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  • Open Access

    ARTICLE

    Privacy Preserved Brain Disorder Diagnosis Using Federated Learning

    Ali Altalbe1,2,*, Abdul Rehman Javed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2187-2200, 2023, DOI:10.32604/csse.2023.040624

    Abstract Federated learning has recently attracted significant attention as a cutting-edge technology that enables Artificial Intelligence (AI) algorithms to utilize global learning across the data of numerous individuals while safeguarding user data privacy. Recent advanced healthcare technologies have enabled the early diagnosis of various cognitive ailments like Parkinson’s. Adequate user data is frequently used to train machine learning models for healthcare systems to track the health status of patients. The healthcare industry faces two significant challenges: security and privacy issues and the personalization of cloud-trained AI models. This paper proposes a Deep Neural Network (DNN) based approach embedded in a federated… More >

  • Open Access

    ARTICLE

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

    Ali Altalbe1,2,*, Abdul Rehman Javed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2119-2134, 2023, DOI:10.32604/csse.2023.040620

    Abstract Kidney infection is a severe medical issue affecting individuals worldwide and increasing mortality rates. Chronic Kidney Disease (CKD) is treatable during its initial phases but can become irreversible and cause renal failure. Among the various diseases, the most prevalent kidney conditions affecting kidney function are cyst growth, kidney tumors, and nephrolithiasis. The significant challenge for the medical community is the immediate diagnosis and treatment of kidney disease. Kidney failure could result from kidney disorders like tumors, stones, and cysts if not often identified and addressed. Computer-assisted diagnostics are necessary to support clinicians’ and specialists’ medical assessments due to the rising… More >

  • Open Access

    ARTICLE

    Muti-Fusion Swarm Intelligence Optimization Algorithm in Base Station Coverage Optimization Problems

    Zhenyu Yan1,*, Haotian Bian2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2241-2257, 2023, DOI:10.32604/csse.2023.040603

    Abstract As millimeter waves will be widely used in the Internet of Things (IoT) and Telematics to provide high bandwidth communication and mass connectivity, the coverage optimization of base stations can effectively improve the quality of communication services. How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers. This paper proposes the Muti-Fusion Sparrow Search Algorithm (MFSSA) optimize the situation to address the problem of discrete coverage maximization and rapid convergence. Firstly, the initial swarm diversity is enriched using a sine chaotic map, and dynamic adaptive weighting is added to the discoverer location… More >

  • Open Access

    ARTICLE

    Knee Osteoarthritis Classification Using X-Ray Images Based on Optimal Deep Neural Network

    Abdul Haseeb1, Muhammad Attique Khan1,*, Faheem Shehzad1, Majed Alhaisoni2, Junaid Ali Khan1, Taerang Kim3, Jae-Hyuk Cha3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529

    Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >

  • Open Access

    ARTICLE

    An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

    Qingqing Ning, Chunhua Jin*, Zhiwei Chen, Yongliang Xu, Huaqi Lu

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2061-2078, 2023, DOI:10.32604/csse.2023.040483

    Abstract Wireless body area networks (WBANs) are an emerging technology for the real-time monitoring of physiological signals. WBANs provide a mechanism for collecting, storing, and transmitting physiological data to healthcare providers. However, the open wireless channel and limited resources of sensors bring security challenges. To ensure physiological data security, this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption (CP-HRSC) scheme, in which sensors are in a certificateless cryptosystem (CLC) environment, and the server is in a public key infrastructure (PKI) environment. CLC could solve the limitations of key escrow in identity-based cryptography (IBC) and certificate management for public… More >

  • Open Access

    ARTICLE

    Edge Cloud Selection in Mobile Edge Computing (MEC)-Aided Applications for Industrial Internet of Things (IIoT) Services

    Dae-Young Kim1, SoYeon Lee2, MinSeung Kim2, Seokhoon Kim1,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2049-2060, 2023, DOI:10.32604/csse.2023.040473

    Abstract In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be also minimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the… More >

  • Open Access

    REVIEW

    Managing Smart Technologies with Software-Defined Networks for Routing and Security Challenges: A Survey

    Babangida Isyaku1,2, Kamalrulnizam Bin Abu Bakar2,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1839-1879, 2023, DOI:10.32604/csse.2023.040456

    Abstract Smart environments offer various services, including smart cities, e-healthcare, transportation, and wearable devices, generating multiple traffic flows with different Quality of Service (QoS) demands. Achieving the desired QoS with security in this heterogeneous environment can be challenging due to traffic flows and device management, unoptimized routing with resource awareness, and security threats. Software Defined Networks (SDN) can help manage these devices through centralized SDN controllers and address these challenges. Various schemes have been proposed to integrate SDN with emerging technologies for better resource utilization and security. Software Defined Wireless Body Area Networks (SDWBAN) and Software Defined Internet of Things (SDIoT)… More >

  • Open Access

    ARTICLE

    Rockburst Intensity Grade Prediction Model Based on Batch Gradient Descent and Multi-Scale Residual Deep Neural Network

    Yu Zhang1,2,3, Mingkui Zhang1,2,*, Jitao Li1,2, Guangshu Chen1,2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1987-2006, 2023, DOI:10.32604/csse.2023.040381

    Abstract Rockburst is a phenomenon in which free surfaces are formed during excavation, which subsequently causes the sudden release of energy in the construction of mines and tunnels. Light rockburst only peels off rock slices without ejection, while severe rockburst causes casualties and property loss. The frequency and degree of rockburst damage increases with the excavation depth. Moreover, rockburst is the leading engineering geological hazard in the excavation process, and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering. Therefore, the prediction of rockburst intensity grade is one problem that needs to be… More >

  • Open Access

    ARTICLE

    Securing Transmitted Color Images Using Zero Watermarking and Advanced Encryption Standard on Raspberry Pi

    Doaa Sami Khafaga1, Sarah M. Alhammad1,*, Amal Magdi2, Osama ElKomy2, Nabil A. Lashin2, Khalid M. Hosny2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1967-1986, 2023, DOI:10.32604/csse.2023.040345

    Abstract Image authentication techniques have recently received a lot of attention for protecting images against unauthorized access. Due to the wide use of the Internet nowadays, the need to ensure data integrity and authentication increases. Many techniques, such as watermarking and encryption, are used for securing images transmitted via the Internet. The majority of watermarking systems are PC-based, but they are not very portable. Hardware-based watermarking methods need to be developed to accommodate real-time applications and provide portability. This paper presents hybrid data security techniques using a zero watermarking method to provide copyright protection for the transmitted color images using multi-channel… More >

  • Open Access

    ARTICLE

    A Triplet-Branch Convolutional Neural Network for Part-Based Gait Recognition

    Sang-Soo Yeo1, Seungmin Rho2,*, Hyungjoon Kim3, Jibran Safdar4, Umar Zia5, Mehr Yahya Durrani5

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2027-2047, 2023, DOI:10.32604/csse.2023.040327

    Abstract Intelligent vision-based surveillance systems are designed to deal with the gigantic volume of videos captured in a particular environment to perform the interpretation of scenes in form of detection, tracking, monitoring, behavioral analysis, and retrievals. In addition to that, another evolving way of surveillance systems in a particular environment is human gait-based surveillance. In the existing research, several methodological frameworks are designed to use deep learning and traditional methods, nevertheless, the accuracies of these methods drop substantially when they are subjected to covariate conditions. These covariate variables disrupt the gait features and hence the recognition of subjects becomes difficult. To… More >

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