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  • Open Access


    Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

    Mohamed Zarouan1, Ibrahim M. Mehedi1,2,*, Shaikh Abdul Latif3, Md. Masud Rana4

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1341-1364, 2024, DOI:10.32604/cmes.2023.030037

    Abstract Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamless operation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0. Specifically, various modernized industrial processes have been equipped with quite a few sensors to collect process-based data to find faults arising or prevailing in processes along with monitoring the status of processes. Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Due to the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experience and human knowledge, intellectual… More >

  • Open Access


    Fractal Fractional Order Operators in Computational Techniques for Mathematical Models in Epidemiology

    Muhammad Farman1,2,4, Ali Akgül3,9,*, Mir Sajjad Hashemi5, Liliana Guran6,7, Amelia Bucur8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1385-1403, 2024, DOI:10.32604/cmes.2023.028803

    Abstract New fractional operators, the COVID-19 model has been studied in this paper. By using different numerical techniques and the time fractional parameters, the mechanical characteristics of the fractional order model are identified. The uniqueness and existence have been established. The model’s Ulam-Hyers stability analysis has been found. In order to justify the theoretical results, numerical simulations are carried out for the presented method in the range of fractional order to show the implications of fractional and fractal orders. We applied very effective numerical techniques to obtain the solutions of the model and simulations. Also, we present conditions of existence for… More >

  • Open Access


    A Conditionally Anonymous Linkable Ring Signature for Blockchain Privacy Protection

    Quan Zhou1,*, Yulong Zheng1, Minhui Chen2, Kaijun Wei2

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2851-2867, 2023, DOI:10.32604/csse.2023.039908

    Abstract In recent years, the issue of preserving the privacy of parties involved in blockchain transactions has garnered significant attention. To ensure privacy protection for both sides of the transaction, many researchers are using ring signature technology instead of the original signature technology. However, in practice, identifying the signer of an illegal blockchain transaction once it has been placed on the chain necessitates a signature technique that offers conditional anonymity. Some illegals can conduct illegal transactions and evade the law using ring signatures, which offer perfect anonymity. This paper firstly constructs a conditionally anonymous linkable ring signature using the Diffie-Hellman key… More >

  • Open Access


    An Adaptive Edge Detection Algorithm for Weed Image Analysis

    Yousef Alhwaiti1,*, Muhammad Hameed Siddiqi1, Irshad Ahmad2

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3011-3031, 2023, DOI:10.32604/csse.2023.042110

    Abstract Weeds are one of the utmost damaging agricultural annoyers that have a major influence on crops. Weeds have the responsibility to get higher production costs due to the waste of crops and also have a major influence on the worldwide agricultural economy. The significance of such concern got motivation in the research community to explore the usage of technology for the detection of weeds at early stages that support farmers in agricultural fields. Some weed methods have been proposed for these fields; however, these algorithms still have challenges as they were implemented against controlled environments. Therefore, in this paper, a… More >

  • Open Access


    Entropy Based Feature Fusion Using Deep Learning for Waste Object Detection and Classification Model

    Ehab Bahaudien Ashary1, Sahar Jambi2, Rehab B. Ashari2, Mahmoud Ragab3,4,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2953-2969, 2023, DOI:10.32604/csse.2023.041523

    Abstract Object Detection is the task of localization and classification of objects in a video or image. In recent times, because of its widespread applications, it has obtained more importance. In the modern world, waste pollution is one significant environmental problem. The prominence of recycling is known very well for both ecological and economic reasons, and the industry needs higher efficiency. Waste object detection utilizing deep learning (DL) involves training a machine-learning method to classify and detect various types of waste in videos or images. This technology is utilized for several purposes recycling and sorting waste, enhancing waste management and reducing… More >

  • Open Access


    Fast and Accurate Detection of Masked Faces Using CNNs and LBPs

    Sarah M. Alhammad1, Doaa Sami Khafaga1,*, Aya Y. Hamed2, Osama El-Koumy3, Ehab R. Mohamed3, Khalid M. Hosny3

