has achieved an exponential progress. Nevertheless, alongside this advancement, IoT networks are facing an ever-increasing rate of security risks because of the continuous and rapid changes in network environments. In order to overcome these security challenges, the fog system has delivered a powerful environment that provides additional resources for a more improved data security. However, because of the emerging of various breaches, several attacks are ceaselessly emerging in IoT and Fog environment. Consequently, the new emerging applications in IoT-Fog environment still require… More >

  • Open AccessOpen Access

    ARTICLE

    Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning

    Mehdi Hassan1,*, Safdar Ali2, Muhammad Sanaullah3, Khuram Shahzad4, Sadaf Mushtaq5,6, Rashda Abbasi6, Zulqurnain Ali4, Hani Alquhayz7
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2743-2760, 2022, DOI:10.32604/cmc.2022.020055
    (This article belongs to the Special Issue: Role of Machine Learning and Evolutionary Algorithms for Cancer Detection and Prediction)
    Abstract Cancer is the second deadliest human disease worldwide with high mortality rate. Rehabilitation and treatment of this disease requires precise and automatic assessment of effective drug response and control system. Prediction of treated and untreated cancerous cell line is one of the most challenging problems for precise and targeted drug delivery and response. A novel approach is proposed for prediction of drug treated and untreated cancer cell line automatically by employing modified Deep neural networks. Human hepatocellular carcinoma (HepG2) cells are exposed to anticancer drug functionalized CFO@BTO nanoparticles developed by our lab. Prediction models are… More >

  • Open AccessOpen Access

    ARTICLE

    Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

    Abdul Hanan Ashraf1, Muhammad Imran1, Abdulrahman M. Qahtani2,*, Abdulmajeed Alsufyani2, Omar Almutiry3, Awais Mahmood3, Muhammad Attique4, Mohamed Habib5,6
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2761-2775, 2022, DOI:10.32604/cmc.2022.018785
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract In recent years, the number of Gun-related incidents has crossed over 250,000 per year and over 85% of the existing 1 billion firearms are in civilian hands, manual monitoring has not proven effective in detecting firearms. which is why an automated weapon detection system is needed. Various automated convolutional neural networks (CNN) weapon detection systems have been proposed in the past to generate good results. However, These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection system. These models have a high rate of false… More >

  • Open AccessOpen Access

    ARTICLE

    Multi-Attribute Selection Procedures Based on Regret and Rejoice for the Decision-Maker

    Hanan Abdullah Mengash*, Manel Farouk Ayadi
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2777-2795, 2022, DOI:10.32604/cmc.2022.015434
    (This article belongs to the Special Issue: Powering the Future Intelligence - Ambient Social Media Analytics)
    Abstract Feelings influence human beings’ decision-making; therefore, incorporation of feeling factors in decision-making is very important. Regret and rejoice are very important emotional feelings that can have a great impact on decision-making if they are considered together. While regret has received most of the attention in related research, rejoice has been less considered even though it can greatly influence people’s preferences in decision-making. Furthermore, systematically incorporating regret and rejoice in the multi-criteria decision-making (MCDM) modeling frameworks for decision-making has received little research attention. In this paper, we introduce a new multi-attribute selection procedure that incorporates both… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Rank-Based Average Pooling Network for Covid-19 Recognition

    Shui-Hua Wang1, Muhammad Attique Khan2, Vishnuvarthanan Govindaraj3, Steven L. Fernandes4, Ziquan Zhu5, Yu-Dong Zhang6,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2797-2813, 2022, DOI:10.32604/cmc.2022.020140
    (This article belongs to the Special Issue: Recent Advances in Deep Learning and Saliency Methods for Agriculture)
    Abstract (Aim) To make a more accurate and precise COVID-19 diagnosis system, this study proposed a novel deep rank-based average pooling network (DRAPNet) model, i.e., deep rank-based average pooling network, for COVID-19 recognition. (Methods) 521 subjects yield 1164 slice images via the slice level selection method. All the 1164 slice images comprise four categories: COVID-19 positive; community-acquired pneumonia; second pulmonary tuberculosis; and healthy control. Our method firstly introduced an improved multiple-way data augmentation. Secondly, an n-conv rank-based average pooling module (NRAPM) was proposed in which rank-based pooling—particularly, rank-based average pooling (RAP)—was employed to avoid overfitting. Third, a… More >

