A. Joshuva¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 69-90, 2017, DOI:10.3970/sdhm.2017.012.069

Abstract Renewable energy sources are considered much in energy fields because of the contemporary energy calamities. Among the important alternatives being considered, wind energy is a durable competitor because of its dependability due to the development of the innovations, comparative cost effectiveness and great framework. To yield wind energy more proficiently, the structure of wind turbines has turned out to be substantially bigger, creating conservation and renovation works troublesome. Due to various ecological conditions, wind turbine blades are subjected to vibration and it leads to failure. If the failure is not diagnosed early, it will lead to catastrophic damage to the… More >

Yuxiang Huang¹, Chuliu He¹, Jiaqiu Wang², Yuehong Miao¹, Tongjin Zhu¹, Ping Zhou¹, Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.15, No.2, pp. 117-125, 2018, DOI: 10.3970/mcb.2018.02478

Abstract Intravascular optical coherence tomography (IVOCT) is becoming more and more popular in clinical diagnosis of coronary atherosclerotic. However, reading IVOCT images is of large amount of work. This article describes a method based on image feature extraction and support vector machine (SVM) to achieve semi-automatic segmentation of IVOCT images. The image features utilized in this work including light attenuation coefficients and image textures based on gray level co-occurrence matrix. Different sets of hyper-parameters and image features were tested. This method achieved an accuracy of 83% on the test images. Single class accuracy of 89% for fibrous, 79.3% for calcification and… More >

Chunliu He¹, Jiaqiu Wang², Yuxiang Huang¹, Tongjing Zhu¹, Yuehong Miao¹, Zhiyong Li^1,2*

Molecular & Cellular Biomechanics, Vol.13, No.1, pp. 23-36, 2016, DOI:10.3970/mcb.2016.013.027

Abstract Fibrous cap thickness (FCT) is seen as critical to plaque vulnerability. Therefore, the development of automatic algorithms for the quantification of FCT is for estimating cardiovascular risk of patients. Intravascular optical coherence tomography (IVOCT) is currently the only in vivo imaging modality with which FCT, the critical component of plaque vulnerability, can be assessed accurately. This study was aimed to discussion the correlation between the texture features of OCT images and the FCT in lipid-rich atheroma. Methods: Firstly, a full automatic segmentation algorithm based on unsupervised fuzzy c means (FCM) clustering with geometric constrains was developed to segment the ROIs… More >

Maoyang Zou^1,2, Jinrong Hu², Huan Zhang², Xi Wu², Jia He², Zhijie Xu³, Yong Zhong^1,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 511-525, 2019, DOI:10.32604/cmc.2019.05912

Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More >

Yi Zheng^1,2, Wentao Zhao^2,*, Chengcheng Sun², Qian Li¹

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 481-496, 2019, DOI:10.32604/cmc.2019.05536

Abstract Drug side-effects impose massive costs on society, leading to almost one-third drug failure in the drug discovery process. Therefore, early identification of potential side-effects becomes vital to avoid risks and reduce costs. Existing computational methods employ few drug features and predict drug side-effects from either drug side or side-effect side separately. In this work, we explore to predict drug side-effects by combining heterogeneous drug features and employing the bipartite local models (BLMs) which fuse predictions from both the drug side and side-effect side. Specifically, we integrate drug chemical structures, drug interacted proteins and drug associated genes into a unified framework… More >

Wei Sun^1,3,*, Hongji Du¹, Shoubai Nie^2,3, Xiaozheng He⁴

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 147-161, 2019, DOI:10.32604/cmc.2019.03581

Abstract Traffic sign recognition (TSR), as a critical task to automated driving and driver assistance systems, is challenging due to the color fading, motion blur, and occlusion. Traditional methods based on convolutional neural network (CNN) only use an end-layer feature as the input to TSR that requires massive data for network training. The computation-intensive network training process results in an inaccurate or delayed classification. Thereby, the current state-of-the-art methods have limited applications. This paper proposes a new TSR method integrating multi-layer feature and kernel extreme learning machine (ELM) classifier. The proposed method applies CNN to extract the multi-layer features of traffic… More >

Munish Kumar¹, Simpel Rani Jindal²

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.2, pp. 195-202, 2017, DOI:10.3970/cmes.2017.113.201

Abstract Grading of writers in perspective of their handwriting is a challenging task owing to various writing styles of different individuals. This paper presents a framework for grading of Devanagari writers in perspective of their handwriting. This framework of grading can be useful in conducting the handwriting competitions and then deciding the winners on the basis of an automated process. Selecting the set of features is a challenging task for implementing a handwriting grading system of particular language. In this paper, curvature features, namely, parabola curve fitting and power curve fitting have been considered for extracting the vital information of writers,… More >

Raquel R. Pinho¹, João Manuel R. S. Tavares¹

CMES-Computer Modeling in Engineering & Sciences, Vol.46, No.1, pp. 51-76, 2009, DOI:10.3970/cmes.2009.046.051

Abstract This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features' movement in every image frame. So as to integrate the measurements obtained from each image into the Kalman filter, a data optimization process has been adopted to achieve the best global correspondence set. The proposed criterion minimizes the cost of global matching, which is based on the Mahalanobis distance. A management model is employed to manage the features being… More >

H. Tang¹, L.C. Wrobel², Z. Fan²

FDMP-Fluid Dynamics & Materials Processing, Vol.3, No.2, pp. 129-146, 2007, DOI:10.3970/fdmp.2007.003.129

Abstract This paper presents an overview of diverse extrusion techniques and, in particular, a focused discussion about the rheoextrusion process for semi-solid casting (a novel casting process for the fabrication of high quality metals). The review reveals a wealth of interesting rheological and microstructural features, illustrating qualitative and quantitative data. The analysis is supported by relevant numerical results and examples. It is shown how numerical studies can lead to significant insights into these processes by providing more detailed information on the fundamental mechanisms of morphology development (during phase change) and profile forming. The die filling and solidification behaviours within extrusion dies… More >

Jingjing Liu^1,2, Bin Zhang³, Xu Cheng⁴, Ying Chen⁵, Li Zhao^1,*

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1097-1108, 2019, DOI:10.32604/cmc.2019.05968

Abstract Visual tracking is a challenging issue in the field of computer vision due to the objects’ intricate appearance variation. To adapt the change of the appearance, multiple channel features which could provide more information are used. However, the low level feature could not represent the structure of the object. In this paper, a superpixel-based adaptive tracking algorithm by using color histogram and haar-like feature is proposed, whose feature is classified into the middle level. Based on the superpixel representation of video frames, the haar-like feature is extracted at the superpixel level as the local feature, and the color histogram feature… More >