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  • Open Access

    ARTICLE

    Soft Computing Based Metaheuristic Algorithms for Resource Management in Edge Computing Environment

    Nawaf Alhebaishi1, Abdulrhman M. Alshareef1, Tawfiq Hasanin1, Raed Alsini1, Gyanendra Prasad Joshi2, Seongsoo Cho3, Doo Ill Chul4,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5233-5250, 2022, DOI:10.32604/cmc.2022.025596 - 21 April 2022

    Abstract In recent times, internet of things (IoT) applications on the cloud might not be the effective solution for every IoT scenario, particularly for time sensitive applications. A significant alternative to use is edge computing that resolves the problem of requiring high bandwidth by end devices. Edge computing is considered a method of forwarding the processing and communication resources in the cloud towards the edge. One of the considerations of the edge computing environment is resource management that involves resource scheduling, load balancing, task scheduling, and quality of service (QoS) to accomplish improved performance. With this… More >

  • Open Access

    ARTICLE

    Intelligent Deep Transfer Learning Based Malaria Parasite Detection and Classification Model Using Biomedical Image

    Ahmad Alassaf, Mohamed Yacin Sikkandar*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5273-5285, 2022, DOI:10.32604/cmc.2022.025577 - 21 April 2022

    Abstract Malaria is a severe disease caused by Plasmodium parasites, which can be detected through blood smear images. The early identification of the disease can effectively reduce the severity rate. Deep learning (DL) models can be widely employed to analyze biomedical images, thereby minimizing the misclassification rate. With this objective, this study developed an intelligent deep-transfer-learning-based malaria parasite detection and classification (IDTL-MPDC) model on blood smear images. The proposed IDTL-MPDC technique aims to effectively determine the presence of malarial parasites in blood smear images. In addition, the IDTL-MPDC technique derives median filtering (MF) as a pre-processing… More >

  • Open Access

    ARTICLE

    Arabic Music Genre Classification Using Deep Convolutional Neural Networks (CNNs)

    Laiali Almazaydeh1,*, Saleh Atiewi2, Arar Al Tawil3, Khaled Elleithy4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5443-5458, 2022, DOI:10.32604/cmc.2022.025526 - 21 April 2022

    Abstract Genres are one of the key features that categorize music based on specific series of patterns. However, the Arabic music content on the web is poorly defined into its genres, making the automatic classification of Arabic audio genres challenging. For this reason, in this research, our objective is first to construct a well-annotated dataset of five of the most well-known Arabic music genres, which are: Eastern Takht, Rai, Muwashshah, the poem, and Mawwal, and finally present a comprehensive empirical comparison of deep Convolutional Neural Networks (CNNs) architectures on Arabic music genres classification. In this work, More >

  • Open Access

    ARTICLE

    A Hybrid System for Customer Churn Prediction and Retention Analysis via Supervised Learning

    Soban Arshad1, Khalid Iqbal1,*, Sheneela Naz2, Sadaf Yasmin1, Zobia Rehman2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4283-4301, 2022, DOI:10.32604/cmc.2022.025442 - 21 April 2022

    Abstract Telecom industry relies on churn prediction models to retain their customers. These prediction models help in precise and right time recognition of future switching by a group of customers to other service providers. Retention not only contributes to the profit of an organization, but it is also important for upholding a position in the competitive market. In the past, numerous churn prediction models have been proposed, but the current models have a number of flaws that prevent them from being used in real-world large-scale telecom datasets. These schemes, fail to incorporate frequently changing requirements. Data… More >

  • Open Access

    ARTICLE

    A Method for Detecting Non-Mask Wearers Based on Regression Analysis

    Dokyung Hwang1, Hyeonmin Ro1, Naejoung Kwak2, Jinsang Hwang3, Dongju Kim1,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378 - 21 April 2022

    Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important… More >

  • Open Access

    ARTICLE

    Impact Analysis of Resilience Against Malicious Code Attacks via Emails

    Chulwon Lee1, Kyungho Lee2,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4803-4816, 2022, DOI:10.32604/cmc.2022.025310 - 21 April 2022

    Abstract The damage caused by malicious software is increasing owing to the COVID-19 pandemic, such as ransomware attacks on information technology and operational technology systems based on corporate networks and social infrastructures and spear-phishing attacks on business or research institutes. Recently, several studies have been conducted to prevent further phishing emails in the workplace because malware attacks employ emails as the primary means of penetration. However, according to the latest research, there appears to be a limitation in blocking email spoofing through advanced blocking systems such as spam email filtering solutions and advanced persistent threat systems.… More >

  • Open Access

    ARTICLE

    An Adaptive Real-Time Third Order Sliding Mode Control for Nonlinear Systems

    Ahmed M. Elmogy1,2,*, Amany Sarhan2, Wael M. Elawady2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5629-5641, 2022, DOI:10.32604/cmc.2022.025247 - 21 April 2022

    Abstract As most real world systems are significantly nonlinear in nature, developing robust controllers have attracted many researchers for decades. Robust controllers are the controllers that are able to cope with the inherent uncertainties of the nonlinear systems. Many control methods have been developed for this purpose. Sliding mode control (SMC) is one of the most commonly used methods in developing robust controllers. This paper presents a higher order SMC (HOSMC) approach to mitigate the chattering problem of the traditional SMC techniques. The developed approach combines a third order SMC with an adaptive PID (proportional, integral, More >

  • Open Access

    ARTICLE

    Fault Tolerance in the Joint EDF-RMS Algorithm: A Comparative Simulation Study

    Rashmi Sharma1, Nitin Nitin2, Deepak Dahiya3,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5197-5213, 2022, DOI:10.32604/cmc.2022.025059 - 21 April 2022

    Abstract Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration. In Real-Time Systems (RTS), deadline is the key to successful completion of the program. If tasks effectively meet the deadline, it means the system is working in pristine order. However, missing the deadline means a systemic fault due to which the system can crash (hard RTS) or degrade inclusive performance (soft RTS). To fine-tune the RTS, tolerance is the critical issue and must be handled with extreme care. This article explains the context of fault tolerance with… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Control Using 3D Hand Gestures

    Fawad Salam Khan1,4, Mohd Norzali Haji Mohd1,*, Saiful Azrin B. M. Zulkifli2, Ghulam E Mustafa Abro2, Suhail Kazi3, Dur Muhammad Soomro1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5741-5759, 2022, DOI:10.32604/cmc.2022.024927 - 21 April 2022

    Abstract The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades. Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle (UAV) required maximum accuracy. In this paper, we designed a hybrid framework, which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures. The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient (DDPG) to receive… More >

  • Open Access

    ARTICLE

    Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

    Saman Riaz1, Ali Arshad2, Shahab S. Band3,*, Amir Mosavi4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819 - 21 April 2022

    Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by… More >

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