  • Open AccessOpen Access

    ARTICLE

    Artificial Intelligence in Medicine: Real Time Electronic Stethoscope for Heart Diseases Detection

    Batyrkhan Omarov1,2,*, Nurbek Saparkhojayev2, Shyrynkyz Shekerbekova3, Oxana Akhmetova1, Meruert Sakypbekova1, Guldina Kamalova3, Zhanna Alimzhanova1, Lyailya Tukenova3, Zhadyra Akanova4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2815-2833, 2022, DOI:10.32604/cmc.2022.019246
    Abstract Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1)… More >

  • Open AccessOpen Access

    ARTICLE

    Integrating Blockchain Technology into Healthcare Through an Intelligent Computing Technique

    Asif Irshad Khan1,*, Abdullah Saad Al-Malaise ALGhamdi2, Fawaz Jaber Alsolami1, Yoosef B. Abushark1, Abdulmohsen Almalawi1, Abdullah Marish Ali1, Alka Agrawal3, Rajeev Kumar4, Raees Ahmad Khan3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2835-2860, 2022, DOI:10.32604/cmc.2022.020342
    (This article belongs to the Special Issue: Big Data Security Using Artificial Intelligence-based Approaches)
    Abstract The blockchain technology plays a significant role in the present era of information technology. In the last few years, this technology has been used effectively in several domains. It has already made significant differences in human life, as well as is intended to have noticeable impact in many other domains in the forthcoming years. The rapid growth in blockchain technology has created numerous new possibilities for use, especially for healthcare applications. The digital healthcare services require highly effective security methodologies that can integrate data security with the available management strategies. To test and understand this… More >

  • Open AccessOpen Access

    ARTICLE

    Handling Class Imbalance in Online Transaction Fraud Detection

    Kanika1, Jimmy Singla1, Ali Kashif Bashir2, Yunyoung Nam3,*, Najam UI Hasan4, Usman Tariq5
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2861-2877, 2022, DOI:10.32604/cmc.2022.019990
    (This article belongs to the Special Issue: Emerging Trends in Artificial Intelligence and Machine Learning)
    Abstract With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem.… More >

  • Open AccessOpen Access

    ARTICLE

    Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

    Mesfer Al Duhayyim1, Manal Abdullah Alohali2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5,*, Mohammad Medani3, Manar Ahmed Hamza5
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2879-2894, 2022, DOI:10.32604/cmc.2022.019594
    Abstract The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text More >

  • Open AccessOpen Access

    ARTICLE

    Analysis of Distance-Based Topological Polynomials Associated with Zero-Divisor Graphs

    Ali Ahmad1, Roslan Hasni2,*, Nahid Akhter3, Kashif Elahi4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2895-2904, 2022, DOI:10.32604/cmc.2022.015644
    Abstract Chemical compounds are modeled as graphs. The atoms of molecules represent the graph vertices while chemical bonds between the atoms express the edges. The topological indices representing the molecular graph corresponds to the different chemical properties of compounds. Let be are two positive integers, and be the zero-divisor graph of the commutative ring . In this article some direct questions have been answered that can be utilized latterly in different applications. This study starts with simple computations, leading to a quite complex ring theoretic problems to prove certain properties. The theory of finite commutative rings More >

  • Open AccessOpen Access

    ARTICLE

    AMBO: All Members-Based Optimizer for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi1, Sajjad Amiri Doumari1, Mohammad Dehghani2, Zeinab Montazeri2, Pavel Trojovský3,*, Gaurav Dhiman4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2905-2921, 2022, DOI:10.32604/cmc.2022.019867
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in… More >

