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  • Open Access

    ARTICLE

    Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

    Yue Yang1, Jiarui Zheng1, Long Cheng1,*, Yongnan Zhu2, Hao Wu2

    Energy Engineering, Vol.121, No.3, pp. 703-728, 2024, DOI:10.32604/ee.2023.044721

    Abstract To effectively quantify the impact of distributed photovoltaic (PV) access on the distribution network, this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution (TOPSIS)—rank sum ratio (RSR) (TOPSIS-RSR) method. Based on the traditional distribution network evaluation system, a comprehensive evaluation system has been constructed. It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection. The analytic hierarchy… More >

  • Open Access

    ARTICLE

    Screen for autophagy-related biomarkers in osteoarthritis based on bioinformatic analysis

    CHAO LIU*

    BIOCELL, Vol.48, No.2, pp. 339-351, 2024, DOI:10.32604/biocell.2023.047044

    Abstract Introduction: Osteoarthritis (OA) is still an important health problem, and understanding its pathological mechanisms is essential for its diagnosis and treatment. There is evidence that autophagy may play a role in OA progression, but the exact mechanism remains unclear. Methods: In this study, we adopted a multi-prong approach to systematically identify the key autophagy-related genes (ARGs) associated with OA. Through weighted gene co-expression network analysis, we initially identified significant gene modules associated with OA. Subsequent differential gene analysis performed on normal and OA specimens. Further analysis later using the MCC algorithm highlighted hub ARGs. These genes were then incorporated into… More >

  • Open Access

    REVIEW

    A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

    Sunil Kumar1, Dilip Kumar1, Ramraj Dangi2, Gaurav Choudhary3, Nicola Dragoni4, Ilsun You5,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 31-63, 2024, DOI:10.32604/cmc.2023.047084

    Abstract The widespread and growing interest in the Internet of Things (IoT) may be attributed to its usefulness in many different fields. Physical settings are probed for data, which is then transferred via linked networks. There are several hurdles to overcome when putting IoT into practice, from managing server infrastructure to coordinating the use of tiny sensors. When it comes to deploying IoT, everyone agrees that security is the biggest issue. This is due to the fact that a large number of IoT devices exist in the physical world and that many of them have constrained resources such as electricity, memory,… More >

  • Open Access

    ARTICLE

    Lightweight Intrusion Detection Using Reservoir Computing

    Jiarui Deng1,2, Wuqiang Shen1,3, Yihua Feng4, Guosheng Lu5, Guiquan Shen1,3, Lei Cui1,3, Shanxiang Lyu1,2,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1345-1361, 2024, DOI:10.32604/cmc.2023.047079

    Abstract The blockchain-empowered Internet of Vehicles (IoV) enables various services and achieves data security and privacy, significantly advancing modern vehicle systems. However, the increased frequency of data transmission and complex network connections among nodes also make them more susceptible to adversarial attacks. As a result, an efficient intrusion detection system (IDS) becomes crucial for securing the IoV environment. Existing IDSs based on convolutional neural networks (CNN) often suffer from high training time and storage requirements. In this paper, we propose a lightweight IDS solution to protect IoV against both intra-vehicle and external threats. Our approach achieves superior performance, as demonstrated by… More >

  • Open Access

    ARTICLE

    A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

    Amira M. Idrees1,*, Abdul Lateef Marzouq Al-Solami2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1115-1133, 2024, DOI:10.32604/cmc.2023.046457

    Abstract The developed system for eye and face detection using Convolutional Neural Networks (CNN) models, followed by eye classification and voice-based assistance, has shown promising potential in enhancing accessibility for individuals with visual impairments. The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system. This research significantly contributes to the field of accessibility technology by integrating computer vision, natural language processing, and voice technologies. By leveraging these advancements, the developed system offers a practical and efficient solution for assisting blind individuals. The modular design ensures flexibility, scalability, and… More >

  • Open Access

    ARTICLE

    An Improved Solov2 Based on Attention Mechanism and Weighted Loss Function for Electrical Equipment Instance Segmentation

