Home / Journals / CMC / Vol.70, No.1, 2022
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  • Open AccessOpen Access

    ARTICLE

    Multiscale Image Dehazing and Restoration: An Application for Visual Surveillance

    Samia Riaz1, Muhammad Waqas Anwar2, Irfan Riaz3, Hyun-Woo Kim4, Yunyoung Nam4,*, Muhammad Attique Khan5
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1-17, 2022, DOI:10.32604/cmc.2022.018268
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract The captured outdoor images and videos may appear blurred due to haze, fog, and bad weather conditions. Water droplets or dust particles in the atmosphere cause the light to scatter, resulting in very limited scene discernibility and deterioration in the quality of the image captured. Currently, image dehazing has gained much popularity because of its usability in a wide variety of applications. Various algorithms have been proposed to solve this ill-posed problem. These algorithms provide quite promising results in some cases, but they include undesirable artifacts and noise in haze patches in adverse cases. Some… More >

  • Open AccessOpen Access

    ARTICLE

    Measuring End-to-End Delay in Low Energy SDN IoT Platform

    Mykola Beshley1, Natalia Kryvinska2,*, Halyna Beshley1, Orest Kochan1, Leonard Barolli3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 19-41, 2022, DOI:10.32604/cmc.2022.018579
    (This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
    Abstract In this paper, we developed a new customizable low energy Software Defined Networking (SDN) based Internet of Things (IoT) platform that can be reconfigured according to the requirements of the target IoT applications. Technically, the platform consists of a set of low cost and energy efficient single-board computers, which are interconnected within a network with the software defined configuration. The proposed SDN switch is deployed on Raspberry Pi 3 board using Open vSwitch (OvS) software, while the Floodlight controller is deployed on the Orange Pi Prime board. We firstly presented and implemented the method for More >

  • Open AccessOpen Access

    ARTICLE

    Deep Optimal VGG16 Based COVID-19 Diagnosis Model

    M. Buvana1, K. Muthumayil2, S. Senthil kumar3, Jamel Nebhen4, Sultan S. Alshamrani5, Ihsan Ali6,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 43-58, 2022, DOI:10.32604/cmc.2022.019331
    Abstract Coronavirus (COVID-19) outbreak was first identified in Wuhan, China in December 2019. It was tagged as a pandemic soon by the WHO being a serious public medical condition worldwide. In spite of the fact that the virus can be diagnosed by qRT-PCR, COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray (CXR) and Computed Tomography (CT) images. In this paper, the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various features. Impressive features like Speeded-Up… More >

  • Open AccessOpen Access

    ARTICLE

    Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic

    Iram Mushtaq1, Muhammad Umer1, Muhammad Imran2, Inzamam Mashood Nasir3, Ghulam Muhammad4,*, Mohammad Shorfuzzaman5
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 59-72, 2022, DOI:10.32604/cmc.2022.019337
    (This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
    Abstract During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of… More >

  • Open AccessOpen Access

    ARTICLE

    A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data

    Harshita Patel1, Dharmendra Singh Rajput1,*, Ovidiu Petru Stan2, Liviu Cristian Miclea2
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 73-89, 2022, DOI:10.32604/cmc.2022.017114
    (This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
    Abstract Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other classes. The Imbalanced distribution of data is a natural occurrence in real world datasets, so needed to be dealt with carefully to get important insights. In case of imbalance in data sets, traditional classifiers have to sacrifice their performances, therefore lead to misclassifications. This paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this issue. We have adapted the ‘existing algorithm modification solution’ to learn… More >

  • Open AccessOpen Access

    ARTICLE

    A Hybrid Approach for Network Intrusion Detection

    Mavra Mehmood1, Talha Javed2, Jamel Nebhen3, Sidra Abbas2,*, Rabia Abid1, Giridhar Reddy Bojja4, Muhammad Rizwan1
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 91-107, 2022, DOI:10.32604/cmc.2022.019127
    (This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
    Abstract Due to the widespread use of the internet and smart devices, various attacks like intrusion, zero-day, Malware, and security breaches are a constant threat to any organization's network infrastructure. Thus, a Network Intrusion Detection System (NIDS) is required to detect attacks in network traffic. This paper proposes a new hybrid method for intrusion detection and attack categorization. The proposed approach comprises three steps to address high false and low false-negative rates for intrusion detection and attack categorization. In the first step, the dataset is preprocessed through the data transformation technique and min-max method. Secondly, the More >

