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  • Open Access

    ARTICLE

    Solving the Generalized Traveling Salesman Problem Using Sequential Constructive Crossover Operator in Genetic Algorithm

    Zakir Hussain Ahmed1,*, Maha Ata Al-Furhood2, Abdul Khader Jilani Saudagar3, Shakir Khan4
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.053574
    (This article belongs to the Special Issue: Metaheuristics Optimization for Real-World Applications)
    Abstract The generalized travelling salesman problem (GTSP), a generalization of the well-known travelling salesman problem (TSP), is considered for our study. Since the GTSP is NP-hard and very complex, finding exact solutions is highly expensive, we will develop genetic algorithms (GAs) to obtain heuristic solutions to the problem. In GAs, as the crossover is a very important process, the crossover methods proposed for the traditional TSP could be adapted for the GTSP. The sequential constructive crossover (SCX) and three other operators are adapted to use in GAs to solve the GTSP. The effectiveness of GA using More >

  • Open Access

    ARTICLE

    Reducing the Encrypted Data Size: Healthcare with IoT-Cloud Computing Applications

    Romaissa Kebache1, Abdelkader Laouid1,*, Ahcene Bounceur2, Mostefa Kara1,3, Konstantinos Karampidis4, Giorgos Papadourakis4, Mohammad Hammoudeh2
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.048738
    (This article belongs to the Special Issue: Explainable AI and Cybersecurity Techniques for IoT-Based Medical and Healthcare Applications)
    Abstract Internet cloud services come at a price, especially when they provide top-tier security measures. The cost incurred by cloud utilization is directly proportional to the storage requirements. Companies are always looking to increase profits and reduce costs while preserving the security of their data by encrypting them. One of the offered solutions is to find an efficient encryption method that can store data in a much smaller space than traditional encryption techniques. This article introduces a novel encryption approach centered on consolidating information into a single ciphertext by implementing Multi-Key Embedded Encryption (MKEE). The effectiveness… More >

  • Open Access

    REVIEW

    IoMT-Based Healthcare Systems: A Review

    Tahir Abbas1,*, Ali Haider Khan2, Khadija Kanwal3, Ali Daud4,*, Muhammad Irfan5, Amal Bukhari6, Riad Alharbey6
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.049026
    (This article belongs to the Special Issue: Advanced Architecture of Fog Computing in Real-Time IoT Devices)
    Abstract The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The More >

  • Open Access

    ARTICLE

    Unleashing User Requirements from Social Media Networks by Harnessing the Deep Sentiment Analytics

    Deema Mohammed Alsekait1,*, Asif Nawaz2, Ayman Nabil3, Mehwish Bukhari2, Diaa Salama AbdElminaam3,4,5,6,*
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.051847
    Abstract The article describes a novel method for sentiment analysis and requirement elicitation from social media feedback, leveraging advanced machine learning techniques. This innovative approach automates the extraction and classification of user requirements by analyzing sentiment in data gathered from social media platforms such as Twitter and Facebook. Utilizing APIs (Application Programming Interface) for data collection and Graphbased Neural Networks (GNN) for feature extraction, the proposed model efficiently processes and analyzes large volumes of unstructured user-generated content. The preprocessing pipeline includes data cleaning, normalization, and tokenization, ensuring high-quality input for the sentiment analysis model. By classifying… More >

  • Open Access

    REVIEW

    Biometric Authentication System on Mobile Environment: A Review

    Qasem Abu Al-Haija1,*, Sara Othman Al-Salameen2
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.050846
    Abstract The paper discusses the importance of biometric verification systems in mobile environments and highlights the challenges and strategies used to overcome them in order to ensure the security of mobile devices. Emphasis is placed on evaluating the impact of illumination on the performance of biometric verification techniques and how to address this challenge using image processing techniques. The importance of accurate and reliable data collection to ensure the accuracy of verification processes is also discussed. The paper also highlights the importance of improving biometric verification techniques and directing research toward developing models aimed at reducing More >

  • Open Access

    ARTICLE

    MG-YOLOv5s: A Faster and Stronger Helmet Detection Algorithm

    Zerui Xiao, Wei Liu, Zhiwei Ye*, Jiatang Yuan, Shishi Liu
    Computer Systems Science and Engineering, DOI:10.32604/csse.2023.040475
    Abstract Nowadays, construction site safety accidents are frequent, and wearing safety helmets is essential to prevent head injuries caused by object collisions and falls. However, existing helmet detection algorithms have several drawbacks, including a complex structure with many parameters, high calculation volume, and poor detection of small helmets, making deployment on embedded or mobile devices difficult. To address these challenges, this paper proposes a YOLOv5-based multi-head detection safety helmet detection algorithm that is faster and more robust for detecting helmets on construction sites. By replacing the traditional DarkNet backbone network of YOLOv5s with a new backbone… More >