    Junpeng Wu1,2,*, Zhenpeng Liu2, Xingfan Jiang2, Xinguang Tao2, Ye Zhang3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 677-694, 2024, DOI:10.32604/cmc.2023.045759

    Abstract The current existing problem of deep learning framework for the detection and segmentation of electrical equipment is dominantly related to low precision. Because of the reliable, safe and easy-to-operate technology provided by deep learning-based video surveillance for unmanned inspection of electrical equipment, this paper uses the bottleneck attention module (BAM) attention mechanism to improve the Solov2 model and proposes a new electrical equipment segmentation mode. Firstly, the BAM attention mechanism is integrated into the feature extraction network to adaptively learn the correlation between feature channels, thereby improving the expression ability of the feature map; secondly, the weighted sum of CrossEntropy… More >

  • Open Access

    ARTICLE

    Software Defect Prediction Method Based on Stable Learning

    Xin Fan1,2,3, Jingen Mao2,3,*, Liangjue Lian2,3, Li Yu1, Wei Zheng2,3, Yun Ge2,3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 65-84, 2024, DOI:10.32604/cmc.2023.045522

    Abstract The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor. In previous software defect prediction studies, transfer learning was effective in solving the problem of inconsistent project data distribution. However, target projects often lack sufficient data, which affects the performance of the transfer learning model. In addition, the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model. To address these problems, this article propose a software defect prediction method based on stable learning (SDP-SL) that combines code… More >

  • Open Access

    ARTICLE

    Lightweight Malicious Code Classification Method Based on Improved SqueezeNet

    Li Li*, Youran Kong, Qing Zhang

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 551-567, 2024, DOI:10.32604/cmc.2023.045512

    Abstract With the growth of the Internet, more and more business is being done online, for example, online offices, online education and so on. While this makes people’s lives more convenient, it also increases the risk of the network being attacked by malicious code. Therefore, it is important to identify malicious codes on computer systems efficiently. However, most of the existing malicious code detection methods have two problems: (1) The ability of the model to extract features is weak, resulting in poor model performance. (2) The large scale of model data leads to difficulties deploying on devices with limited resources. Therefore,… More >

  • Open Access

    ARTICLE

    Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

    Sangeeta Yadav1, Preeti Gulia1,*, Nasib Singh Gill1,*, Piyush Kumar Shukla2, Arfat Ahmad Khan3, Sultan Alharby4, Ahmed Alhussen4, Mohd Anul Haq5

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1253-1274, 2024, DOI:10.32604/cmc.2023.042869

    Abstract Inpatient falls from beds in hospitals are a common problem. Such falls may result in severe injuries. This problem can be addressed by continuous monitoring of patients using cameras. Recent advancements in deep learning-based video analytics have made this task of fall detection more effective and efficient. Along with fall detection, monitoring of different activities of the patients is also of significant concern to assess the improvement in their health. High computation-intensive models are required to monitor every action of the patient precisely. This requirement limits the applicability of such networks. Hence, to keep the model lightweight, the already designed… More >

  • Open Access

    ARTICLE

    Multi-Scale Design and Optimization of Composite Material Structure for Heavy-Duty Truck Protection Device

    Yanhui Zhang1, Lianhua Ma1, Hailiang Su1,2,3,*, Jirong Qin2, Zhining Chen2, Kaibiao Deng1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1961-1980, 2024, DOI:10.32604/cmes.2023.045570

    Abstract In this paper, to present a lightweight-developed front underrun protection device (FUPD) for heavy-duty trucks, plain weave carbon fiber reinforced plastic (CFRP) is used instead of the original high-strength steel. First, the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale perspective. For studying the design capability of carbon fiber composite materials, we investigate the effects of TC-33 carbon fiber diameter (D), fiber yarn width (W) and height (H), and fiber yarn density (N) on the front underrun protective beam of carbon fiber composite materials. Based on the investigation, a material-structure matching… More >

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