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  • Open Access

    ARTICLE

    Detection Algorithm of Surface Defect Word on Printed Circuit Board

    Min Zhang*, Haixu Xi

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3911-3923, 2023, DOI:10.32604/csse.2023.036709 - 03 April 2023

    Abstract For Printed Circuit Board (PCB) surface defect detection, traditional detection methods mostly focus on template matching-based reference method and manual detections, which have the disadvantages of low defect detection efficiency, large errors in defect identification and localization, and low versatility of detection methods. In order to further meet the requirements of high detection accuracy, real-time and interactivity required by the PCB industry in actual production life. In the current work, we improve the You-only-look-once (YOLOv4) defect detection method to train and detect six types of PCB small target defects. Firstly, the original Cross Stage Partial… More >

  • Open Access

    ARTICLE

    A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

    Jiwon Jeon, Junho Kim, Mincheol Shin, Mucheol Kim*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3403-3421, 2023, DOI:10.32604/csse.2023.036658 - 03 April 2023

    Abstract The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment. However, while collaborative business expands the realm of businesses, it also causes various hazards in collaborative Interaction, such as data falsification, inconstancy, and misuse. To solve these issues, a blockchain-based collaborative business modeling approach was proposed and analyzed. However, the existing studies lack the blockchain risk problem-solving specification, and there is no verification technique to examine the process. Consequently, it is difficult to confirm the appropriateness of the approach. Thus, here, we propose and… More >

  • Open Access

    ARTICLE

    A Novel Cluster Analysis-Based Crop Dataset Recommendation Method in Precision Farming

    K. R. Naveen Kumar1, Husam Lahza2, B. R. Sreenivasa3,*, Tawfeeq Shawly4, Ahmed A. Alsheikhy5, H. Arunkumar1, C. R. Nirmala1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3239-3260, 2023, DOI:10.32604/csse.2023.036629 - 03 April 2023

    Abstract Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making information. Precision agriculture uses data mining to advance agricultural developments. Many farmers aren’t getting the most out of their land because they don’t use precision agriculture. They harvest crops without a well-planned recommendation system. Future crop production is calculated by combining environmental conditions and management behavior, yielding numerical and categorical data. Most existing research still needs to address data preprocessing and crop categorization/classification. Furthermore, statistical analysis receives less attention, despite producing more accurate and valid results. The study was conducted on… More >

  • Open Access

    ARTICLE

    Modified Metaheuristics with Transfer Learning Based Insect Pest Classification for Agricultural Crops

    Saud Yonbawi1, Sultan Alahmari2, T. Satyanarayana murthy3, Ravuri Daniel4, E. Laxmi Lydia5, Mohamad Khairi Ishak6, Hend Khalid Alkahtani7,*, Ayman Aljarbouh8, Samih M. Mostafa9

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3847-3864, 2023, DOI:10.32604/csse.2023.036552 - 03 April 2023

    Abstract Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged, and due to the pest attacks, the quality is degraded. They are the major reason behind crop quality degradation and diminished crop productivity. Hence, accurate pest detection is essential to guarantee safety and crop quality. Conventional identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological features. Lately, some progress has been made in agriculture by employing machine learning (ML) to classify and detect pests. This study introduces a Modified Metaheuristics with Transfer… More >

  • Open Access

    ARTICLE

    Fuzzy Logic-Based System for Liver Fibrosis Disease

    Tamim Alkhalifah1,*, Jimmy Singla2, Fahad Alurise1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3559-3582, 2023, DOI:10.32604/csse.2023.036534 - 03 April 2023

    Abstract The diagnosis of liver fibrosis (LF) is crucial as it is a deadly and life-threatening disease. Artificial intelligence techniques aid doctors by using the previous data on health and making a diagnostic system, which helps to take decisions about patients’ health as experts can. The historical data of a patient’s health can have vagueness, inaccurate, and can also have missing values. The fuzzy logic theory can deal with these issues in the dataset. In this paper, a multilayer fuzzy expert system is developed to diagnose LF. The model is created by using multiple layers of… More >