  • Open Access

    CORRECTION

    Correction: Human Stress Recognition by Correlating Vision and EEG Data

    S. Praveenkumar*, T. Karthick
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.054414
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    A Multivariate Relevance Frequency Analysis Based Feature Selection for Classification of Short Text Data

    Saravanan Arumugam*
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.051770
    Abstract Text mining presents unique challenges in extracting meaningful information from the vast volumes of digital documents. Traditional filter feature selection methods often fall short in handling the complexities of short text data. To address this issue, this paper presents a novel approach to feature selection in text classification, aiming to overcome challenges posed by high dimensionality and reduced accuracy in the face of increasing digital document volumes. Unlike traditional filter feature selection techniques, the proposed method, Multivariate Relevance Frequency Analysis, offers a tailored solution for diverse text data types. By integrating positive, negative, and dependency… More >

  • Open Access

    RETRACTION

    Retraction: Deep Belief Network for Lung Nodule Segmentation and Cancer Detection

    Computer Systems Science and Engineering Editorial Office
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.054265
    Abstract This article has no abstract. More >

  • Open Access

    CORRECTION

    Correction: Applying Customized Convolutional Neural Network to Kidney Image Volumes for Kidney Disease Detection

    Ali Altalbe1,2,*, Abdul Rehman Javed3
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.054179
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    FFRA: A Fine-Grained Function-Level Framework to Reduce the Attack Surface

    Xingxing Zhang1, Liang Liu1,*, Yu Fan1, Qian Zhou2
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.046615
    Abstract System calls are essential interfaces that enable applications to access and utilize the operating system’s services and resources. Attackers frequently exploit application’s vulnerabilities and misuse system calls to execute malicious code, aiming to elevate privileges and so on. Consequently, restricting the misuse of system calls becomes a crucial measure in ensuring system security. It is an effective method known as reducing the attack surface. Existing attack surface reduction techniques construct a global whitelist of system calls for the entire lifetime of the application, which is coarse-grained. In this paper, we propose a Fine-grained Function-level framework… More >

  • Open Access

    ARTICLE

    A Novel Optimization Approach for Energy-Efficient Multiple Workflow Scheduling in Cloud Environment

    Ambika Aggarwal1, Sunil Kumar2,3, Ashok Bhansali4, Deema Mohammed Alsekait5,*, Diaa Salama AbdElminaam6,7,8
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.050406
    Abstract Existing multiple workflow scheduling techniques focus on traditional Quality of Service (QoS) parameters such as cost, deadline, and makespan to find optimal solutions by consuming a large amount of electrical energy. Higher energy consumption decreases system efficiency, increases operational cost, and generates more carbon footprint. These major problems can lead to several problems, such as economic strain, environmental degradation, resource depletion, energy dependence, health impacts, etc. In a cloud computing environment, scheduling multiple workflows is critical in developing a strategy for energy optimization, which is an NP-hard problem. This paper proposes a novel, bi-phase Energy-Efficient… More >

  • Open Access

    ARTICLE

    Microarray Gene Expression Classification: An Efficient Feature Selection Using Hybrid Swarm Intelligence Algorithm

    Punam Gulande*, R. N. Awale
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.046123
    (This article belongs to the Special Issue: Impact of Internet of Medical Things (IoMT) on Smart and Secure Healthcare Applications)
    Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

  • Open Access

    ARTICLE

    Intelligent Image Text Detection via Pixel Standard Deviation Representation

    Sana Sahar Guia1, Abdelkader Laouid1, Mohammad Hammoudeh2,*, Mostafa Kara1,3
    Computer Systems Science and Engineering, DOI:10.32604/csse.2024.046414
    Abstract Artificial intelligence has been involved in several domains. Despite the advantages of using artificial intelligence techniques, some crucial limitations prevent them from being implemented in specific domains and locations. The accuracy, poor quality of gathered data, and processing time are considered major concerns in implementing machine learning techniques, certainly in low-end smart devices. This paper aims to introduce a novel pre-treatment technique dedicated to image text detection that uses the images’ pixel divergence and similarity to reduce the image size. Mitigating the image size while keeping its features improves the model training time with an… More >