Home / Journals / CMC / Vol.71, No.3, 2022
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  • Open AccessOpen Access

    ARTICLE

    AMDnet: An Academic Misconduct Detection Method for Authors’ Behaviors

    Shihao Zhou1, Ziyuan Xu3,4, Jin Han1,*, Xingming Sun1,2, Yi Cao5
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5995-6009, 2022, DOI:10.32604/cmc.2022.023316
    Abstract In recent years, academic misconduct has been frequently exposed by the media, with serious impacts on the academic community. Current research on academic misconduct focuses mainly on detecting plagiarism in article content through the application of character-based and non-text element detection techniques over the entirety of a manuscript. For the most part, these techniques can only detect cases of textual plagiarism, which means that potential culprits can easily avoid discovery through clever editing and alterations of text content. In this paper, we propose an academic misconduct detection method based on scholars’ submission behaviors. The model can effectively capture the atypical… More >

  • Open AccessOpen Access

    ARTICLE

    Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

    Ahmed Saeed Alfakeeh1, Abdulmohsen Almalawi2, Fawaz Jaber Alsolami2, Yoosef B. Abushark2, Asif Irshad Khan2,*, Adel Aboud S. Bahaddad1, Md Mottahir Alam3, Alka Agrawal4, Rajeev Kumar5, Raees Ahmad Khan4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6011-6037, 2022, DOI:10.32604/cmc.2022.024903
    (This article belongs to this Special Issue: Advances in Artificial Intelligence and Machine learning in Biomedical and Healthcare Informatics)
    Abstract The current cyber-attack environment has put even the most protected systems at risk as the hackers are now modifying technologies to exploit even the tiniest of weaknesses and infiltrate networks. In this situation, it's critical to design and construct software that is both secure and long-lasting. While security is the most well-defined aspect of health information software systems, it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same time. In this league, it is crucial to determine those characteristics in… More >

  • Open AccessOpen Access

    ARTICLE

    Reinforced CNN Forensic Discriminator to Detect Document Forgery by DCGAN

    Seo-young Lim, Jeongho Cho*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6039-6051, 2022, DOI:10.32604/cmc.2022.024862
    Abstract Recently, the technology of digital image forgery based on a generative adversarial network (GAN) has considerably improved to the extent that it is difficult to distinguish it from the original image with the naked eye by compositing and editing a person's face or a specific part with the original image. Thus, much attention has been paid to digital image forgery as a social issue. Further, document forgery through GANs can completely change the meaning and context in a document, and it is difficult to identify whether the document is forged or not, which is dangerous. Nonetheless, few studies have been… More >

  • Open AccessOpen Access

    ARTICLE

    An Optimized Convolution Neural Network Architecture for Paddy Disease Classification

    Muhammad Asif Saleem1, Muhammad Aamir1,2, * ,*, Rosziati Ibrahim1, Norhalina Senan1, Tahir Alyas3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6053-6067, 2022, DOI:10.32604/cmc.2022.022215
    (This article belongs to this Special Issue: Application of Machine-Learning in Computer Vision)
    Abstract Plant disease classification based on digital pictures is challenging. Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize, identify, and diagnose plant diseases in the previous decade. Increasing the yield quantity and quality of rice forming is an important cause for the paddy production countries. However, some diseases that are blocking the improvement in paddy production are considered as an ominous threat. Convolution Neural Network (CNN) has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing era of science and technology.… More >

  • Open AccessOpen Access

    ARTICLE

    Low-Cost Flexible Graphite Monopole Patch Antenna for Wireless Communication Applications

    Suwat Sakulchat1, Amnoiy Ruengwaree1,*, Voranuch Thongpool2, Watcharaphon Naktong3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6069-6088, 2022, DOI:10.32604/cmc.2022.024050
    (This article belongs to this Special Issue: Advances in 5G Antenna Designs and Systems)
    Abstract This research investigates a monopole patch antenna for Wi-Fi applications at 2.45 and 5.2 GHz, and WiMax at 3.5 GHz. A low-cost and flexible graphite sheet with good conductivity, base on graphite conductive powder and glue is used to create a radiator patch and ground plane. Instead of commercially available conductive inks or graphite sheets, we use our self-produced graphite liquid to create the graphite sheet because it is easy to produce and inexpensive. The antenna structure is formed using a low-cost and easy hand-screen printing approach that involved placing graphite liquid on a bendable polyester substrate. This research focuses… More >

