Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (573)
  • Open Access

    ARTICLE

    A Novel Framework for Learning and Classifying the Imbalanced Multi-Label Data

    P. K. A. Chitra1, S. Appavu alias Balamurugan2, S. Geetha3, Seifedine Kadry4,5,6, Jungeun Kim7,*, Keejun Han8

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1367-1385, 2024, DOI:10.32604/csse.2023.034373

    Abstract A generalization of supervised single-label learning based on the assumption that each sample in a dataset may belong to more than one class simultaneously is called multi-label learning. The main objective of this work is to create a novel framework for learning and classifying imbalanced multi-label data. This work proposes a framework of two phases. The imbalanced distribution of the multi-label dataset is addressed through the proposed Borderline MLSMOTE resampling method in phase 1. Later, an adaptive weighted l21 norm regularized (Elastic-net) multi-label logistic regression is used to predict unseen samples in phase 2. The proposed… More >

  • Open Access

    ARTICLE

    YOLO-RLC: An Advanced Target-Detection Algorithm for Surface Defects of Printed Circuit Boards Based on YOLOv5

    Yuanyuan Wang1,2,*, Jialong Huang1, Md Sharid Kayes Dipu1, Hu Zhao3, Shangbing Gao1,2, Haiyan Zhang1,2, Pinrong Lv1

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4973-4995, 2024, DOI:10.32604/cmc.2024.055839

    Abstract Printed circuit boards (PCBs) provide stable connections between electronic components. However, defective printed circuit boards may cause the entire equipment system to malfunction, resulting in incalculable losses. Therefore, it is crucial to detect defective printed circuit boards during the generation process. Traditional detection methods have low accuracy in detecting subtle defects in complex background environments. In order to improve the detection accuracy of surface defects on industrial printed circuit boards, this paper proposes a residual large kernel network based on YOLOv5 (You Only Look Once version 5) for PCBs surface defect detection, called YOLO-RLC (You… More >

  • Open Access

    ARTICLE

    Enhanced UAV Pursuit-Evasion Using Boids Modelling: A Synergistic Integration of Bird Swarm Intelligence and DRL

    Weiqiang Jin1,#, Xingwu Tian1,#, Bohang Shi1, Biao Zhao1,*, Haibin Duan2, Hao Wu3

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3523-3553, 2024, DOI:10.32604/cmc.2024.055125

    Abstract The UAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles (UAVs), which is pivotal in public safety applications, particularly in scenarios involving intrusion monitoring and interception. To address the challenges of data acquisition, real-world deployment, and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks, we propose an innovative swarm intelligence-based UAV pursuit-evasion control framework, namely “Boids Model-based DRL Approach for Pursuit and Escape” (Boids-PE), which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning (DRL). The Boids model, which simulates collective… More >

  • Open Access

    ARTICLE

    Leveraging Uncertainty for Depth-Aware Hierarchical Text Classification

    Zixuan Wu1, Ye Wang1,*, Lifeng Shen2, Feng Hu1, Hong Yu1,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4111-4127, 2024, DOI:10.32604/cmc.2024.054581

    Abstract Hierarchical Text Classification (HTC) aims to match text to hierarchical labels. Existing methods overlook two critical issues: first, some texts cannot be fully matched to leaf node labels and need to be classified to the correct parent node instead of treating leaf nodes as the final classification target. Second, error propagation occurs when a misclassification at a parent node propagates down the hierarchy, ultimately leading to inaccurate predictions at the leaf nodes. To address these limitations, we propose an uncertainty-guided HTC depth-aware model called DepthMatch. Specifically, we design an early stopping strategy with uncertainty to More >

  • Open Access

    ARTICLE

    A Quarterly High RFM Mining Algorithm for Big Data Management

    Cuiwei Peng1, Jiahui Chen2,*, Shicheng Wan3, Guotao Xu4

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4341-4360, 2024, DOI:10.32604/cmc.2024.054109

    Abstract In today’s highly competitive retail industry, offline stores face increasing pressure on profitability. They hope to improve their ability in shelf management with the help of big data technology. For this, on-shelf availability is an essential indicator of shelf data management and closely relates to customer purchase behavior. RFM (recency, frequency, and monetary) pattern mining is a powerful tool to evaluate the value of customer behavior. However, the existing RFM pattern mining algorithms do not consider the quarterly nature of goods, resulting in unreasonable shelf availability and difficulty in profit-making. To solve this problem, we… More >