  • Open AccessOpen Access

    ARTICLE

    Joint Channel and Multi-User Detection Empowered with Machine Learning

    Mohammad Sh. Daoud1, Areej Fatima2, Waseem Ahmad Khan3, Muhammad Adnan Khan4,5,*, Sagheer Abbas3, Baha Ihnaini6, Munir Ahmad3, Muhammad Sheraz Javeid7, Shabib Aftab3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 109-121, 2022, DOI:10.32604/cmc.2022.019295
    Abstract The numbers of multimedia applications and their users increase with each passing day. Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems. In this article, a fuzzy logic empowered adaptive backpropagation neural network (FLeABPNN) algorithm is proposed for joint channel and multi-user detection (CMD). FLeABPNN has two stages. The first stage estimates the channel parameters, and the second performs multi-user detection. The proposed approach capitalizes on a neuro-fuzzy hybrid system that combines the competencies of both fuzzy logic and neural More >

  • Open AccessOpen Access

    ARTICLE

    Amino Acid Encryption Method Using Genetic Algorithm for Key Generation

    Ahmed S. Sakr1, M. Y. Shams2, Amena Mahmoud3, Mohammed Zidan4,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 123-134, 2022, DOI:10.32604/cmc.2022.019455
    (This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract In this new information era, the transfer of data and information has become a very important matter. Transferred data must be kept secured from unauthorized persons using cryptography. The science of cryptography depends not only on complex mathematical models but also on encryption keys. Amino acid encryption is a promising model for data security. In this paper, we propose an amino acid encryption model with two encryption keys. The first key is generated randomly using the genetic algorithm. The second key is called the protein key which is generated from converting DNA to a protein… More >

  • Open AccessOpen Access

    ARTICLE

    A Robust MPPT Control Based on Double Ended Forward Converter Architecture

    M. Usman Khan1,*, K. M. Hasan1, A. Faisal Murtaza2, H. M. Usman2, Hadeed A. Sher3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 135-150, 2022, DOI:10.32604/cmc.2022.019381
    Abstract

    In this paper, a stand-alone photovoltaic (PV) system based on a Double Ended Forward Converter (DEFC) is presented. The proposed converter is specified for 48 V, 100 W applications as most of the equipment used in telecommunication and aircraft fall in this range. The literature has limited potential application of DEFC in PV systems. The research work deals with an in-depth study of DEFC and proposes an improved DEFC for PV applications with battery backup. Besides, a bi-directional dc-dc converter for the battery is integrated to track the Maximum Power Point (MPP) of the PV

    More >

  • Open AccessOpen Access

    ARTICLE

    Design of a Low-Cost Air Quality Monitoring System Using Arduino and ThingSpeak

    Anabi Hilary Kelechi1, Mohammed H. Alsharif2, Chidumebi Agbaetuo3, Osichinaka Ubadike1, Alex Aligbe1, Peerapong Uthansakul4,*, Raju Kannadasan5, Ayman A. Aly6
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 151-169, 2022, DOI:10.32604/cmc.2022.019431
    Abstract The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing concerns. This impact has significantly led to a notable increase in mortality in the highly industrialized zones. Therefore, monitoring air quality and creating public awareness are important for a safer future, which led the governments globally to invest multi-billion in policymaking and solution stratification to address the problem. This study aims to design a real-time Internet of Things low-cost air quality monitoring system. The system utilizes air quality and carbon monoxide sensors… More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Tuning of FOPID-Like Fuzzy Controller for High-Performance Fractional-Order Systems

    Ahmed M. Nassef1,2,*, Hegazy Rezk1,3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 171-180, 2022, DOI:10.32604/cmc.2022.019347
    Abstract This paper addresses improvements in fractional order (FO) system performance. Although the classical proportional–integral–derivative (PID)-like fuzzy controller can provide adequate results for both transient and steady-state responses in both linear and nonlinear systems, the FOPID fuzzy controller has been proven to provide better results. This high performance was obtained thanks to the combinative benefits of FO and fuzzy-logic techniques. This paper describes how the optimal gains and FO parameters of the FOPID controller were obtained by the use of a modern optimizer, social spider optimization, in order to improve the response of fractional dynamical systems.… More >

  • Open AccessOpen Access

    ARTICLE

    Tour Planning Design for Mobile Robots Using Pruned Adaptive Resonance Theory Networks

    S. Palani Murugan1,*, M. Chinnadurai1, S. Manikandan2
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 181-194, 2022, DOI:10.32604/cmc.2022.016152
    Abstract The development of intelligent algorithms for controlling autonom- ous mobile robots in real-time activities has increased dramatically in recent years. However, conventional intelligent algorithms currently fail to accurately predict unexpected obstacles involved in tour paths and thereby suffer from inefficient tour trajectories. The present study addresses these issues by proposing a potential field integrated pruned adaptive resonance theory (PPART) neural network for effectively managing the touring process of autonomous mobile robots in real-time. The proposed system is implemented using the AlphaBot platform, and the performance of the system is evaluated according to the obstacle prediction More >

