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  • Open Access

    ARTICLE

    Research on Robustness of Charging Station Networks under Multiple Recommended Charging Methods for Electric Vehicles

    Lei Feng1, Miao Liu1, Yexun Yuan1, Chi Zhang2, Peng Geng1,*

    Journal on Internet of Things, Vol.6, pp. 1-16, 2024, DOI:10.32604/jiot.2024.053584

    Abstract With the rapid development of electric vehicles, the requirements for charging stations are getting higher and higher. In this study, we constructed a charging station topology network in Nanjing through the Space-L method, mapping charging stations as network nodes and constructing edges through road relationships. The experiment introduced five EV charging recommendation strategies (based on distance, number of fast charging piles, user preference, price, and overall rating) used to simulate disordered charging caused by different user preferences, and the impact of the network dynamic robustness in case of node failure is explored by simulating the… More >

  • Open Access

    ARTICLE

    MarkNeRF: Watermarking for Neural Radiance Field

    Lifeng Chen1,2, Jia Liu1,2,*, Wenquan Sun1,2, Weina Dong1,2, Xiaozhong Pan1,2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1235-1250, 2024, DOI:10.32604/cmc.2024.051608

    Abstract This paper presents a novel watermarking scheme designed to address the copyright protection challenges encountered with Neural radiation field (NeRF) models. We employ an embedding network to integrate the watermark into the images within the training set. Then, the NeRF model is utilized for 3D modeling. For copyright verification, a secret image is generated by inputting a confidential viewpoint into NeRF. On this basis, design an extraction network to extract embedded watermark images from confidential viewpoints. In the event of suspicion regarding the unauthorized usage of NeRF in a black-box scenario, the verifier can extract More >

  • Open Access

    ARTICLE

    Dynamic Hypergraph Modeling and Robustness Analysis for SIoT

    Yue Wan, Nan Jiang*, Ziyu Liu

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3017-3034, 2024, DOI:10.32604/cmes.2024.051101

    Abstract The Social Internet of Things (SIoT) integrates the Internet of Things (IoT) and social networks, taking into account the social attributes of objects and diversifying the relationship between humans and objects, which overcomes the limitations of the IoT’s focus on associations between objects. Artificial Intelligence (AI) technology is rapidly evolving. It is critical to build trustworthy and transparent systems, especially with system security issues coming to the surface. This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT, aiming to build an SIoT hypergraph generation… More >

  • Open Access

    ARTICLE

    Robust Information Hiding Based on Neural Style Transfer with Artificial Intelligence

    Xiong Zhang1,2, Minqing Zhang1,2,3,*, Xu An Wang1,2,3, Wen Jiang1,2, Chao Jiang1,2, Pan Yang1,4

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1925-1938, 2024, DOI:10.32604/cmc.2024.050899

    Abstract This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission. The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission. The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data. This process effectively enhances the concealment and imperceptibility of confidential information, thereby improving the security of such information during transmission and… More >

  • Open Access

    ARTICLE

    Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

    Yiming Tang1,2, Jianwei Gao1,*, Yifan Huang1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1063-1088, 2024, DOI:10.32604/cmc.2024.049341

    Abstract The α-universal triple I (α-UTI) method is a recognized scheme in the field of fuzzy reasoning, which was proposed by our research group previously. The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent, which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference. Therefore, in this study, the interval robustness (embodied as the interval stability) of the α-UTI method is explored in the interval-valued fuzzy environment. To begin with, the stability of the α-UTI method is explored for the… More >

  • Open Access

    ARTICLE

    A Robust Conformer-Based Speech Recognition Model for Mandarin Air Traffic Control

    Peiyuan Jiang1, Weijun Pan1,*, Jian Zhang1, Teng Wang1, Junxiang Huang2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 911-940, 2023, DOI:10.32604/cmc.2023.041772

    Abstract

    This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition (ASR) technology in the Air Traffic Control (ATC) field. This paper presents a novel cascaded model architecture, namely Conformer-CTC/Attention-T5 (CCAT), to build a highly accurate and robust ATC speech recognition model. To tackle the challenges posed by noise and fast speech rate in ATC, the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms. On the decoding side, the Attention mechanism is integrated to facilitate precise alignment between input features and