  • Open AccessOpen Access

    ARTICLE

    A Hybrid Meta-Classifier of Fuzzy Clustering and Logistic Regression for Diabetes Prediction

    Altyeb Altaher Taha*, Sharaf Jameel Malebary
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6089-6105, 2022, DOI:10.32604/cmc.2022.023848
    Abstract Diabetes is a chronic health condition that impairs the body's ability to convert food to energy, recognized by persistently high levels of blood glucose. Undiagnosed diabetes can cause many complications, including retinopathy, nephropathy, neuropathy, and other vascular disorders. Machine learning methods can be very useful for disease identification, prediction, and treatment. This paper proposes a new ensemble learning approach for type 2 diabetes prediction based on a hybrid meta-classifier of fuzzy clustering and logistic regression. The proposed approach consists of two levels. First, a base-learner comprising six machine learning algorithms is utilized for predicting diabetes. Second, a hybrid meta-learner that… More >

  • Open AccessOpen Access

    ARTICLE

    Estimator-Based GPS Attitude and Angular Velocity Determination

    Dah-Jing Jwo*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6107-6124, 2022, DOI:10.32604/cmc.2022.024722
    Abstract In this paper, the estimator-based Global Positioning System (GPS) attitude and angular velocity determination is presented. Outputs of the attitude estimator include the attitude angles and attitude rates or body angular velocities, depending on the design of estimator. Traditionally as a position, velocity and time sensor, the GPS also offers a free attitude-determination interferometer. GPS research and applications to the field of attitude determination using carrier phase or Doppler measurement has been extensively conducted. The raw attitude solution using the interferometry technique based on the least-squares approach is inherently noisy. The estimator such as the Kalman filter (KF) or extended… More >

  • Open AccessOpen Access

    ARTICLE

    A Provably Secure and Efficient Remote Password Authentication Scheme Using Smart Cards

    Fairuz Shohaimay1,2, Eddie Shahril Ismail1,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6125-6145, 2022, DOI:10.32604/cmc.2022.022759
    Abstract Communication technology has advanced dramatically amid the 21st century, increasing the security risk in safeguarding sensitive information. The remote password authentication (RPA) scheme is the simplest cryptosystem that serves as the first line of defence against unauthorised entity attacks. Although the literature contains numerous RPA schemes, to the best of the authors’ knowledge, only few schemes based on the integer factorisation problem (IFP) and the discrete logarithm problem (DLP) that provided a provision for session key agreement to ensure proper mutual authentication. Furthermore, none of the previous schemes provided formal security proof using the random oracle model. Therefore, this study… More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Resource Allocation in Fog Computing for Healthcare Applications

    Salman Khan1,*, Ibrar Ali Shah1, Nasser Tairan2, Habib Shah2, Muhammad Faisal Nadeem3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6147-6163, 2022, DOI:10.32604/cmc.2022.023234
    (This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
    Abstract In recent years, the significant growth in the Internet of Things (IoT) technology has brought a lot of attention to information and communication industry. Various IoT paradigms like the Internet of Vehicle Things (IoVT) and the Internet of Health Things (IoHT) create massive volumes of data every day which consume a lot of bandwidth and storage. However, to process such large volumes of data, the existing cloud computing platforms offer limited resources due to their distance from IoT devices. Consequently, cloud-computing systems produce intolerable latency problems for latency-sensitive real-time applications. Therefore, a new paradigm called fog computing makes use of… More >

  • Open AccessOpen Access

    ARTICLE

    Accurate Location Estimation of Smart Dusts Using Machine Learning

    Shariq Bashir1,*, Owais Ahmed Malik2, Daphne Teck Ching Lai2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6165-6181, 2022, DOI:10.32604/cmc.2022.024269
    (This article belongs to this Special Issue: Emergent Computer-Based Methods and Internet of Things Technologies for Physical Therapy, Dentistry, Medicine, and Engineering)
    Abstract Traditional wireless sensor networks (WSNs) are not suitable for rough terrains that are difficult or impossible to access by humans. Smart dust is a technology that works with the combination of many tiny sensors which is highly useful for obtaining remote sensing information from rough terrains. The tiny sensors are sprinkled in large numbers on rough terrains using airborne distribution through drones or aircraft without manually setting their locations. Although it is clear that a number of remote sensing applications can benefit from this technology, but the small size of smart dust fundamentally restricts the integration of advanced hardware on… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Energy Storage to Control and Optimize Electric Propulsion Systems