  • Open AccessOpen Access

    ARTICLE

    Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

    Xiaoli He1, Yu Song2,3,*, Yu Xue4, Muhammad Owais5, Weijian Yang1, Xinwen Cheng1
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 195-212, 2022, DOI:10.32604/cmc.2022.017105
    Abstract Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR,… More >

  • Open AccessOpen Access

    ARTICLE

    Empirical Assessment of Bacillus Calmette-Guérin Vaccine to Combat COVID-19

    Nikita Jain1, Vedika Gupta1,*, Chinmay Chakraborty2, Agam Madan1, Deepali Virmani3, Lorenzo Salas-Morera4, Laura Garcia-Hernandez4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 213-231, 2022, DOI:10.32604/cmc.2022.016424
    (This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
    Abstract COVID-19 has become one of the critical health issues globally, which surfaced first in latter part of the year 2019. It is the topmost concern for many nations’ governments as the contagious virus started mushrooming over adjacent regions of infected areas. In 1980, a vaccine called Bacillus Calmette-Guérin (BCG) was introduced for preventing tuberculosis and lung cancer. Countries that have made the BCG vaccine mandatory have witnessed a lesser COVID-19 fatality rate than the countries that have not made it compulsory. This paper’s initial research shows that the countries with a long-term compulsory BCG vaccination… More >

  • Open AccessOpen Access

    ARTICLE

    A Cost-Effective Approach for NDN-Based Internet of Medical Things Deployment

    Syed Sajid Ullah1, Saddam Hussain1, Abdu Gumaei2,3,*, Mohsin S. Alhilal4, Bader Fahad Alkhamees4, Mueen Uddin5, Mabrook Al-Rakhami2
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 233-249, 2022, DOI:10.32604/cmc.2022.017971
    Abstract Nowadays, healthcare has become an important area for the Internet of Things (IoT) to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services. At present, the host-based Internet paradigm is used for sharing and accessing healthcare-related data. However, due to the location-dependent nature, it suffers from latency, mobility, and security. For this purpose, Named Data Networking (NDN) has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm. Unfortunately, the novel breed lacks a secure framework for healthcare. This article constructs an More >

  • Open AccessOpen Access

    ARTICLE

    Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

    Mohammad Riyaz Belgaum1, Fuead Ali1, Zainab Alansari2, Shahrulniza Musa1,*, Muhammad Mansoor Alam1,3, M. S. Mazliham4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211
    Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To… More >

  • Open AccessOpen Access

    ARTICLE

    Soft -Rough Set and Its Applications in Decision Making of Coronavirus

    M. A. El Safty1,*, Samirah Al Zahrani1, M. K. El-Bably2, M. El Sayed3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 267-285, 2022, DOI:10.32604/cmc.2022.019345
    (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 In this paper, we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al. approach. Comparisons were obtained between our approach and the previous study and also. Eventually, an application on Coronavirus (COVID-19) has been presented, illustrated using our proposed concept, and some influencing results for symptoms of Coronavirus patients have been deduced. Moreover, following these concepts, we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach. Finally, a proposed approach that competes with others has been More >

  • Open AccessOpen Access

    ARTICLE

    Stock Prediction Based on Technical Indicators Using Deep Learning Model

    Manish Agrawal1, Piyush Kumar Shukla2, Rajit Nair3, Anand Nayyar4,5,*, Mehedi Masud6
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.014637
    Abstract Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature. The stock data is usually non-stationary, and attributes are non-correlative to each other. Several traditional Stock Technical Indicators (STIs) may incorrectly predict the stock market trends. To study the stock market characteristics using STIs and make efficient trading decisions, a robust model is built. This paper aims to build up an Evolutionary Deep Learning Model (EDLM) to identify stock trends’ prices by using STIs. The proposed model has implemented the Deep Learning… More >

  • Open AccessOpen Access

    ARTICLE

    Three Dimensional Optimum Node Localization in Dynamic Wireless Sensor Networks

    Gagandeep Singh Walia1, Parulpreet Singh1, Manwinder Singh1, Mohamed Abouhawwash2,3, Hyung Ju Park4, Byeong-Gwon Kang4,*, Shubham Mahajan5, Amit Kant Pandit5
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 305-321, 2022, DOI:10.32604/cmc.2022.019171
    Abstract Location information plays an important role in most of the applications in Wireless Sensor Network (WSN). Recently, many localization techniques have been proposed, while most of these deals with two Dimensional applications. Whereas, in Three Dimensional applications the task is complex and there are large variations in the altitude levels. In these 3D environments, the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level. For such applications, 2D localization models are not reliable. Due to this, the design of 3D localization systems in WSNs faces new challenges. In this… More >

