Shubin Zheng^1,3, Yue Wang², Liming Li^2,3,*, Xieqi Chen^2,3, Lele Peng^2,3, Zhanhao Shang²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 565-592, 2024, DOI:10.32604/cmes.2023.043832

Abstract Regular fastener detection is necessary to ensure the safety of railways. However, the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways. Existing supervised inspection methods have insufficient detection ability in cases of imbalanced samples. To solve this problem, we propose an approach based on deep convolutional neural networks (DCNNs), which consists of three stages: fastener localization, abnormal fastener sample generation based on saliency detection, and fastener state inspection. First, a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions. Then, the foreground clip region of a fastener image… More >

Jun Shu^1,2, Shuai Wang^1,2, Shiqi Yu^1,2, Jie Zhang^3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2677-2697, 2023, DOI:10.32604/cmc.2023.045818

Abstract Traditional models for semantic segmentation in point clouds primarily focus on smaller scales. However, in real-world applications, point clouds often exhibit larger scales, leading to heavy computational and memory requirements. The key to handling large-scale point clouds lies in leveraging random sampling, which offers higher computational efficiency and lower memory consumption compared to other sampling methods. Nevertheless, the use of random sampling can potentially result in the loss of crucial points during the encoding stage. To address these issues, this paper proposes cross-fusion self-attention network (CFSA-Net), a lightweight and efficient network architecture specifically designed for directly processing large-scale point clouds.… More >

Ye-Yeon Kang¹, Geon Park¹, Hyun Yoo², Kyungyong Chung^1,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3619-3635, 2023, DOI:10.32604/cmc.2023.043566

Abstract Object tracking, an important technology in the field of image processing and computer vision, is used to continuously track a specific object or person in an image. This technology may be effective in identifying the same person within one image, but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same. When tracking the same object using two or more images, there must be a way to determine that objects existing in different images are the same object. Therefore, this paper attempts to determine the same object… More >

Xiangqun Li^1,*, Jiawen Liang², Jinyu Zhu², Shengping Shi², Fangyu Ding², Jianpeng Sun², Bo Liu²

Energy Engineering, Vol.121, No.1, pp. 203-219, 2024, DOI:10.32604/ee.2023.029295

Abstract To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis, this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition (VMD), fuzzy entropy (FE) and fuzzy clustering (FC). Firstly, based on the OTDR curve data collected in the field, VMD is used to extract the different modal components (IMF) of the original signal and calculate the fuzzy entropy (FE) values of different components to characterize the subtle differences between them. The fuzzy entropy of each curve is used as the feature vector, which… More >

Bah Mamoudou^*

Journal on Artificial Intelligence, Vol.5, pp. 163-180, 2023, DOI:10.32604/jai.2023.045324

Abstract It has become an annual tradition for Convolutional Neural Networks (CNNs) to continuously improve their performance in image classification and other applications. These advancements are often attributed to the adoption of more intricate network architectures, such as modules and skip connections, as well as the practice of stacking additional layers to create increasingly complex networks. However, the quest to identify the most optimized model is a daunting task, given that state of the art Convolutional Neural Network (CNN) models are manually engineered. In this research paper, we leveraged a conventional Genetic Algorithm (GA) to craft optimized Convolutional Neural Network (CNN)… More >

Wimonmas Bamrungsetthapong¹, Pramote Charongrattanasakul^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2471-2495, 2024, DOI:10.32604/cmes.2023.031433

Abstract This study presents the design of a modified attributed control chart based on a double sampling (DS) np chart applied in combination with generalized multiple dependent state (GMDS) sampling to monitor the mean life of the product based on the time truncated life test employing the Weibull distribution. The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing. Three control limit levels are used: the warning control limit, inner control limit, and outer control limit. Together, they enhance the capability for variation detection. A genetic algorithm can be used… More >

Longteng Liang^1,2,3, Zhouquan Feng^2,4,*, Hongyi Zhang^2,4, Zhengqing Chen^2,4, Changzhao Qian^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2403-2419, 2024, DOI:10.32604/cmes.2023.031260

Abstract Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to their exceptional damping performance and durability. However, the existing constitutive models present challenges to the widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA) software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing a new constitutive model that is both easily understandable and user-friendly for FEA software. By utilizing numerical results obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture the nonlinear behavior of ECDs. The effectiveness… More >

Ayla Ocak¹, Ümit Işıkdağ², Gebrail Bekdaş^1,*, Sinan Melih Nigdeli¹, Sanghun Kim³, Zong Woo Geem^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2899-2924, 2024, DOI:10.32604/cmes.2023.030418

Abstract Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures. The base isolators may lose their damping capacity over time due to environmental or dynamic effects. This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-term isolator life. In this study, an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time. With the developed model, the required damping capacity of the isolator structure was estimated and compared… More >

Suripeddi Srinivas^a , Akshay Gupta^b,*, Ashish Kumar Kandoi^b

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-12, 2014, DOI:10.5098/hmt.5.21

Abstract The present work deals with the flow and thermal analysis of nanofluid in the wavy channels. The governing flow equations are solved numerically using CFD package assuming single phase approach. To study the effect of the concentration and size variation of the nanoparticle, the concentration and size are varied from 0% - 5% and 25 nm - 100 nm respectively over the Reynolds number range of 250-1500 for Au-water nanofluid. The effect on heat transfer enhancement because of corrugation of wavy channel is analyzed on four different shapes (sinusoidal, triangular, trapezoidal and square) channels. The effect of amplitude of the… More >

Yuanjun Dai^1,2,*, Xin Wei¹, Baohua Li¹, Cong Wang¹, Kunju Shi¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.2, pp. 337-348, 2024, DOI:10.32604/fdmp.2023.042434

Abstract To study the impact of the trailing-edge wear on the vibrational behavior of wind-turbine blades, unworn blades and trailing-edge worn blades have been assessed through relevant modal tests. According to these experiments, the natural frequencies of trailing-edge worn blades −1, −2, and −3 increase the most in the second to fourth order, the fifth order increases in the middle, and the first order increases the least. The damping ratio data indicate that, in general, the first five-order damping ratios of trailing-edge worn blades −1 and trailing-edge worn blades −2 are reduced, and the first five-order damping ratios of trailing-edge worn… More >