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  • Open Access

    ARTICLE

    Battle Royale Optimization-Based Resource Scheduling Scheme for Cloud Computing Environment

    Lenin Babu Russeliah1,*, R. Adaline Suji2, D. Bright Anand3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3925-3938, 2023, DOI:10.32604/csse.2023.034727

    Abstract Cloud computing (CC) is developing as a powerful and flexible computational structure for providing ubiquitous service to users. It receives interrelated software and hardware resources in an integrated manner distinct from the classical computational environment. The variation of software and hardware resources were combined and composed as a resource pool. The software no more resided in the single hardware environment, it can be executed on the schedule of resource pools to optimize resource consumption. Optimizing energy consumption in CC environments is the question that allows utilizing several energy conservation approaches for effective resource allocation. This study introduces a Battle Royale… More >

  • Open Access

    ARTICLE

    Optimal Deep Hybrid Boltzmann Machine Based Arabic Corpus Classification Model

    Mesfer Al Duhayyim1,*, Badriyya B. Al-onazi2, Mohamed K. Nour3, Ayman Yafoz4, Amal S. Mehanna5, Ishfaq Yaseen6, Amgad Atta Abdelmageed6, Gouse Pasha Mohammed6

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2755-2772, 2023, DOI:10.32604/csse.2023.034609

    Abstract Natural Language Processing (NLP) for the Arabic language has gained much significance in recent years. The most commonly-utilized NLP task is the ‘Text Classification’ process. Its main intention is to apply the Machine Learning (ML) approaches for automatically classifying the textual files into one or more pre-defined categories. In ML approaches, the first and foremost crucial step is identifying an appropriate large dataset to test and train the method. One of the trending ML techniques, i.e., Deep Learning (DL) technique needs huge volumes of different types of datasets for training to yield the best outcomes. The current study designs a… More >

  • Open Access

    ARTICLE

    Intelligent Sound-Based Early Fault Detection System for Vehicles

    Fawad Nasim1,2,*, Sohail Masood1,2, Arfan Jaffar1,2, Usman Ahmad1, Muhammad Rashid3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3175-3190, 2023, DOI:10.32604/csse.2023.034550

    Abstract An intelligent sound-based early fault detection system has been proposed for vehicles using machine learning. The system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the car. Early detection and correction of defects can improve the efficiency and life of the engine and other mechanical parts. The system uses a microphone to capture the sound emitted by the vehicle and a machine-learning algorithm to analyze the sound and detect faults. A possible fault is determined in the vehicle based on this processed sound. Binary classification is done at the first stage… More >

  • Open Access

    ARTICLE

    Reliable Failure Restoration with Bayesian Congestion Aware for Software Defined Networks

    Babangida Isyaku1,2,*, Kamalrulnizam Bin Abu Bakar1, Wamda Nagmeldin3, Abdelzahir Abdelmaboud4, Faisal Saeed5,6, Fuad A. Ghaleb1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3729-3748, 2023, DOI:10.32604/csse.2023.034509

    Abstract Software Defined Networks (SDN) introduced better network management by decoupling control and data plane. However, communication reliability is the desired property in computer networks. The frequency of communication link failure degrades network performance, and service disruptions are likely to occur. Emerging network applications, such as delay-sensitive applications, suffer packet loss with higher Round Trip Time (RTT). Several failure recovery schemes have been proposed to address link failure recovery issues in SDN. However, these schemes have various weaknesses, which may not always guarantee service availability. Communication paths differ in their roles; some paths are critical because of the higher frequency usage.… More >

  • Open Access

    ARTICLE

    Automated Spam Review Detection Using Hybrid Deep Learning on Arabic Opinions

    Ibrahim M. Alwayle1, Badriyya B. Al-onazi2, Mohamed K. Nour3, Khaled M. Alalayah1, Khadija M. Alaidarous1, Ibrahim Abdulrab Ahmed4, Amal S. Mehanna5, Abdelwahed Motwakel6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2947-2961, 2023, DOI:10.32604/csse.2023.034456

    Abstract Online reviews regarding purchasing services or products offered are the main source of users’ opinions. To gain fame or profit, generally, spam reviews are written to demote or promote certain targeted products or services. This practice is called review spamming. During the last few years, various techniques have been recommended to solve the problem of spam reviews. Previous spam detection study focuses on English reviews, with a lesser interest in other languages. Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced. Thus, this study develops an Automated Spam Review Detection using… More >