  • Open AccessOpen Access

    ARTICLE

    An Optimized Algorithm for Resource Allocation for D2D in Heterogeneous Networks

    Abdul Kadir Hamid1, Fahd N. Al-Wesabi2,3,*, Nadhem Nemri4, Ammar Zahary3, Imran Khan5
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2923-2936, 2022, DOI:10.32604/cmc.2022.020309
    Abstract With the emergence of 5G mobile multimedia services, end users’ demand for high-speed, low-latency mobile communication network access is increasing. Among them, the device-to-device (D2D) communication is one of the considerable technology. In D2D communication, the data does not need to be relayed and forwarded by the base station, but under the control of the base station, a direct local link is allowed between two adjacent mobile devices. This flexible communication mode reduces the processing bottlenecks and coverage blind spots of the base station, and can be widely used in dense user communication scenarios such… More >

  • Open AccessOpen Access

    ARTICLE

    A Deep Learning-Based Continuous Blood Pressure Measurement by Dual Photoplethysmography Signals

    Chih-Ta Yen1,*, Sheng-Nan Chang2, Liao Jia-Xian3, Yi-Kai Huang3
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2937-2952, 2022, DOI:10.32604/cmc.2022.020493
    Abstract This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a deep learning (DL) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI) and heart rate (HR); these indicators were then fed into the DL to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3… More >

  • Open AccessOpen Access

    ARTICLE

    Enhancing Parkinson’s Disease Diagnosis Accuracy Through Speech Signal Algorithm Modeling

    Omar M. El-Habbak1, Abdelrahman M. Abdelalim1, Nour H. Mohamed1, Habiba M. Abd-Elaty1, Mostafa A. Hammouda1, Yasmeen Y. Mohamed1, Mohanad A. Taifor1, Ali W. Mohamed2,3,*
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2953-2969, 2022, DOI:10.32604/cmc.2022.020109
    (This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract Parkinson’s disease (PD), one of whose symptoms is dysphonia, is a prevalent neurodegenerative disease. The use of outdated diagnosis techniques, which yield inaccurate and unreliable results, continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field. To solve this issue, the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’ voice recordings. Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers. Results were highly successful, with 90% accuracy produced by the random More >

  • Open AccessOpen Access

    ARTICLE

    A Feature Selection Strategy to Optimize Retinal Vasculature Segmentation

    José Escorcia-Gutierrez1,4,*, Jordina Torrents-Barrena4, Margarita Gamarra2, Natasha Madera1, Pedro Romero-Aroca3, Aida Valls4, Domenec Puig4
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2971-2989, 2022, DOI:10.32604/cmc.2022.020074
    Abstract Diabetic retinopathy (DR) is a complication of diabetes mellitus that appears in the retina. Clinitians use retina images to detect DR pathological signs related to the occlusion of tiny blood vessels. Such occlusion brings a degenerative cycle between the breaking off and the new generation of thinner and weaker blood vessels. This research aims to develop a suitable retinal vasculature segmentation method for improving retinal screening procedures by means of computer-aided diagnosis systems. The blood vessel segmentation methodology relies on an effective feature selection based on Sequential Forward Selection, using the error rate of a… More >

  • Open AccessOpen Access

    ARTICLE

    Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

    Shibli Nisar1, Muhammad Asghar Khan2,*, Fahad Algarni3, Abdul Wakeel1, M. Irfan Uddin4, Insaf Ullah2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376
    (This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
    Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted… More >

  • Open AccessOpen Access

    ARTICLE

    Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

    Chia-Nan Wang1, Chao-Fen Pan1,*, Viet Tinh Nguyen2, Syed Tam Husain2
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3005-3019, 2022, DOI:10.32604/cmc.2022.020206
    (This article belongs to the Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
    Abstract As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is… More >

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