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  • Open Access

    ARTICLE

    A Hybrid Feature Fusion Traffic Sign Detection Algorithm Based on YOLOv7

    Bingyi Ren1,4, Juwei Zhang2,3,4,*, Tong Wang2,4

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1425-1440, 2024, DOI:10.32604/cmc.2024.052667

    Abstract Autonomous driving technology has entered a period of rapid development, and traffic sign detection is one of the important tasks. Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced, and traffic sign targets are small and have unclear features, which makes detection more difficult. Therefore, we propose a Hybrid Feature Fusion Traffic Sign detection algorithm based on YOLOv7 (HFFT-YOLO). First, a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales; Secondly, the cross-scale fusion part of the neck introduces a… More >

  • Open Access

    ARTICLE

    Sentiment Analysis Using E-Commerce Review Keyword-Generated Image with a Hybrid Machine Learning-Based Model

    Jiawen Li1,2, Yuesheng Huang1, Yayi Lu1, Leijun Wang1,*, Yongqi Ren1, Rongjun Chen1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1581-1599, 2024, DOI:10.32604/cmc.2024.052666

    Abstract In the context of the accelerated pace of daily life and the development of e-commerce, online shopping is a mainstream way for consumers to access products and services. To understand their emotional expressions in facing different shopping experience scenarios, this paper presents a sentiment analysis method that combines the e-commerce review keyword-generated image with a hybrid machine learning-based model, in which the Word2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence (AI). Subsequently, a hybrid Convolutional Neural Network and Support Vector Machine (CNN-SVM) model… More >

  • Open Access

    ARTICLE

    Two Stages Segmentation Algorithm of Breast Tumor in DCE-MRI Based on Multi-Scale Feature and Boundary Attention Mechanism

    Bing Li1,2,*, Liangyu Wang1, Xia Liu1,2, Hongbin Fan1, Bo Wang3, Shoudi Tong1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1543-1561, 2024, DOI:10.32604/cmc.2024.052009

    Abstract Nuclear magnetic resonance imaging of breasts often presents complex backgrounds. Breast tumors exhibit varying sizes, uneven intensity, and indistinct boundaries. These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation. Thus, we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms. Initially, the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs. Subsequently, we devise a fusion network incorporating multi-scale features and boundary attention mechanisms for breast tumor segmentation. We incorporate multi-scale parallel dilated convolution modules into… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things: A Hybrid Approach

    Amal Al-Rasheed1, Rahim Khan2,3,*, Tahani Alsaed4, Mahwish Kundi2,5, Mohamad Hanif Md. Saad6, Mahidur R. Sarker7,8

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1305-1323, 2024, DOI:10.32604/cmc.2024.049215

    Abstract Due to the overwhelming characteristics of the Internet of Things (IoT) and its adoption in approximately every aspect of our lives, the concept of individual devices’ privacy has gained prominent attention from both customers, i.e., people, and industries as wearable devices collect sensitive information about patients (both admitted and outdoor) in smart healthcare infrastructures. In addition to privacy, outliers or noise are among the crucial issues, which are directly correlated with IoT infrastructures, as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing, i.e.,… More >

  • Open Access

    ARTICLE

    Hybrid Multi-Infeed Interaction Factor Calculation Method Considering Voltage Regulation Control Characteristics of Voltage Source Converter

    Shan Liu1, Chengbin Chi1, Fengze Han2, Yanan Wu1, Lin Zhu1, Tuo Wang2,*

    Energy Engineering, Vol.121, No.8, pp. 2257-2273, 2024, DOI:10.32604/ee.2024.049861