    Sikander Hans1, Smarajit Ghosh1, Suman Bhullar1, Aman Kataria2, Vinod Karar2,*, Divya Agrawal2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6183-6200, 2022, DOI:10.32604/cmc.2022.020768
    Abstract Today, ship development has concentrated on electrifying ships in commercial and military applications to improve efficiency, support high-power missile systems and reduce emissions. However, the electric propulsion of the shipboard system experiences torque fluctuation, thrust, and power due to the rotation of the propeller shaft and the motion of waves. In order to meet these challenges, a new solution is needed. This paper explores hybrid energy management systems using the battery and ultracapacitor to control and optimize the electric propulsion system. The battery type and ultracapacitor are ZEBRA and MAXWELL, respectively. The 3-, 4-and 5-blade propellers are considered to produce… More >

  • Open AccessOpen Access

    ARTICLE

    Content Feature Extraction-based Hybrid Recommendation for Mobile Application Services

    Chao Ma1,*, Yinggang Sun1, Zhenguo Yang1, Hai Huang1, Dongyang Zhan2,3, Jiaxing Qu4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6201-6217, 2022, DOI:10.32604/cmc.2022.022717
    Abstract The number of mobile application services is showing an explosive growth trend, which makes it difficult for users to determine which ones are of interest. Especially, the new mobile application services are emerge continuously, most of them have not be rated when they need to be recommended to users. This is the typical problem of cold start in the field of collaborative filtering recommendation. This problem may makes it difficult for users to locate and acquire the services that they actually want, and the accuracy and novelty of service recommendations are also difficult to satisfy users. To solve this problem,… More >

  • Open AccessOpen Access

    ARTICLE

    IoMT Enabled Melanoma Detection Using Improved Region Growing Lesion Boundary Extraction

    Tanzila Saba1, Rabia Javed2,3, Mohd Shafry Mohd Rahim2, Amjad Rehman1,*, Saeed Ali Bahaj4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6219-6237, 2022, DOI:10.32604/cmc.2022.020865
    (This article belongs to this Special Issue: Pervasive Computing and Communication: Challenges, Technologies & Opportunities)
    Abstract The Internet of Medical Things (IoMT) and cloud-based healthcare applications, services are beneficial for better decision-making in recent years. Melanoma is a deadly cancer with a higher mortality rate than other skin cancer types such as basal cell, squamous cell, and Merkel cell. However, detection and treatment at an early stage can result in a higher chance of survival. The classical methods of detection are expensive and labor-intensive. Also, they rely on a trained practitioner's level, and the availability of the needed equipment is essential for the early detection of Melanoma. The current improvement in computer-aided systems is providing very… More >

  • Open AccessOpen Access

    ARTICLE

    Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

    Anshul Sharma1, Divneet Singh Kapoor1, Anand Nayyar2,3,*, Basit Qureshi4, Kiran Jot Singh1, Khushal Thakur1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6239-6256, 2022, DOI:10.32604/cmc.2022.024639
    Abstract The simultaneous advances in the Internet of Things (IoT), Artificial intelligence (AI) and Robotics is going to revolutionize our world in the near future. In recent years, LoRa (Long Range) wireless powered by LoRaWAN (LoRa Wide Area Network) protocol has attracted the attention of researchers for numerous applications in the IoT domain. LoRa is a low power, unlicensed Industrial, Scientific, and Medical (ISM) band-equipped wireless technology that utilizes a wide area network protocol, i.e., LoRaWAN, to incorporate itself into the network infrastructure. In this paper, we have evaluated the LoRaWAN communication protocol for the implementation of the IoT (Internet of Things)… More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Hybrid Feature Extraction with Deep Learning for COVID-19 Classifications

