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  • Open Access

    ARTICLE

    Enhanced Transmission Tower Foundation Reliability Assessment: A Fuzzy Comprehensive Evaluation Framework

    Yang Li1, Zikang Zheng1,*, Jiangkun Zhang2

    Structural Durability & Health Monitoring, Vol.18, No.4, pp. 425-444, 2024, DOI:10.32604/sdhm.2024.046584

    Abstract Due to the lack of a quantitative basis for the inspection, evaluation, and identification of existing transmission tower foundations, a new fuzzy comprehensive evaluation method is proposed to assess the reliability of transmission tower foundation bearing capacity. This method is based on the reliability analysis of the transmission tower foundation bearing capacity by analyzing the sensitivity of degradation of detection indexes on the reliability of transmission tower foundation bearing capacity, the weighting coefficient matrix is established about the influencing factors in the evaluation model. Through the correlation analysis between the bearing capacity degradation of the More > Graphic Abstract

    Enhanced Transmission Tower Foundation Reliability Assessment: A Fuzzy Comprehensive Evaluation Framework

  • Open Access

    ARTICLE

    Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

    Lin Ma1, Liyong Wang1, Shuang Zeng1, Yutong Zhao1, Chang Liu1, Heng Zhang1, Qiong Wu2,*, Hongbo Ren2

    Energy Engineering, Vol.121, No.6, pp. 1473-1493, 2024, DOI:10.32604/ee.2024.047332

    Abstract Accurate load forecasting forms a crucial foundation for implementing household demand response plans and optimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations, a single prediction model is hard to capture temporal features effectively, resulting in diminished prediction accuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neural network (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), is proposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features from the original data, enhancing the quality of data… More >

  • Open Access

    ARTICLE

    2P3FL: A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

    Sandeep Dasari, Rajesh Kaluri*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2035-2051, 2024, DOI:10.32604/cmes.2024.049152

    Abstract The increasing data pool in finance sectors forces machine learning (ML) to step into new complications. Banking data has significant financial implications and is confidential. Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages. As a result, this study employs federated learning (FL) using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model. However, diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy. To address this issue, the… More > Graphic Abstract

    2P3FL: A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

  • Open Access

    ARTICLE

    An Improved Deep Learning Framework for Automated Optic Disc Localization and Glaucoma Detection

    Hela Elmannai1,*, Monia Hamdi1, Souham Meshoul1, Amel Ali Alhussan2, Manel Ayadi3, Amel Ksibi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1429-1457, 2024, DOI:10.32604/cmes.2024.048557

    Abstract Glaucoma disease causes irreversible damage to the optical nerve and it has the potential to cause permanent loss of vision. Glaucoma ranks as the second most prevalent cause of permanent blindness. Traditional glaucoma diagnosis requires a highly experienced specialist, costly equipment, and a lengthy wait time. For automatic glaucoma detection, state-of-the-art glaucoma detection methods include a segmentation-based method to calculate the cup-to-disc ratio. Other methods include multi-label segmentation networks and learning-based methods and rely on hand-crafted features. Localizing the optic disc (OD) is one of the key features in retinal images for detecting retinal diseases,… More >

  • Open Access

    ARTICLE

    A Hybrid Machine Learning Framework for Security Intrusion Detection

    Fatimah Mudhhi Alanazi*, Bothina Abdelmeneem Elsobky, Shaimaa Aly Elmorsy

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 835-851, 2024, DOI:10.32604/csse.2024.042401

    Abstract Proliferation of technology, coupled with networking growth, has catapulted cybersecurity to the forefront of modern security concerns. In this landscape, the precise detection of cyberattacks and anomalies within networks is crucial, necessitating the development of efficient intrusion detection systems (IDS). This article introduces a framework utilizing the fusion of fuzzy sets with support vector machines (SVM), named FSVM. The core strategy of FSVM lies in calculating the significance of network features to determine their relative importance. Features with minimal significance are prudently disregarded, a method akin to feature selection. This process not only curtails the… More >