    Abstract Voltage source converter based high voltage direct current (VSC-HVDC) can participate in voltage regulation by flexible control to help maintain the voltage stability of the power grid. In order to quantitatively evaluate its influence on the voltage interaction between VSC-HVDC and line commutated converter based high voltage direct current (LCC-HVDC), this paper proposes a hybrid multi-infeed interaction factor (HMIIF) calculation method considering the voltage regulation control characteristics of VSC-HVDC. Firstly, for a hybrid multi-infeed high voltage direct current system, an additional equivalent operating admittance matrix is constructed to characterize HVDC equipment characteristics under small disturbance.… More >

  • Open Access

    ARTICLE

    Synergism of Zinc Oxide/Organoclay-Loaded Poly(lactic acid) Hybrid Nanocomposite Plasticized by Triacetin for Sustainable Active Food Packaging

    Ponusa Songtipya1,2,*, Thummanoon Prodpran1,2, Ladawan Songtipya1,2, Theerarat Sengsuk1

    Journal of Renewable Materials, Vol.12, No.5, pp. 951-967, 2024, DOI:10.32604/jrm.2024.049068

    Abstract The synergistic effect of organoclay (OC) and zinc oxide (ZnO) nanoparticles on the crucial properties of poly(lactic acid) (PLA) nanocomposite films was systematically investigated herein. After their incorporation into PLA via the solvent casting technique, the water vapor barrier property of the PLA/OC/ZnO film improved by a maximum of 86% compared to the neat PLA film without the deterioration of Young’s modulus or the tensile strength. Moreover, the film’s self-antibacterial activity against foodborne pathogens, including gram-negative (Escherichia coli, E. coli) and gram-positive (Staphylococcus aureus, S. aureus) bacteria, was enhanced by a maximum of approximately 98–99% compared to the neat… More > Graphic Abstract

    Synergism of Zinc Oxide/Organoclay-Loaded Poly(lactic acid) Hybrid Nanocomposite Plasticized by Triacetin for Sustainable Active Food Packaging

  • Open Access

    ARTICLE

    Microarray Gene Expression Classification: An Efficient Feature Selection Using Hybrid Swarm Intelligence Algorithm

    Punam Gulande*, R. N. Awale

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 937-952, 2024, DOI:10.32604/csse.2024.046123

    Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

  • Open Access

    ARTICLE

    Evaluations of Chris-Jerry Data Using Generalized Progressive Hybrid Strategy and Its Engineering Applications

    Refah Alotaibi1, Hoda Rezk2, Ahmed Elshahhat3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3073-3103, 2024, DOI:10.32604/cmes.2024.050606

    Abstract A new one-parameter Chris-Jerry distribution, created by mixing exponential and gamma distributions, is discussed in this article in the presence of incomplete lifetime data. We examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry (CJ) distribution. When the indicated censored data is present, Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices, including the hazard rate and reliability functions. We acquire the estimated asymptotic and credible confidence intervals of each unknown quantity. More >

  • Open Access

    ARTICLE

    Optimizing Hybrid Fibre-Reinforced Polymer Bars Design: A Machine Learning Approach

    Aneel Manan1, Pu Zhang1,*, Shoaib Ahmad2, Jawad Ahmad2

    Journal of Polymer Materials, Vol.41, No.1, pp. 15-44, 2024, DOI:10.32604/jpm.2024.053859

    Abstract Fiber-reinforced polymer (FRP) bars are gaining popularity as an alternative to steel reinforcement due to their advantages such as corrosion resistance and high strength-to-weight ratio. However, FRP has a lower modulus of elasticity compared to steel. Therefore, special attention is required in structural design to address deflection related issues and ensure ductile failure. This research explores the use of machine learning algorithms such as gene expression programming (GEP) to develop a simple and effective equation for predicting the elastic modulus of hybrid fiber-reinforced polymer (HFPR) bars. A comprehensive database of 125 experimental results of HFPR… More >

  • Open Access

    ARTICLE

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

    Djeldjli Halima1,*, Benatiallah Djelloul1, Ghasri Mehdi2, Tanougast Camel3, Benatiallah Ali4, Benabdelkrim Bouchra1

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002

    Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract

    Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

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