    More >

  • Open Access

    ARTICLE

    Deep Facial Emotion Recognition Using Local Features Based on Facial Landmarks for Security System

    Youngeun An, Jimin Lee, EunSang Bak*, Sungbum Pan*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1817-1832, 2023, DOI:10.32604/cmc.2023.039460

    Abstract Emotion recognition based on facial expressions is one of the most critical elements of human-machine interfaces. Most conventional methods for emotion recognition using facial expressions use the entire facial image to extract features and then recognize specific emotions through a pre-trained model. In contrast, this paper proposes a novel feature vector extraction method using the Euclidean distance between the landmarks changing their positions according to facial expressions, especially around the eyes, eyebrows, nose, and mouth. Then, we apply a new classifier using an ensemble network to increase emotion recognition accuracy. The emotion recognition performance was More >

  • Open Access

    ARTICLE

    Adversarial Attack-Based Robustness Evaluation for Trustworthy AI

    Eungyu Lee, Yongsoo Lee, Taejin Lee*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1919-1935, 2023, DOI:10.32604/csse.2023.039599

    Abstract Artificial Intelligence (AI) technology has been extensively researched in various fields, including the field of malware detection. AI models must be trustworthy to introduce AI systems into critical decision-making and resource protection roles. The problem of robustness to adversarial attacks is a significant barrier to trustworthy AI. Although various adversarial attack and defense methods are actively being studied, there is a lack of research on robustness evaluation metrics that serve as standards for determining whether AI models are safe and reliable against adversarial attacks. An AI model’s robustness level cannot be evaluated by traditional evaluation… More >

  • Open Access

    ARTICLE

    Influence of High-Robustness Polycarboxylate Superplasticizer on the Performances of Concrete Incorporating Fly Ash and Manufactured Sand

    Panpan Cao1,2, Xiulin Huang1,3,*, Shenxu Bao4, Jin Yang5,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2041-2051, 2023, DOI:10.32604/fdmp.2023.027399

    Abstract Using ethylene glycol monovinyl polyoxyethylene ether, 2-acrylamido-2-methylpropane sulfonic acid (AMPS) and acrylic acid as the main synthetic monomers, a high robustness polycarboxylate superplasticizer was prepared. The effects of initial temperature, ratio of acid to ether, amount of chain transfer agent, and synthesis process on the properties of the superplasticizer were studied. The molecular structure was characterized by GPC (Gel Permeation Chromatography) and IR (Infrared Spectrometer). As shown by the results, when the initial reaction temperature is 15°C, the ratio of acid to ether is 3.4:1 and the acrylic acid pre-neutralization is 15%, The AMPS substitution More > Graphic Abstract

    Influence of High-Robustness Polycarboxylate Superplasticizer on the Performances of Concrete Incorporating Fly Ash and Manufactured Sand

  • Open Access

    ARTICLE

    AC-DC Fuzzy Linear Active Disturbance Rejection Control Strategy of Front Stage of Bidirectional Converter Based on V2G

    Guosheng Li1, Qingquan Lv2, Zhenzhen Zhang2, Haiying Dong1,*

    Energy Engineering, Vol.120, No.4, pp. 1045-1065, 2023, DOI:10.32604/ee.2023.023770

    Abstract Aiming at the problems of output voltage fluctuation and current total harmonic distortion (THD) in the front stage totem-pole bridgeless PFC of two-stage V2G (Vehicle to Grid) vehicle-mounted bi-directional converter, a fuzzy linear active disturbance rejection control strategy for V2G front-stage AC-DC power conversion system is proposed. Firstly, the topological working mode of the totem-pole bridgeless PFC is analyzed, and the mathematical model is established. Combined with the system model and the linear active disturbance rejection theory, a double closed-loop controller is designed with the second-order linear active disturbance rejection control as the voltage outer More > Graphic Abstract

    AC-DC Fuzzy Linear Active Disturbance Rejection Control Strategy of Front Stage of Bidirectional Converter Based on V2G

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