Farida Asriani^1,2, Azhari Azhari^1,*, Wahyono Wahyono¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3079-3096, 2024, DOI:10.32604/cmc.2024.058193 - 18 November 2024

Abstract Incredible progress has been made in human action recognition (HAR), significantly impacting computer vision applications in sports analytics. However, identifying dynamic and complex movements in sports like badminton remains challenging due to the need for precise recognition accuracy and better management of complex motion patterns. Deep learning techniques like convolutional neural networks (CNNs), long short-term memory (LSTM), and graph convolutional networks (GCNs) improve recognition in large datasets, while the traditional machine learning methods like SVM (support vector machines), RF (random forest), and LR (logistic regression), combined with handcrafted features and ensemble approaches, perform well but… More >

Jingbo Zhang¹, Qiong Wu^1,*, Pingyi Fan², Qiang Fan³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1953-1998, 2024, DOI:10.32604/cmc.2024.057006 - 18 November 2024

Abstract Federated Edge Learning (FEL), an emerging distributed Machine Learning (ML) paradigm, enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data. However, with the development of complex application scenarios such as the Internet of Things (IoT) and Smart Earth, the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands. Therefore, joint resource optimization may be the key solution to the scaling problem. This paper simultaneously addresses the multifaceted challenges of computation and communication, with the growing multiple resource demands. We… More >

Zhenhua Gao¹, Bin Han^1,*, Shengyuan Niu¹, Liying Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-4, 2024, DOI:10.32604/icces.2024.013339

Abstract With the rapid development of industry and globalization, the demand and strategic importance of oil and natural gas have become increasingly significant, leading to energy extraction in more complex corrosive environments [1, 2]. Bimetallic composite pipes, which offer strength and corrosion resistance, exhibit promising potential. For the welding of bimetallic composite plates, it is optimal to follow the welding sequence of the base layer, transition layer, and inner layer [3, 4]. For the welding of bimetal composite pipes, due to the diameter limit, the inner layer is usually welded first, followed by the transition layer,… More >

Wei Song^1,*, Xiaojian Shi², Shoupan Wei²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012236

Abstract Different post-welding treatments, such as TIG-Dressing, blinding, HFMI et.al are often used for steel welded joints in construction machinery manufacturing as an effective and reliable method for fatigue strength improvement. This paper investigates the fatigue performance of thick Q355D cruciform joints in heavy load-carrying steel structures under different treatments. Two TIG-Dressing treatments, blinding and HFMI for the full-penetration welded joints were used for fatigue tests. Experimental tests studied the fatigue strength of cruciform welded joints of Q355D structural steel under different treatments. The geometric parameters and relevant statistical analyses were performed by actual 3D optical More >

Xin Zhang^1,2, Xitao Zheng^1,2, Tiantian Yang³, Mingyu Song^1,2, Yuanyuan Tian⁴, Leilei Yan^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011277

Abstract Composite joints are widely used in machinery industries such as aviation, aerospace, and marine, where they transfer main loads as lightweight connectors. Recently, 3D printing with continuous fibers has relieved the required molds in composite manufacturing process and given flexibility to the design of robust composite joints. However, how the curved paths and variable hatch spaces affect the mechanical properties and failure modes of 3D-printed single-bolt composite joints with continuous fibers remains undisclosed. In this study, 3D printing has been introduced to fabricate three types of continuous fiber-reinforced single-bolt composite joints with different paths, including… More >

Vesal Khean¹, Chomyong Kim², Sunjoo Ryu², Awais Khan¹, Min Kyung Hong³, Eun Young Kim⁴, Joungmin Kim⁵, Yunyoung Nam^3,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 773-787, 2024, DOI:10.32604/cmc.2024.056767 - 15 October 2024

Abstract Human Interaction Recognition (HIR) was one of the challenging issues in computer vision research due to the involvement of multiple individuals and their mutual interactions within video frames generated from their movements. HIR requires more sophisticated analysis than Human Action Recognition (HAR) since HAR focuses solely on individual activities like walking or running, while HIR involves the interactions between people. This research aims to develop a robust system for recognizing five common human interactions, such as hugging, kicking, pushing, pointing, and no interaction, from video sequences using multiple cameras. In this study, a hybrid Deep… More >

Muhammad Ahmad^1,*, Manuel Mazzara², Salvatore Distefano³, Adil Mehmood Khan⁴, Hamad Ahmed Altuwaijri⁵

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 503-532, 2024, DOI:10.32604/cmc.2024.056318 - 15 October 2024

Abstract Disjoint sampling is critical for rigorous and unbiased evaluation of state-of-the-art (SOTA) models e.g., Attention Graph and Vision Transformer. When training, validation, and test sets overlap or share data, it introduces a bias that inflates performance metrics and prevents accurate assessment of a model’s true ability to generalize to new examples. This paper presents an innovative disjoint sampling approach for training SOTA models for the Hyperspectral Image Classification (HSIC). By separating training, validation, and test data without overlap, the proposed method facilitates a fairer evaluation of how well a model can classify pixels it was… More >

Chunyuan Li^1,2,3, Peng Zhang^1,2,3, Shuangming Wang⁴, Lie Liu⁴, Mingquan Shi^2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1197-1214, 2024, DOI:10.32604/cmc.2024.055893 - 15 October 2024

Abstract With the remarkable advancements in machine vision research and its ever-expanding applications, scholars have increasingly focused on harnessing various vision methodologies within the industrial realm. Specifically, detecting vehicle floor welding points poses unique challenges, including high operational costs and limited portability in practical settings. To address these challenges, this paper innovatively integrates template matching and the Faster RCNN algorithm, presenting an industrial fusion cascaded solder joint detection algorithm that seamlessly blends template matching with deep learning techniques. This algorithm meticulously weights and fuses the optimized features of both methodologies, enhancing the overall detection capabilities. Furthermore,… More >

Bayan Alabdullah¹, Muhammad Tayyab², Yahay AlQahtani³, Naif Al Mudawi⁴, Asaad Algarni⁵, Ahmad Jalal², Jeongmin Park^6,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 309-326, 2024, DOI:10.32604/cmc.2024.053538 - 15 October 2024

Abstract In the modern era of a growing population, it is arduous for humans to monitor every aspect of sports, events occurring around us, and scenarios or conditions. This recognition of different types of sports and events has increasingly incorporated the use of machine learning and artificial intelligence. This research focuses on detecting and recognizing events in sequential photos characterized by several factors, including the size, location, and position of people’s body parts in those pictures, and the influence around those people. Common approaches utilized, here are feature descriptors such as MSER (Maximally Stable Extremal Regions),… More >

Ritian Ji¹, Zhiguo Qu^1,*, Hui Wang¹, Binbin Jiao², Yuxin Ye²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012210

Abstract In this manuscript, a finite volume discrete topology optimization method based on the continuous adjoint method is proposed to simulate turbulent flow using the k-omega turbulence model for solving the topology optimization problem of conjugate heat transfer at high Reynolds number. The manuscript simulates the conjugate turbulent convective heat transfer problem at high Reynolds number with a set of Reynolds-Averaged Navier-Stokes (RANS) equations coupled with energy transport equations and control equations of the k-omega turbulence model, and implements the methodology by using the variable density method, interpolates the material values of thermal conductivity, heat capacity,… More >