  • Open Access

    ARTICLE

    Automated Leukemia Screening and Sub-types Classification Using Deep Learning

    Chaudhary Hassan Abbas Gondal1,*, Muhammad Irfan2, Sarmad Shafique3, Muhammad Salman Bashir4, Mansoor Ahmed1, Osama M.Alshehri5, Hassan H. Almasoudi5, Samar M. Alqhtani6, Mohammed M. Jalal7, Malik A. Altayar7, Khalaf F. Alsharif8

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3541-3558, 2023, DOI:10.32604/csse.2023.036476 - 03 April 2023

    Abstract Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human body. It produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells (RBCs) and white blood cells (WBC), and platelets. Leukemia can be diagnosed manually by taking a complete blood count test of the patient’s blood, from which medical professionals can investigate the signs of leukemia cells. Furthermore, two other methods, microscopic inspection of blood smears… More >

  • Open Access

    ARTICLE

    Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

    Hala Ahmed1, Hassan Soliman1, Shaker El-Sappagh2,3,4, Tamer Abuhmed4,*, Mohammed Elmogy1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2773-2795, 2023, DOI:10.32604/csse.2023.036371 - 03 April 2023

    Abstract The precise diagnosis of Alzheimer’s disease is critical for patient treatment, especially at the early stage, because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage occurs. It is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities, known as image fusion. In this paper, the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain images. First, the preprocessing was performed on the data. Then, the data augmentation techniques are used to handle overfitting. Also, the… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

    Khaled M. Alalayah1, Fatma S. Alrayes2, Jaber S. Alzahrani3, Khadija M. Alaidarous1, Ibrahim M. Alwayle1, Heba Mohsen4, Ibrahim Abdulrab Ahmed5, Mesfer Al Duhayyim6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3121-3139, 2023, DOI:10.32604/csse.2023.036352 - 03 April 2023

    Abstract With the increased advancements of smart industries, cybersecurity has become a vital growth factor in the success of industrial transformation. The Industrial Internet of Things (IIoT) or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether. In industry 4.0, powerful Intrusion Detection Systems (IDS) play a significant role in ensuring network security. Though various intrusion detection techniques have been developed so far, it is challenging to protect the intricate data of networks. This is because conventional Machine Learning (ML) approaches are inadequate and insufficient to address the demands of dynamic IIoT networks. Further,… More >

  • Open Access

    ARTICLE

    Two-Way Approach for Improved Real-Time Transmission in Fog-IoT-Based Health Monitoring System for Critical Patients

    Abeera Ilyas1,*, Saeed Mahfooz1, Zahid Mehmood2,3, Gauhar Ali4, Muhammad ElAffendi4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3815-3829, 2023, DOI:10.32604/csse.2023.036316 - 03 April 2023

    Abstract Health monitoring systems are now required, particularly for essential patients, following the COVID-19 pandemic, which was followed by its variants and other epidemics of a similar nature. Effective procedures and strategies are required, though, to react promptly to the enormous volume of real-time data offered by monitoring equipment. Although fog-based designs for IoT health systems typically result in enhanced services, they also give rise to issues that need to be resolved. In this paper, we propose a two-way strategy to reduce network latency and use while increasing real-time data transmission of device gateways used for More >

  • Open Access

    ARTICLE

    SMOGN, MFO, and XGBoost Based Excitation Current Prediction Model for Synchronous Machine

    Ping-Huan Kuo1,2, Yu-Tsun Chen1, Her-Terng Yau1,2,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2687-2709, 2023, DOI:10.32604/csse.2023.036293 - 03 April 2023

    Abstract The power factor is the ratio between the active and apparent power, and it is available to determine the operational capability of the intended circuit or the parts. The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status. Although the excitation current should predict with the experimental devices, such a method is unsuitable for online real-time prediction. The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the… More >

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