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2939-2952, 2023, DOI:10.32604/csse.2023.041011

    Abstract Face mask detection has several applications, including real-time surveillance, biometrics, etc. Identifying face masks is also helpful for crowd control and ensuring people wear them publicly. With monitoring personnel, it is impossible to ensure that people wear face masks; automated systems are a much superior option for face mask detection and monitoring. This paper introduces a simple and efficient approach for masked face detection. The architecture of the proposed approach is very straightforward; it combines deep learning and local binary patterns to extract features and classify them as masked or unmasked. The proposed system requires hardware with minimal power consumption… More >

  • Open Access


    MBE: A Music Copyright Depository Framework Incorporating Blockchain and Edge Computing

    Jianmao Xiao1, Ridong Huang1, Jiangyu Wang1, Zhean Zhong1, Chenyu Liu1, Yuanlong Cao1,*, Chuying Ouyang2

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2815-2834, 2023, DOI:10.32604/csse.2023.039716

    Abstract Audio copyright is a crucial issue in the music industry, as it protects the rights and interests of creators and distributors. This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on “blockchain + edge computing mode,” abbreviated as MBE, by integrating edge computing into the Hyperledger Fabric system. MBE framework compresses and splits the audio into small chunks, performs Fast Fourier Transform (FFT) to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information. After being confirmed by various nodes on the Fabric alliance… More >

  • Open Access


    Medi-Block Record Secure Data Sharing in Healthcare System: Issues, Solutions and Challenges

    Zuriati Ahmad Zukarnain1,*, Amgad Muneer2,3, Nur Atirah Mohamad Nassir1, Akram A. Almohammedi4,5

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2725-2740, 2023, DOI:10.32604/csse.2023.034448

    Abstract With the advancements in the era of artificial intelligence, blockchain, cloud computing, and big data, there is a need for secure, decentralized medical record storage and retrieval systems. While cloud storage solves storage issues, it is challenging to realize secure sharing of records over the network. Medi-block record in the healthcare system has brought a new digitalization method for patients’ medical records. This centralized technology provides a symmetrical process between the hospital and doctors when patients urgently need to go to a different or nearby hospital. It enables electronic medical records to be available with the correct authentication and restricts… More >

  • Open Access


    Protective Graphite Coating for Two-Dimensional Carbon/Carbon Composites

    Wei Shi1,2, Zhengyi Li1, Xiaobing Xu1, Yingshui Yu1, Xiaofei Ding1, Heng Ju1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 97-108, 2024, DOI:10.32604/fdmp.2023.029028

    Abstract Two-dimensional carbon/carbon (2D C/C) composites are a special class of carbon/carbon composites, generally obtained by combining resin-impregnated carbon fiber clothes, which are then cured and carbonized. This study deals with the preparation of a protective coating for these materials. This coating, based on graphite, was prepared by the slurry method. The effect of graphite and phenolic resin powders with different weight ratios was examined. The results have shown that the coating slurry can fill the pores and cracks of the composite surface, thereby densifying the surface layer of the material. With the increase of the graphite powder/phenolic resin weight ratio,… More >

  • Open Access


    Efficient Technique for Image Cryptography Using Sudoku Keys

    M. A. P. Manimekalai1, M. Karthikeyan1, I. Thusnavis Bella Mary1, K. Martin Sagayam1, Ahmed A Elngar2, Unai Fernandez-Gamiz3, Hatıra Günerhan4,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1325-1353, 2023, DOI:10.32604/cmc.2023.035856

    Abstract This paper proposes a cryptographic technique on images based on the Sudoku solution. Sudoku is a number puzzle, which needs applying defined protocols and filling the empty boxes with numbers. Given a small size of numbers as input, solving the sudoku puzzle yields an expanded big size of numbers, which can be used as a key for the Encryption/Decryption of images. In this way, the given small size of numbers can be stored as the prime key, which means the key is compact. A prime key clue in the sudoku puzzle always leads to only one solution, which means the… More >

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