  • Open AccessOpen Access

    ARTICLE

    Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

    A. Prithiviraj1,*, A. Maheswari2, D. Balamurugan1, Vinayakumar Ravi3, Moez Krichen4,5, Roobaea Alroobaea6, Saeed Rubaiee7, Sankar Sennan1
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 323-341, 2022, DOI:10.32604/cmc.2022.015299
    (This article belongs to the Special Issue: Deep Learning Trends in Intelligent Systems)
    Abstract Despite the seemingly exponential growth of mobile and wireless communication, this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication, Bluetooth, and Wi-Fi to achieve better network connection which in turn gives the best quality of service (QoS). Many analysts have established many handover decision systems (HDS) to enable assured continuous mobility between various radio access technologies. Unbroken mobility is one of the most significant problems considered in wireless communication networks. Each application needs a distinct QoS, so the network choice may shift appropriately. To achieve this objective and to… More >

  • Open AccessOpen Access

    ARTICLE

    Human Gait Recognition: A Deep Learning and Best Feature Selection Framework

    Asif Mehmood1, Muhammad Attique Khan2, Usman Tariq3, Chang-Won Jeong4, Yunyoung Nam5,*, Reham R. Mostafa6, Amira ElZeiny7
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 343-360, 2022, DOI:10.32604/cmc.2022.019250
    (This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
    Abstract Background—Human Gait Recognition (HGR) is an approach based on biometric and is being widely used for surveillance. HGR is adopted by researchers for the past several decades. Several factors are there that affect the system performance such as the walking variation due to clothes, a person carrying some luggage, variations in the view angle. Proposed—In this work, a new method is introduced to overcome different problems of HGR. A hybrid method is proposed or efficient HGR using deep learning and selection of best features. Four major steps are involved in this work-preprocessing of the video frames,… More >

  • Open AccessOpen Access

    ARTICLE

    Utilization of Machine Learning Methods in Modeling Specific Heat Capacity of Nanofluids

    Mamdouh El Haj Assad1, Ibrahim Mahariq2, Raymond Ghandour2, Mohammad Alhuyi Nazari3, Thabet Abdeljawad4,5,6,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 361-374, 2022, DOI:10.32604/cmc.2022.019048
    (This article belongs to the Special Issue: Big Data Analytics and Artificial Intelligence Techniques for Complex Systems)
    Abstract Nanofluids are extensively applied in various heat transfer mediums for improving their heat transfer characteristics and hence their performance. Specific heat capacity of nanofluids, as one of the thermophysical properties, performs principal role in heat transfer of thermal mediums utilizing nanofluids. In this regard, different studies have been carried out to investigate the influential factors on nanofluids specific heat. Moreover, several regression models based on correlations or artificial intelligence have been developed for forecasting this property of nanofluids. In the current review paper, influential parameters on the specific heat capacity of nanofluids are introduced. Afterwards, More >

  • Open AccessOpen Access

    ARTICLE

    Improving Routine Immunization Coverage Through Optimally Designed Predictive Models

    Fareeha Sameen1, Abdul Momin Kazi2, Majida Kazmi1,*, Munir A Abbasi3, Saad Ahmed Qazi1,4, Lampros K Stergioulas3,5
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 375-395, 2022, DOI:10.32604/cmc.2022.019167
    Abstract Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive… More >

  • Open AccessOpen Access

    ARTICLE

    Optimization Model for Selecting Temporary Hospital Locations During COVID-19 Pandemic

    Chia-Nan Wang1, Chien-Chang Chou2,*, Hsien-Pin Hsu3, Van Thanh Nguyen4, Viet Tinh Nguyen4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 397-412, 2022, DOI:10.32604/cmc.2022.019470
    Abstract The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures. As such, the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic, especially in densely populated areas where the risk of transmission of the virus is highest. If the location selection process or the prioritization of measures is poor, healthcare workers and patients can be harmed,… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Semisupervised Learning-Based Network Anomaly Detection in Heterogeneous Information Systems

    Nazarii Lutsiv1, Taras Maksymyuk1,*, Mykola Beshley1, Orest Lavriv1, Volodymyr Andrushchak1, Anatoliy Sachenko2, Liberios Vokorokos3, Juraj Gazda3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 413-431, 2022, DOI:10.32604/cmc.2022.018773
    Abstract The extensive proliferation of modern information services and ubiquitous digitization of society have raised cybersecurity challenges to new levels. With the massive number of connected devices, opportunities for potential network attacks are nearly unlimited. An additional problem is that many low-cost devices are not equipped with effective security protection so that they are easily hacked and applied within a network of bots (botnet) to perform distributed denial of service (DDoS) attacks. In this paper, we propose a novel intrusion detection system (IDS) based on deep learning that aims to identify suspicious behavior in modern heterogeneous… More >