    Majdy M. Eltahir1, Ibrahim Abunadi2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5, Adil Yousif6, Abdelwahed Motwakel5, Mesfer Al Duhayyim7, Manar Ahmed Hamza5,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6257-6273, 2022, DOI:10.32604/cmc.2022.024312
    Abstract Novel coronavirus 2019 (COVID-19) has affected the people's health, their lifestyle and economical status across the globe. The application of advanced Artificial Intelligence (AI) methods in combination with radiological imaging is useful in accurate detection of the disease. It also assists the physicians to take care of remote villages too. The current research paper proposes a novel automated COVID-19 analysis method with the help of Optimal Hybrid Feature Extraction (OHFE) and Optimal Deep Neural Network (ODNN) called OHFE-ODNN from chest x-ray images. The objective of the presented technique is for performing binary and multi-class classification of COVID-19 analysis from chest… More >

  • Open AccessOpen Access

    ARTICLE

    Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

    Riad Alharbey1, Ameen Banjar1, Yahia Said2,3,*, Mohamed Atri4, Abdulrahman Alshdadi1, Mohamed Abid5
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272
    Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number of existing visitors and face… More >

  • Open AccessOpen Access

    ARTICLE

    A Secure Three-Party Authenticated Key Exchange Protocol for Social Networks

    Vivek Kumar Sinha1, Divya Anand1,*, Fahd S. Alharithi2, Ahmed H. Almulihi2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6293-6305, 2022, DOI:10.32604/cmc.2022.024877
    Abstract The 3PAKE (Three-Party Authenticated Key Exchange) protocol is a valuable cryptographic method that offers safe communication and permits two diverse parties to consent to a new safe meeting code using the trusted server. There have been explored numerous 3PAKE protocols earlier to create a protected meeting code between users employing the trusted server. However, existing modified 3PAKE protocols have numerous drawbacks and are incapable to provide desired secrecy against diverse attacks such as man-in-the-middle, brute-force attacks, and many others in social networks. In this article, the authors proposed an improved as well as safe 3PAKE protocol based on the hash… More >

  • Open AccessOpen Access

    ARTICLE

    Coronavirus Detection Using Two Step-AS Clustering and Ensemble Neural Network Model

    Ahmed Hamza Osman*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6307-6331, 2022, DOI:10.32604/cmc.2022.024145
    Abstract This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical applications. The proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chest X-ray images through Two Step-As clustering algorithm with rich filter families, abstraction and weight-sharing properties. In contrast to the generally used transformational learning approach, the proposed model was trained before and after clustering. The compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to each new group, with each… More >

  • Open AccessOpen Access

    ARTICLE

    Rainfall Forecasting Using Machine Learning Algorithms for Localized Events

    Ganapathy Pattukandan Ganapathy1, Kathiravan Srinivasan2, Debajit Datta2, Chuan-Yu Chang3,4,*, Om Purohit5, Vladislav Zaalishvili6, Olga Burdzieva6
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6333-6350, 2022, DOI:10.32604/cmc.2022.023254
    Abstract A substantial amount of the Indian economy depends solely on agriculture. Rainfall, on the other hand, plays a significant role in agriculture–while an adequate amount of rainfall can be considered as a blessing, if the amount is inordinate or scant, it can ruin the entire hard work of the farmers. In this work, the rainfall dataset of the Vellore region, of Tamil Nadu, India, in the years 2021 and 2022 is forecasted using several machine learning algorithms. Feature engineering has been performed in this work in order to generate new features that remove all sorts of autocorrelation present in the… More >

  • Open AccessOpen Access

    ARTICLE

    Echo Location Based Bat Algorithm for Energy Efficient WSN Routing

    Anwer Mustafa Hilal1,*, Siwar Ben Haj Hassine2, Jaber S. Alzahrani3, Masoud Alajmi4, Fahd N. Al-Wesabi2,5, Mesfer Al Duhayyim6, Ishfaq Yaseen1, Abdelwahed Motwakel1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6351-6364, 2022, DOI:10.32604/cmc.2022.024489
    Abstract Due to the wide range of applications, Wireless Sensor Networks (WSN) are increased in day to day life and becomes popular. WSN has marked its importance in both practical and research domains. Energy is the most significant resource, the important challenge in WSN is to extend its lifetime. The energy reduction is a key to extend the network's lifetime. Clustering of sensor nodes is one of the well-known and proved methods for achieving scalable and energy conserving WSN. In this paper, an energy efficient protocol is proposed using metaheuristic Echo location-based BAT algorithm (ECHO-BAT). ECHO-BAT works in two stages. First… More >

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