  • Open Access

    ARTICLE

    Covid-19 Detection Using Deep Correlation-Grey Wolf Optimizer

    K. S. Bhuvaneshwari1, Ahmed Najat Ahmed2, Mehedi Masud3, Samah H. Alajmani4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2933-2945, 2023, DOI:10.32604/csse.2023.034288

    Abstract The immediate and quick spread of the coronavirus has become a life-threatening disease around the globe. The widespread illness has dramatically changed almost all sectors, moving from offline to online, resulting in a new normal lifestyle for people. The impact of coronavirus is tremendous in the healthcare sector, which has experienced a decline in the first quarter of 2020. This pandemic has created an urge to use computer-aided diagnosis techniques for classifying the Covid-19 dataset to reduce the burden of clinical results. The current situation motivated me to choose correlation-based development called correlation-based grey wolf optimizer to perform accurate classification.… More >

  • Open Access

    ARTICLE

    Enhancing the Adversarial Transferability with Channel Decomposition

    Bin Lin1, Fei Gao2, Wenli Zeng3,*, Jixin Chen4, Cong Zhang5, Qinsheng Zhu6, Yong Zhou4, Desheng Zheng4, Qian Qiu7,5, Shan Yang8

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3075-3085, 2023, DOI:10.32604/csse.2023.034268

    Abstract The current adversarial attacks against deep learning models have achieved incredible success in the white-box scenario. However, they often exhibit weak transferability in the black-box scenario, especially when attacking those with defense mechanisms. In this work, we propose a new transfer-based black-box attack called the channel decomposition attack method (CDAM). It can attack multiple black-box models by enhancing the transferability of the adversarial examples. On the one hand, it tunes the gradient and stabilizes the update direction by decomposing the channels of the input example and calculating the aggregate gradient. On the other hand, it helps to escape from local… More >

  • Open Access

    ARTICLE

    Remote Sensing Image Encryption Using Optimal Key Generation-Based Chaotic Encryption

    Mesfer Al Duhayyim1,*, Fatma S. Alrayes2, Saud S. Alotaibi3, Sana Alazwari4, Nasser Allheeib5, Ayman Yafoz6, Raed Alsini6, Amira Sayed A. Aziz7

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3209-3223, 2023, DOI:10.32604/csse.2023.034185

    Abstract The Internet of Things (IoT) offers a new era of connectivity, which goes beyond laptops and smart connected devices for connected vehicles, smart homes, smart cities, and connected healthcare. The massive quantity of data gathered from numerous IoT devices poses security and privacy concerns for users. With the increasing use of multimedia in communications, the content security of remote-sensing images attracted much attention in academia and industry. Image encryption is important for securing remote sensing images in the IoT environment. Recently, researchers have introduced plenty of algorithms for encrypting images. This study introduces an Improved Sine Cosine Algorithm with Chaotic… More >

  • Open Access

    ARTICLE

    Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection

    Khaled M. Alalayah1, Fatma S. Alrayes2, Mohamed K. Nour3, Khadija M. Alaidarous1, Ibrahim M. Alwayle1, Heba Mohsen4, Ibrahim Abdulrab Ahmed5, Mesfer Al Duhayyim6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3103-3119, 2023, DOI:10.32604/csse.2023.034034

    Abstract Malware is a ‘malicious software program that performs multiple cyberattacks on the Internet, involving fraud, scams, nation-state cyberwar, and cybercrime. Such malicious software programs come under different classifications, namely Trojans, viruses, spyware, worms, ransomware, Rootkit, botnet malware, etc. Ransomware is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it; then, the user pays a ransom procedure of a sum of money. To prevent detection, various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine… More >

  • Open Access

    ARTICLE

    Improvements in Weather Forecasting Technique Using Cognitive Internet of Things

    Kaushlendra Yadav*, Anuj Singh, Arvind Kumar Tiwari

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3767-3782, 2023, DOI:10.32604/csse.2023.033991

    Abstract Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate. However, effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and technology. The primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any damage. Currently, most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the atmosphere. In this work, sensors are used to collect real-time data for a particular location to capture the… More >

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