Tianzhe Jiao, Chaopeng Guo, Xiaoyue Feng, Yuming Chen, Jie Song^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1-35, 2024, DOI:10.32604/cmc.2024.053204

Abstract Multi-modal fusion technology gradually become a fundamental task in many fields, such as autonomous driving, smart healthcare, sentiment analysis, and human-computer interaction. It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities. Under complex scenes, multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions. However, achieving outstanding performance is challenging because of equipment performance limitations, missing information, and data noise. This paper comprehensively reviews existing methods based on multi-modal fusion techniques and completes a detailed and in-depth analysis.… More >

Dinh Phu Cuong Le^1,2, Dong Wang¹, Viet-Tuan Le^3,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 37-60, 2024, DOI:10.32604/cmc.2024.050790

Abstract Transformer models have emerged as dominant networks for various tasks in computer vision compared to Convolutional Neural Networks (CNNs). The transformers demonstrate the ability to model long-range dependencies by utilizing a self-attention mechanism. This study aims to provide a comprehensive survey of recent transformer-based approaches in image and video applications, as well as diffusion models. We begin by discussing existing surveys of vision transformers and comparing them to this work. Then, we review the main components of a vanilla transformer network, including the self-attention mechanism, feed-forward network, position encoding, etc. In the main part of More >

Ahmed Khalid¹, Rana Asif Rehman¹, Byung-Seo Kim^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 61-103, 2024, DOI:10.32604/cmc.2024.049981

Abstract Wireless Ad Hoc Networks consist of devices that are wirelessly connected. Mobile Ad Hoc Networks (MANETs), Internet of Things (IoT), and Vehicular Ad Hoc Networks (VANETs) are the main domains of wireless ad hoc network. Internet is used in wireless ad hoc network. Internet is based on Transmission Control Protocol (TCP)/Internet Protocol (IP) network where clients and servers interact with each other with the help of IP in a pre-defined environment. Internet fetches data from a fixed location. Data redundancy, mobility, and location dependency are the main issues of the IP network paradigm. All these… More >

Deepak Upreti¹, Eunmok Yang², Hyunil Kim^3,*, Changho Seo^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2239-2274, 2024, DOI:10.32604/cmes.2024.048932

Abstract Federated learning is an innovative machine learning technique that deals with centralized data storage issues while maintaining privacy and security. It involves constructing machine learning models using datasets spread across several data centers, including medical facilities, clinical research facilities, Internet of Things devices, and even mobile devices. The main goal of federated learning is to improve robust models that benefit from the collective knowledge of these disparate datasets without centralizing sensitive information, reducing the risk of data loss, privacy breaches, or data exposure. The application of federated learning in the healthcare industry holds significant promise More >

Khaldon Azzam Kordi¹, Mardeni Roslee^1,*, Mohamad Yusoff Alias¹, Abdulraqeb Alhammadi², Athar Waseem³, Anwar Faizd Osman⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3261-3298, 2024, DOI:10.32604/cmc.2024.044890

Abstract This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning. It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this research explores the integration of multiple sensor modalities (e.g., Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expand indoor localization methods, particularly in obstructed environments. It addresses the challenge of precise object localization, introducing a novel hybrid DL approach using received signal information (RSI), Received Signal Strength (RSS), and Channel State Information (CSI) data… More >

Hao Jiang¹, Yuerong Liao¹, Dongdong Zhao², Wenjian Luo³, Xingyi Zhang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1045-1075, 2024, DOI:10.32604/cmes.2024.048653

Abstract Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the… More >

Xianwei Jiang¹, Yanqiong Zhang^1,*, Juan Lei¹, Yudong Zhang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1-40, 2024, DOI:10.32604/cmes.2024.047649

Abstract Research on Chinese Sign Language (CSL) provides convenience and support for individuals with hearing impairments to communicate and integrate into society. This article reviews the relevant literature on Chinese Sign Language Recognition (CSLR) in the past 20 years. Hidden Markov Models (HMM), Support Vector Machines (SVM), and Dynamic Time Warping (DTW) were found to be the most commonly employed technologies among traditional identification methods. Benefiting from the rapid development of computer vision and artificial intelligence technology, Convolutional Neural Networks (CNN), 3D-CNN, YOLO, Capsule Network (CapsNet) and various deep neural networks have sprung up. Deep Neural… More >

Pengjun Li¹, Qixin Zhao¹, Yingmin Liu¹, Chao Zhong¹, Jinlong Wang^1,*, Zhihan Lyu²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3825-3865, 2024, DOI:10.32604/cmc.2024.046851

Abstract Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order. Amidst the challenges posed by intricate and unpredictable risk factors, knowledge graph technology is effectively driving risk management, leveraging its ability to associate and infer knowledge from diverse sources. This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios. Firstly, employing bibliometric methods, the aim is to uncover the developmental trends and current research hotspots within the… More >

Yuming Tang^1,#, Yitian Zhang^2,#, Tao Niu¹, Zhen Li^2,3,*, Zijian Zhang^1,3, Huaping Chen⁴, Long Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2451-2477, 2024, DOI:10.32604/cmes.2024.030084

Abstract Federated Learning (FL), as an emergent paradigm in privacy-preserving machine learning, has garnered significant interest from scholars and engineers across both academic and industrial spheres. Despite its innovative approach to model training across distributed networks, FL has its vulnerabilities; the centralized server-client architecture introduces risks of single-point failures. Moreover, the integrity of the global model—a cornerstone of FL—is susceptible to compromise through poisoning attacks by malicious actors. Such attacks and the potential for privacy leakage via inference starkly undermine FL’s foundational privacy and security goals. For these reasons, some participants unwilling use their private data… More >

Ruirui Zhang¹, Xuguang Zhang², Minxin Yang³, Haoran Zhang^4,5,*

International Journal of Mental Health Promotion, Vol.26, No.2, pp. 117-126, 2024, DOI:10.32604/ijmhp.2023.045819

Abstract Contingent self-esteem captures the fragile nature of self-esteem and is often regarded as suboptimal to psychological functioning. Self-compassion is another important self-related concept assumed to promote mental health and well-being. However, research on the relation of self-compassion to contingent self-esteem is lacking. Two studies were conducted to explore the role of self-compassion, either as a personal characteristic or an induced mindset, in influencing the effects of contingent self-esteem on well-being. Study 1 recruited 256 Chinese college students (30.4% male, mean age = 21.72 years) who filled out measures of contingent self-esteem, self-compassion, and well-being. The… More >