Thamotharan B^1,*, Venkatraman B², Chandrasekaran S³

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 335-340, 2020, DOI:10.31209/2019.100000156

Abstract Accumulation of impurities within cold trap device results in degradation of efficient performance in a nuclear reactor systems. The impurities have to be identified and the device has to be replaced periodically based on the accumulation level. Though there are a few techniques available to identify these impurities from the cold trap device, there are certain limitations in these techniques. In order to overcome these constraints, a new harmless and easy approach for identifying and separating the impurities using the radiographic images of cold traps is proposed in this paper. It includes a new segmentation algorithm to segregate the deposited… More >

Yonghong Zhang^1,2, Guangyi Ma^1,2,*, Wei Tian³, Jiangeng Wang⁴, Shiwei Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1149-1165, 2020, DOI:10.32604/cmes.2020.010932

Abstract Snow cover is an important parameter in the fields of computer modeling, engineering technology and energy development. With the extensive growth of novel hardware and software compositions creating smart, cyber physical systems’ (CPS) efficient end-to-end workflows. In order to provide accurate snow detection results for the CPS’s terminal, this paper proposed a snow cover detection algorithm based on the unsupervised Gaussian mixture model (GMM) for the FY-4A satellite data. At present, most snow cover detection algorithms mainly utilize the characteristics of the optical spectrum, which is based on the normalized difference snow index (NDSI) with thresholds in different wavebands. These… More >

Li-Hong Juang^a, Ming-Ni Wu^b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 257-266, 2018, DOI:10.1080/10798587.2016.1272778

Abstract In this paper we explore these math approaches for medical image applications. The application of the proposed method for detection tumor will be able to distinguish exactly tumor size and region. In this research, some major design and experimental results of tumor objects detection method for medical brain images is developed to utilize an automatic multi-thresholding method to handle this problem by combining the histogram analysis and the Otsu clustering. The histogram evaluations can decide the superior number of clusters firstly. The Otsu classification algorithm solves the given medical image by continuously separating the input gray-level image by multi-thresholding until… More >

Qing-Hua He^a, Bin Yu^b, Xin Hong^a, Bo Lv^a, Tao Liu^b, Jian Ran^b, Yu-Tian Bi^a

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 223-230, 2018, DOI:10.1080/10798587.2016.1261957

Abstract Lung abnormalities and respiratory diseases increase with the development of urban life. Lung sound analysis provides vital information of the present condition of the pulmonary. But lung sounds are easily interfered by noises in the transmission and record process, then it cannot be used for diagnosis of diseases. So the noised sound should be processed to reduce noises and to enhance the quality of signals received. On the basis of analyzing wavelet packet transform theory and the characteristics of traditional wavelet threshold de-noising method, we proposed a modified threshold selection method based on Particle Swarm Optimization (PSO) and support vector… More >

Nan Pan^1*, Dilin Pan², Yi Liu², Gang Li³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 367-373, 2019, DOI:10.31209/2019.100000098

Abstract A set of laser detection system for shearing tools is developed, By holding breakage of the cable, firstly, using single-point laser displacement sensors to pick up surface features signal of line trace, then wavelet decomposition is used to reduce the noise, and the signal after noise reduction is obtained. After that, the threshold based sequence comparison method is used to achieve matches of similar coincidence for trace features, and then using a gradient descent method to getting the minimum cost of cost function value through continuous iterative, and finally realizing the fast traceability of corresponding shearing tool. More >

Yuheng Sun¹, Ye Mu^{1, 2, 3, 4, *}, Qin Feng⁵, Tianli Hu^{1, 2, 3, 4}, He Gong^{1, 2, 3, 4}, Shijun Li^{1, 2, 3, 4}, Jing Zhou⁶

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1317-1328, 2020, DOI:10.32604/cmc.2020.010510

Abstract In large-scale deer farming image analysis, K-means or maximum betweenclass variance (Otsu) algorithms can be used to distinguish the deer from the background. However, in an actual breeding environment, the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer. Also, when the target and background grey values are similar, the multiple background targets cannot be completely separated. To better identify the posture and behaviour of deer in a deer shed, we used digital image processing to separate the deer from the background. To address the problems… More >

A. Renugambal^{1, *}, K. Selva Bhuvaneswari²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 681-700, 2020, DOI:10.32604/cmc.2020.09519

Abstract In this study, a novel hybrid Water Cycle Moth-Flame Optimization (WCMFO) algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance (MR) image slices. WCMFO constitutes a hybrid between the two techniques, comprising the water cycle and moth-flame optimization algorithms. The optimal thresholds are obtained by maximizing the between class variance (Otsu’s function) of the image. To test the performance of threshold searching process, the proposed algorithm has been evaluated on standard benchmark of ten axial T₂-weighted brain MR images for image segmentation. The experimental outcomes infer that it produces better optimal threshold values at a greater and… More >

Mohamed A. El-Sayed^{1, *}, Abdelmgeid A. Ali², Mohamed E. Hussien³, Hameda A. Sennary³

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 1-16, 2020, DOI:10.32604/cmc.2020.08444

Abstract The essential tool in image processing, computer vision and machine vision is edge detection, especially in the fields of feature extraction and feature detection. Entropy is a basic area in information theory. The entropy, in image processing field has a role associated with image settings. As an initial step in image processing, the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in image. Image segmentation known as the process which divides the image into multiple regions or sets of pixels. Many applications have been development to… More >

D. Benasciutti¹, R. Tovo¹

Structural Durability & Health Monitoring, Vol.2, No.3, pp. 149-164, 2006, DOI:10.3970/sdhm.2006.002.149

Abstract The probability density functions used to characterize the distribution of fatigue cycles in random loads are usually defined over an infinite domain. This means that they give a non-zero probability to count cycles with an infinitely large peak or valley, which however seems of less physical sense. Moreover, practically all the methods existing in the literature completely neglect the negative effect on fatigue strength produced by fatigue cycles with positive mean values. With theses premises, this work tries to further extending the probabilistic theory used by the frequency-domain methods by addressing to distinct problems. First, it tries to include in… More >

C. Colombo¹, M. Guagliano^1,2, L. Vergani¹

Structural Durability & Health Monitoring, Vol.1, No.4, pp. 253-266, 2005, DOI:10.3970/sdhm.2005.001.253

Abstract In this paper the fatigue crack growth properties of a nitrided and shot-peened steel is dealt with: different peening intensities were considered and the resulting residual stresses measured by means of an X-ray diffractometer. Rotating bending fatigue tests were executed on specimens including a blind micro hole, acting as a pre-existent crack. The fracture surface of broken specimens was observed with a SEM to detect the crack growth initiation point. The run-out specimens were broken after the test and the presence of non-propagating cracks detected. The results allowed to determine the propagation threshold of the nitrided and shot peened material. More >