Open Access
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
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
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
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
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
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
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
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
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
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 >
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