  • Open Access

    ARTICLE

    A Framework for Driver Drowsiness Monitoring Using a Convolutional Neural Network and the Internet of Things

    Muhamad Irsan1,2,*, Rosilah Hassan2, Anwar Hassan Ibrahim3, Mohamad Khatim Hasan2, Meng Chun Lam2, Wan Mohd Hirwani Wan Hussain4

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 157-174, 2024, DOI:10.32604/iasc.2024.042193

    Abstract One of the major causes of road accidents is sleepy drivers. Such accidents typically result in fatalities and financial losses and disadvantage other road users. Numerous studies have been conducted to identify the driver’s sleepiness and integrate it into a warning system. Most studies have examined how the mouth and eyelids move. However, this limits the system’s ability to identify drowsiness traits. Therefore, this study designed an Accident Detection Framework (RPK) that could be used to reduce road accidents due to sleepiness and detect the location of accidents. The drowsiness detection model used three facial… More >

  • Open Access

    ARTICLE

    Influence of Confined Concrete Models on the Seismic Response of RC Frames

    Hüseyin Bilgin*, Bredli Plaku

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 197-222, 2024, DOI:10.32604/sdhm.2024.048645

    Abstract In this study, the influence of confined concrete models on the response of reinforced concrete structures is investigated at member and global system levels. The commonly encountered concrete models such as Modified Kent-Park, Saatçioğlu-Razvi, and Mander are considered. Two moment-resisting frames designed according to the pre-modern code are taken into consideration to reflect the example of an RC moment-resisting frame in the current building stock. The building is in an earthquake-prone zone located on Z3 Soil Type. The inelastic response of the building frame is modelled by considering the plastic hinges formed on each beam… More >

  • Open Access

    ARTICLE

    Field Load Test Based SHM System Safety Standard Determination for Rigid Frame Bridge

    Xilong Zheng*, Qiong Wang, Di Guan

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 361-376, 2024, DOI:10.32604/sdhm.2024.048473

    Abstract The deteriorated continuous rigid frame bridge is strengthened by external prestressing. Static loading tests were conducted before and after the bridge rehabilitation to verify the effectiveness of the rehabilitation process. The stiffness of the repaired bridge is improved, and the maximum deflection of the load test is reduced from 37.9 to 27.6 mm. A bridge health monitoring system is installed after the bridge is reinforced. To achieve an easy assessment of the bridge’s safety status by directly using transferred data, a real-time safety warning system is created based on a five-level safety standard. The threshold More >

  • Open Access

    REVIEW

    Federated Learning on Internet of Things: Extensive and Systematic Review

    Meenakshi Aggarwal1, Vikas Khullar1, Sunita Rani2, Thomas André Prola3,4,5, Shyama Barna Bhattacharjee6, Sarowar Morshed Shawon7, Nitin Goyal8,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1795-1834, 2024, DOI:10.32604/cmc.2024.049846

    Abstract The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation. However, FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios. The paper systematically reviewed the available literature using the PRISMA guiding principle. The study aims to provide a detailed overview of the increasing use of FL in IoT networks, including the architecture and challenges. A systematic review approach is used to collect, categorize and analyze FL-IoT-based articles.… More >

  • Open Access

    ARTICLE

    A Novel Scheduling Framework for Multi-Programming Quantum Computing in Cloud Environment

    Danyang Zheng, Jinchen Xv, Feng Yue, Qiming Du, Zhiheng Wang, Zheng Shan*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1957-1974, 2024, DOI:10.32604/cmc.2024.048956

    Abstract As cloud quantum computing gains broader acceptance, a growing quantity of researchers are directing their focus towards this domain. Nevertheless, the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity, which in turn hampers users from achieving optimal satisfaction. Therefore, cloud quantum computing service providers require a unified analysis and scheduling framework for their quantum resources and user jobs to meet the ever-growing usage demands. This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment. The framework addresses the issue of limited quantum computing resources More >

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