  • Open Access

    ARTICLE

    Value Function Mechanism in WSNs-Based Mango Plantation Monitoring System

    Wen-Tsai Sung1, Indra Griha Tofik Isa1,2, Sung-Jung Hsiao3,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3733-3759, 2024, DOI:10.32604/cmc.2024.053634

    Abstract Mango fruit is one of the main fruit commodities that contributes to Taiwan’s income. The implementation of technology is an alternative to increasing the quality and quantity of mango plantation product productivity. In this study, a Wireless Sensor Networks (“WSNs”)-based intelligent mango plantation monitoring system will be developed that implements deep reinforcement learning (DRL) technology in carrying out prediction tasks based on three classifications: “optimal,” “sub-optimal,” or “not-optimal” conditions based on three parameters including humidity, temperature, and soil moisture. The key idea is how to provide a precise decision-making mechanism in the real-time monitoring system.… More >

  • Open Access

    ARTICLE

    Improving Low-Resource Machine Translation Using Reinforcement Learning from Human Feedback

    Liqing Wang*, Yiheng Xiao

    Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 619-631, 2024, DOI:10.32604/iasc.2024.052971

    Abstract Neural Machine Translation is one of the key research directions in Natural Language Processing. However, limited by the scale and quality of parallel corpus, the translation quality of low-resource Neural Machine Translation has always been unsatisfactory. When Reinforcement Learning from Human Feedback (RLHF) is applied to low-resource machine translation, commonly encountered issues of substandard preference data quality and the higher cost associated with manual feedback data. Therefore, a more cost-effective method for obtaining feedback data is proposed. At first, optimizing the quality of preference data through the prompt engineering of the Large Language Model (LLM), More >

  • Open Access

    ARTICLE

    Numerical Study of Temperature-Dependent Viscosity and Thermal Conductivity of Micropolar Ag–MgO Hybrid Nanofluid over a Rotating Vertical Cone

    Mekonnen S. Ayano1,*, Thokozani N. Khumalo1, Stephen T. Sikwila2, Stanford Shateyi3

    Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1153-1169, 2024, DOI:10.32604/fhmt.2024.048474

    Abstract The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver ()−Magnesium oxide () hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone, with the influence of transverse magnetic field and thermal radiation. The physical flow problem has been modeled with coupled partial differential equations. We apply similarity transformations to the non-dimensionalized equations, and the resulting nonlinear differential equations are solved using overlapping grid multidomain spectral quasilinearization method. The flow behavior for the fluid is scrutinized under the impact of diverse physical constraints, which are illustrated graphically. The More >

  • Open Access

    ARTICLE

    A Linked List Encryption Scheme for Image Steganography without Embedding

    Pengbiao Zhao1, Qi Zhong2, Jingxue Chen1, Xiaopei Wang3, Zhen Qin1, Erqiang Zhou1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 331-352, 2024, DOI:10.32604/cmes.2024.050148

    Abstract Information steganography has received more and more attention from scholars nowadays, especially in the area of image steganography, which uses image content to transmit information and makes the existence of secret information undetectable. To enhance concealment and security, the Steganography without Embedding (SWE) method has proven effective in avoiding image distortion resulting from cover modification. In this paper, a novel encrypted communication scheme for image SWE is proposed. It reconstructs the image into a multi-linked list structure consisting of numerous nodes, where each pixel is transformed into a single node with data and pointer domains.… More >

  • Open Access

    ARTICLE

    Applying the Shearlet-Based Complexity Measure for Analyzing Mass Transfer in Continuous-Flow Microchannels

    Elena Mosheva1,*, Ivan Krasnyakov2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1743-1758, 2024, DOI:10.32604/fdmp.2024.049146

    Abstract Continuous-flow microchannels are widely employed for synthesizing various materials, including nanoparticles, polymers, and metal-organic frameworks (MOFs), to name a few. Microsystem technology allows precise control over reaction parameters, resulting in purer, more uniform, and structurally stable products due to more effective mass transfer manipulation. However, continuous-flow synthesis processes may be accompanied by the emergence of spatial convective structures initiating convective flows. On the one hand, convection can accelerate reactions by intensifying mass transfer. On the other hand, it may lead to non-uniformity in the final product or defects, especially in MOF microcrystal synthesis. The ability… More > Graphic Abstract

    Applying the Shearlet-Based Complexity Measure for Analyzing Mass Transfer in Continuous-Flow Microchannels

Displaying 1-10 on page 1 of 573. Per Page