  • Open AccessOpen Access

    ARTICLE

    Isomorphic 2D/3D Objects and Saccadic Characteristics in Mental Rotation

    Akanksha Tiwari1, Ram Bilas Pachori1,2, Premjit Khanganba Sanjram1,3,4,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 433-450, 2022, DOI:10.32604/cmc.2022.019256
    (This article belongs to the Special Issue: Advanced signal acquisition and processing for Internet of Medical Things)
    Abstract Mental rotation (MR) is an important aspect of cognitive processing in gaming since transformation and manipulation of visuospatial information are necessary in order to execute a gaming task. This study provides insights on saccadic characteristics in gaming task performance that involves 2D and 3D isomorphic objects with varying angular disparity. Healthy participants (N =60) performed MR gaming task. Each participant was tested individually in an acoustic treated lab environment. Gaze behavior data of all participants were recorded during task execution and analyzed to find the changes in spatiotemporal characteristics of saccades associated with the variation in angular… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Approach for Analysis and Characterization of COVID-19

    Indrajeet Kumar1, Sultan S. Alshamrani2, Abhishek Kumar3, Jyoti Rawat4, Kamred Udham Singh1, Mamoon Rashid5,*, Ahmed Saeed AlGhamdi6
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 451-468, 2022, DOI:10.32604/cmc.2022.019443
    (This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
    Abstract Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more effectively. In a recent pandemic, laboratories perform diagnostics manually, which requires a lot of time and expertise of the laboratorial technicians to yield accurate results. Moreover, the cost of kits is high, and well-equipped labs are needed to perform this test. Therefore, other means of diagnosis is highly desirable. Radiography is one of the existing methods that finds its use in the diagnosis of COVID-19. The radiography observes change in… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Computational Modeling for Web Application Security Assessment

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Md Tarique Jamal Ansari1, Rajeev Kumar4,*, Mohammad Ubaidullah Bokhari5, Raees Ahmad Khan1
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 469-489, 2022, DOI:10.32604/cmc.2022.019593
    Abstract Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

    Hyun-Sun Hwang1, Jae-Hyun Ro2, Chan-Yeob Park1, Young-Hwan You3, Hyoung-Kyu Song1,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 491-504, 2022, DOI:10.32604/cmc.2022.019397
    Abstract A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output (MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is used. In this paper, the horizontal Gauss-Seidel (HGS) method is proposed as precoding scheme in massive MIMO systems. In massive MIMO systems, the exact inversion of channel matrix is impractical due to the severe computational complexity. Therefore, the conventional Gauss-Seidel (GS) method is used to approximate the inversion of channel matrix. The GS has good performance by More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator

    Summra Saleem1,2, M. Usman Ghani Khan1,2, Tanzila Saba3, Ibrahim Abunadi3, Amjad Rehman3,*, Saeed Ali Bahaj4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 505-521, 2022, DOI:10.32604/cmc.2022.018871
    Abstract Image translation plays a significant role in realistic image synthesis, entertainment tasks such as editing and colorization, and security including personal identification. In Edge GAN, the major contribution is attribute guided vector that enables high visual quality content generation. This research study proposes automatic face image realism from freehand sketches based on Edge GAN. We propose a density variant image synthesis model, allowing the input sketch to encompass face features with minute details. The density level is projected into non-latent space, having a linear controlled function parameter. This assists the user to appropriately devise the More >

  • Open AccessOpen Access

    ARTICLE

    Prediction of BRIC Stock Price Using ARIMA, SutteARIMA, and Holt-Winters

    Ansari Saleh Ahmar1, Pawan Kumar Singh2, Nguyen Van Thanh3,*, Nguyen Viet Tinh3, Vo Minh Hieu3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 523-534, 2022, DOI:10.32604/cmc.2022.017068
    (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 The novel coronavirus has played a disastrous role in many countries worldwide. The outbreak became a major epidemic, engulfing the entire world in lockdown and it is now speculated that its economic impact might be worse than economic deceleration and decline. This paper identifies two different models to capture the trend of closing stock prices in Brazil (BVSP), Russia (IMOEX.ME), India (BSESN), and China (SSE), i.e., (BRIC) countries. We predict the stock prices for three daily time periods, so appropriate preparations can be undertaken to solve these issues. First, we compared the ARIMA, SutteARIMA and… More >

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    ARTICLE

    Hemodynamic Response Detection Using Integrated EEG-fNIRS-VPA for BCI

    Arshia Arif1, M. Jawad Khan1,2,*, Kashif Javed1, Hasan Sajid1,2, Saddaf Rubab1, Noman Naseer3, Talha Irfan Khan4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 535-555, 2022, DOI:10.32604/cmc.2022.018318
    (This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
    Abstract For BCI systems, it is important to have an accurate and less complex architecture to control a device with enhanced accuracy. In this paper, a novel methodology for more accurate detection of the hemodynamic response has been developed using a multimodal brain-computer interface (BCI). An integrated classifier has been developed for achieving better classification accuracy using two modalities. An integrated EEG-fNIRS-based vector-phase analysis (VPA) has been conducted. An open-source dataset collected at the Technische Universität Berlin, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals of 26 healthy participants during n-back tests, has been… More >

