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  • Open Access


    SNELM: SqueezeNet-Guided ELM for COVID-19 Recognition

    Yudong Zhang1, Muhammad Attique Khan2, Ziquan Zhu1, Shuihua Wang1,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 13-26, 2023, DOI:10.32604/csse.2023.034172

    Abstract (Aim) The COVID-19 has caused 6.26 million deaths and 522.06 million confirmed cases till 17/May/2022. Chest computed tomography is a precise way to help clinicians diagnose COVID-19 patients. (Method) Two datasets are chosen for this study. The multiple-way data augmentation, including speckle noise, random translation, scaling, salt-and-pepper noise, vertical shear, Gamma correction, rotation, Gaussian noise, and horizontal shear, is harnessed to increase the size of the training set. Then, the SqueezeNet (SN) with complex bypass is used to generate SN features. Finally, the extreme learning machine (ELM) is used to serve as the classifier due to its simplicity of usage,… More >

  • Open Access


    An Efficient Intrusion Detection Framework for Industrial Internet of Things Security

    Samah Alshathri1, Ayman El-Sayed2, Walid El-Shafai3,4,*, Ezz El-Din Hemdan2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 819-834, 2023, DOI:10.32604/csse.2023.034095

    Abstract Recently, the Internet of Things (IoT) has been used in various applications such as manufacturing, transportation, agriculture, and healthcare that can enhance efficiency and productivity via an intelligent management console remotely. With the increased use of Industrial IoT (IIoT) applications, the risk of brutal cyber-attacks also increased. This leads researchers worldwide to work on developing effective Intrusion Detection Systems (IDS) for IoT infrastructure against any malicious activities. Therefore, this paper provides effective IDS to detect and classify unpredicted and unpredictable severe attacks in contradiction to the IoT infrastructure. A comprehensive evaluation examined on a new available benchmark TON_IoT dataset is… More >

  • Open Access


    Optimization of Interactive Videos Empowered the Experience of Learning Management System

    Muhammad Akram1, Muhammad Waseem Iqbal2,*, M. Usman Ashraf3, Erssa Arif1, Khalid Alsubhi4, Hani Moaiteq Aljahdali5

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1021-1038, 2023, DOI:10.32604/csse.2023.034085

    Abstract The Learning management system (LMS) is now being used for uploading educational content in both distance and blended setups. LMS platform has two types of users: the educators who upload the content, and the students who have to access the content. The students, usually rely on text notes or books and video tutorials while their exams are conducted with formal methods. Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode. The aim is to design an interactive LMS and examination video-based… More >

  • Open Access


    IoT-Driven Optimal Lightweight RetinaNet-Based Object Detection for Visually Impaired People

    Mesfer Alduhayyem1,*, Mrim M. Alnfiai2,3, Nabil Almalki4, Fahd N. Al-Wesabi5, Anwer Mustafa Hilal6, Manar Ahmed Hamza6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 475-489, 2023, DOI:10.32604/csse.2023.034067

    Abstract Visual impairment is one of the major problems among people of all age groups across the globe. Visually Impaired Persons (VIPs) require help from others to carry out their day-to-day tasks. Since they experience several problems in their daily lives, technical intervention can help them resolve the challenges. In this background, an automatic object detection tool is the need of the hour to empower VIPs with safe navigation. The recent advances in the Internet of Things (IoT) and Deep Learning (DL) techniques make it possible. The current study proposes IoT-assisted Transient Search Optimization with a Lightweight RetinaNet-based object detection (TSOLWR-ODVIP)… More >

  • Open Access


    Secured Access Policy in Ciphertext-Policy Attribute-Based Encryption for Cloud Environment

    P. Prathap Nayudu, Krovi Raja Sekhar*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1079-1092, 2023, DOI:10.32604/csse.2023.033961

    Abstract The cloud allows clients to store and share data. Depending on the user’s needs, it is imperative to design an effective access control plan to share the information only with approved users. The user loses control of their data when the data is outsourced to the cloud. Therefore, access control mechanisms will become a significant challenging problem. The Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is an essential solution in which the user can control data access. CP-ABE encrypts the data under a limited access policy after the user sets some access policies. The user can decrypt the data if they satisfy the… More >

  • Open Access


    Byte-Level Function-Associated Method for Malware Detection

    Jingwei Hao*, Senlin Luo, Limin Pan

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 719-734, 2023, DOI:10.32604/csse.2023.033923

    Abstract The byte stream is widely used in malware detection due to its independence of reverse engineering. However, existing methods based on the byte stream implement an indiscriminate feature extraction strategy, which ignores the byte function difference in different segments and fails to achieve targeted feature extraction for various byte semantic representation modes, resulting in byte semantic confusion. To address this issue, an enhanced adversarial byte function associated method for malware backdoor attack is proposed in this paper by categorizing various function bytes into three functions involving structure, code, and data. The Minhash algorithm, grayscale mapping, and state transition probability statistics… More >

  • Open Access


    Improving QoS Using Mobility-Based Optimized Multipath Routing Protocol in MANET

    S. J. Sangeetha1,*, T. Rajendran2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1169-1181, 2023, DOI:10.32604/csse.2023.033392

    Abstract Mobile Ad-hoc Networks (MANETs) connect numerous nodes to communicate data from the sender node to the target node. Due to the lack of an infrastructure network, mobile nodes communicate through wireless without an access point. MANET does not have a centralized controller and has a dynamic network topology, which increases link failure and energy consumption resulting in excessive path delay, loss of Quality of service (QoS), and reduced throughput during data communication. Congestion is a significant problem when the QoS of the link carrying the data is degraded. Routing is one of the vital challenges of MANET due to the… More >

  • Open Access


    A Multi-Module Machine Learning Approach to Detect Tax Fraud

    N. Alsadhan*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 241-253, 2023, DOI:10.32604/csse.2023.033375

    Abstract Tax fraud is one of the substantial issues affecting governments around the world. It is defined as the intentional alteration of information provided on a tax return to reduce someone’s tax liability. This is done by either reducing sales or increasing purchases. According to recent studies, governments lose over $500 billion annually due to tax fraud. A loss of this magnitude motivates tax authorities worldwide to implement efficient fraud detection strategies. Most of the work done in tax fraud using machine learning is centered on supervised models. A significant drawback of this approach is that it requires tax returns that… More >

  • Open Access


    Behavioral Intention to Continue Using a Library Mobile App

    X. Zhang1, H. Liu1, Z. H. Liu1, J. R. Ming1,*, Y. Zhou2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 357-369, 2023, DOI:10.32604/csse.2023.033251

    Abstract To meet the needs of today’s library users, institutions are developing library mobile apps (LMAs), as their libraries are increasingly intelligent and rely on deep learning. This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA. A research model was constructed based on the technology acceptance model. A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data. The analysis was based on structural equation modeling. The empirical results show that the perceived ease of use, the… More >

  • Open Access


    Visual Object Tracking Based on Modified LeNet-5 and RCCF

    Aparna Gullapelly, Barnali Gupta Banik*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1127-1139, 2023, DOI:10.32604/csse.2023.032904

    Abstract The field of object tracking has recently made significant progress. Particularly, the performance results in both deep learning and correlation filters, based trackers achieved effective tracking performance. Moreover, there are still some difficulties with object tracking for example illumination and deformation (DEF). The precision and accuracy of tracking algorithms suffer from the effects of such occurrences. For this situation, finding a solution is important. This research proposes a new tracking algorithm to handle this problem. The features are extracted by using Modified LeNet-5, and the precision and accuracy are improved by developing the Real-Time Cross-modality Correlation Filtering method (RCCF). In… More >

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