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    ARTICLE

    BHGSO: Binary Hunger Games Search Optimization Algorithm for Feature Selection Problem

    R. Manjula Devi1, M. Premkumar2, Pradeep Jangir3, B. Santhosh Kumar4, Dalal Alrowaili5, Kottakkaran Sooppy Nisar6,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 557-579, 2022, DOI:10.32604/cmc.2022.019611
    Abstract In machine learning and data mining, feature selection (FS) is a traditional and complicated optimization problem. Since the run time increases exponentially, FS is treated as an NP-hard problem. The researcher’s effort to build a new FS solution was inspired by the ongoing need for an efficient FS framework and the success rates of swarming outcomes in different optimization scenarios. This paper presents two binary variants of a Hunger Games Search Optimization (HGSO) algorithm based on V- and S-shaped transfer functions within a wrapper FS model for choosing the best features from a large dataset.… More >

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    ARTICLE

    Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry

    Alamgir Safi1, Muhammad Asghar Khan2,*, Fahad Algarni3, Muhammad Adnan Aziz1, M. Irfan Uddin4, Insaf Ullah2, Tanweer Ahmad Cheema1
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 581-599, 2022, DOI:10.32604/cmc.2022.018963
    (This article belongs to the Special Issue: Advances in 5G Antenna Designs and Systems)
    Abstract Linear antenna arrays (LAs) can be used to accurately predict the direction of arrival (DOAs) of various targets of interest in a given area. However, under certain conditions, LA suffers from the problem of ambiguities among the angles of targets, which may result in misinterpretation of such targets. In order to cope up with such ambiguities, various techniques have been proposed. Unfortunately, none of them fully resolved such a problem because of rank deficiency and high computational cost. We aimed to resolve such a problem by proposing an algorithm using differential geometry. The proposed algorithm… More >

  • Open AccessOpen Access

    ARTICLE

    A Secure Communication Protocol for Unmanned Aerial Vehicles

    Navid Ali Khan1, N. Z. Jhanjhi1,*, Sarfraz Nawaz Brohi2, Abdulwahab Ali Almazroi3, Abdulaleem Ali Almazroi4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 601-618, 2022, DOI:10.32604/cmc.2022.019419
    Abstract Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial Vehicles. Multiple UAVs and autopilot systems support it, and it provides bi-directional communication between the UAV and Ground Control Station. The communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to GCS. In order to increase the transfer speed and efficiency, the Mavlink does not encrypt the messages. As a result, the protocol is vulnerable to various security attacks such as Eavesdropping, GPS Spoofing, and DDoS. In this study, we… More >

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    ARTICLE

    Fruits and Vegetable Diseases Recognition Using Convolutional Neural Networks

    Javaria Amin1, Muhammad Almas Anjum2, Muhammad Sharif3, Seifedine Kadry4, Yunyoung Nam5,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 619-635, 2022, DOI:10.32604/cmc.2022.018562
    (This article belongs to the Special Issue: Recent Advances in Deep Learning and Saliency Methods for Agriculture)
    Abstract As they have nutritional, therapeutic, so values, plants were regarded as important and they’re the main source of humankind’s energy supply. Plant pathogens will affect its leaves at a certain time during crop cultivation, leading to substantial harm to crop productivity & economic selling price. In the agriculture industry, the identification of fungal diseases plays a vital role. However, it requires immense labor, greater planning time, and extensive knowledge of plant pathogens. Computerized approaches are developed and tested by different researchers to classify plant disease identification, and that in many cases they have also had… More >

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    ARTICLE

    Defect Detection in Printed Circuit Boards with Pre-Trained Feature Extraction Methodology with Convolution Neural Networks

    Mohammed A. Alghassab*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 637-652, 2022, DOI:10.32604/cmc.2022.019527
    (This article belongs to the Special Issue: Emerging Trends in Artificial Intelligence and Machine Learning)
    Abstract Printed Circuit Boards (PCBs) are very important for proper functioning of any electronic device. PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs. If PCBs do not function properly then the whole electric machine might fail. So, keeping this in mind researchers are working in this field to develop error free PCBs. Initially these PCBs were examined by the human beings manually, but the human error did not give good results as sometime defected PCBs were categorized as non-defective. So, researchers and experts transformed this… More >

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    ARTICLE

    Towards Aspect Based Components Integration Framework for Cyber-Physical System

    Sadia Ali1, Yaser Hafeez1, Muhammad Bilal2, Saqib Saeed3, Kyung Sup Kwak4,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 653-668, 2022, DOI:10.32604/cmc.2022.018779
    Abstract Cyber-Physical Systems (CPS) comprise interactive computation, networking, and physical processes. The integrative environment of CPS enables the smart systems to be aware of the surrounding physical world. Smart systems, such as smart health care systems, smart homes, smart transportation, and smart cities, are made up of complex and dynamic CPS. The components integration development approach should be based on the divide and conquer theory. This way multiple interactive components can reduce the development complexity in CPS. As reusability enhances efficiency and consistency in CPS, encapsulation of component functionalities and a well-designed user interface is vital… More >

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    ARTICLE

    Integrating Deep Learning and Machine Translation for Understanding Unrefined Languages

    HongGeun Ji1,2, Soyoung Oh1, Jina Kim3, Seong Choi1,2, Eunil Park1,2,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 669-678, 2022, DOI:10.32604/cmc.2022.019521
    Abstract In the field of natural language processing (NLP), the advancement of neural machine translation has paved the way for cross-lingual research. Yet, most studies in NLP have evaluated the proposed language models on well-refined datasets. We investigate whether a machine translation approach is suitable for multilingual analysis of unrefined datasets, particularly, chat messages in Twitch. In order to address it, we collected the dataset, which included 7,066,854 and 3,365,569 chat messages from English and Korean streams, respectively. We employed several machine learning classifiers and neural networks with two different types of embedding: word-sequence embedding and the… More >

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    ARTICLE

    Design of an Information Security Service for Medical Artificial Intelligence

    Yanghoon Kim1, Jawon Kim2, Hangbae Chang3,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 679-694, 2022, DOI:10.32604/cmc.2022.015610
    (This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
    Abstract The medical convergence industry has gradually adopted ICT devices, which has led to legacy security problems related to ICT devices. However, it has been difficult to solve these problems due to data resource issues. Such problems can cause a lack of reliability in medical artificial intelligence services that utilize medical information. Therefore, to provide reliable services focused on security internalization, it is necessary to establish a medical convergence environment-oriented security management system. This study proposes the use of system identification and countermeasures to secure system reliability when using medical convergence environment information in medical artificial More >

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    ARTICLE

    Attention-Based and Time Series Models for Short-Term Forecasting of COVID-19 Spread

    Jurgita Markevičiūtė1,*, Jolita Bernatavičienė2, Rūta Levulienė1, Viktor Medvedev2, Povilas Treigys2, Julius Venskus2
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 695-714, 2022, DOI:10.32604/cmc.2022.018735
    Abstract The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide. The pandemic has brought much uncertainty to the global economy and the situation in general. Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics, which have negative impact on public health. The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions. To evaluate the effectiveness of the proposed attention-based method combining certain data mining… More >

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    ARTICLE

    Real-Time and Intelligent Flood Forecasting Using UAV-Assisted Wireless Sensor Network

    Shidrokh Goudarzi1,2,*, Seyed Ahmad Soleymani2,3, Mohammad Hossein Anisi4, Domenico Ciuonzo5, Nazri Kama6, Salwani Abdullah1, Mohammad Abdollahi Azgomi2, Zenon Chaczko7, Azri Azmi6
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 715-738, 2022, DOI:10.32604/cmc.2022.019550
    Abstract The Wireless Sensor Network (WSN) is a promising technology that could be used to monitor rivers’ water levels for early warning flood detection in the 5G context. However, during a flood, sensor nodes may be washed up or become faulty, which seriously affects network connectivity. To address this issue, Unmanned Aerial Vehicles (UAVs) could be integrated with WSN as routers or data mules to provide reliable data collection and flood prediction. In light of this, we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river levels. The framework is… More >

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    ARTICLE

    Droid-IoT: Detect Android IoT Malicious Applications Using ML and Blockchain

    Hani Mohammed Alshahrani*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 739-766, 2022, DOI:10.32604/cmc.2022.019623
    (This article belongs to the Special Issue: Emerging Trends in Artificial Intelligence and Machine Learning)
    Abstract One of the most rapidly growing areas in the last few years is the Internet of Things (IoT), which has been used in widespread fields such as healthcare, smart homes, and industries. Android is one of the most popular operating systems (OS) used by IoT devices for communication and data exchange. Android OS captured more than 70 percent of the market share in 2021. Because of the popularity of the Android OS, it has been targeted by cybercriminals who have introduced a number of issues, such as stealing private information. As reported by one of… More >

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    ARTICLE

    Comparison of Missing Data Imputation Methods in Time Series Forecasting

    Hyun Ahn1, Kyunghee Sun2, Kwanghoon Pio Kim3,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 767-779, 2022, DOI:10.32604/cmc.2022.019369
    Abstract Time series forecasting has become an important aspect of data analysis and has many real-world applications. However, undesirable missing values are often encountered, which may adversely affect many forecasting tasks. In this study, we evaluate and compare the effects of imputation methods for estimating missing values in a time series. Our approach does not include a simulation to generate pseudo-missing data, but instead perform imputation on actual missing data and measure the performance of the forecasting model created therefrom. In an experiment, therefore, several time series forecasting models are trained using different training datasets prepared More >

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    ARTICLE

    AI Cannot Understand Memes: Experiments with OCR and Facial Emotions

    Ishaani Priyadarshini*, Chase Cotton
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 781-800, 2022, DOI:10.32604/cmc.2022.019284
    Abstract

    The increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences,

    More >

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    ARTICLE

    Type II Fuzzy Logic Based Cluster Head Selection for Wireless Sensor Network

    J. Jean Justus1,*, M. Thirunavukkarasan2, K. Dhayalini3, G. Visalaxi4, Adel Khelifi5, Mohamed Elhoseny6,7
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 801-816, 2022, DOI:10.32604/cmc.2022.019122
    Abstract Wireless Sensor Network (WSN) forms an essential part of IoT. It is embedded in the target environment to observe the physical parameters based on the type of application. Sensor nodes in WSN are constrained by different features such as memory, bandwidth, energy, and its processing capabilities. In WSN, data transmission process consumes the maximum amount of energy than sensing and processing of the sensors. So, diverse clustering and data aggregation techniques are designed to achieve excellent energy efficiency in WSN. In this view, the current research article presents a novel Type II Fuzzy Logic-based Cluster… More >

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    ARTICLE

    An Artificial Intelligence Approach for Solving Stochastic Transportation Problems

    Prachi Agrawal1, Khalid Alnowibet2, Talari Ganesh1, Adel F. Alrasheedi2, Hijaz Ahmad3, Ali Wagdy Mohamed4,5,*
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.019685
    (This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water cycle algorithm (WCA), in the transportation problem. A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull distribution. Since the parameters are stochastic, the… More >

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    ARTICLE

    Utilization of HEVC ChaCha20-Based Selective Encryption for Secure Telehealth Video Conferencing

    Osama S. Faragallah1,*, Ahmed I. Sallam2, Hala S. El-sayed3
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 831-845, 2022, DOI:10.32604/cmc.2022.019151
    Abstract Coronavirus (COVID-19) is a contagious disease that causes exceptional effect on healthcare organizations worldwide with dangerous impact on medical services within the hospitals. Because of the fast spread of COVID-19, the healthcare facilities could be a big source of disease infection. So, healthcare video consultations should be used to decrease face-to-face communication between clinician and patients. Healthcare video consultations may be beneficial for some COVID-19 conditions and reduce the need for face-to-face contact with a potentially positive patient without symptoms. These conditions are like top clinicians who provide remote consultations to develop treatment methodology and… More >

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    ARTICLE

    Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

    Mohamed Abdel-Basset1, Ahmed Sleem1, Asmaa Atef1, Yunyoung Nam2,*, Mohamed Abouhawwash3,4
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 847-874, 2022, DOI:10.32604/cmc.2022.017106
    (This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)
    Abstract Project scheduling is a key objective of many models and is the proposed method for project planning and management. Project scheduling problems depend on precedence relationships and resource constraints, in addition to some other limitations for achieving a subset of goals. Project scheduling problems are dependent on many limitations, including limitations of precedence relationships, resource constraints, and some other limitations for achieving a subset of goals. Deterministic project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required, which are known and stable during… More >

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    ARTICLE

    Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

    Muhammad Reazul Haque1, Saw Chin Tan1, Zulfadzli Yusoff2,*, Kashif Nisar3,7, Rizaludin Kaspin4, Iram Haider3, Sana Nisar3, J. P. C. Rodrigues5,6, Bhawani Shankar Chowdhry7, Muhammad Aslam Uqaili7, Satya Prasad Majumder8, Danda B. Rawat9, Richard Etengu1, Rajkumar Buyya10
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 875-894, 2022, DOI:10.32604/cmc.2022.018505
    Abstract In the design and planning of next-generation Internet of Things (IoT), telecommunication, and satellite communication systems, controller placement is crucial in software-defined networking (SDN). The programmability of the SDN controller is sophisticated for the centralized control system of the entire network. Nevertheless, it creates a significant loophole for the manifestation of a distributed denial of service (DDoS) attack straightforwardly. Furthermore, recently a Distributed Reflected Denial of Service (DRDoS) attack, an unusual DDoS attack, has been detected. However, minimal deliberation has given to this forthcoming single point of SDN infrastructure failure problem. Moreover, recently the high More >

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