Lei Feng^1,2, Haibin Li^1,*, Yakun Gao¹, Yakun Zhang¹

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 831-839, 2020, DOI:10.32604/iasc.2020.010117

Abstract In the paper, we apply the sparse reconstruction algorithm of improved background dictionary to saliency detection. Firstly, after super-pixel segmentation, two bottom features are extracted: the color information of LAB and the texture features of the image by Gabor filter. Secondly, the convex hull theory is used to remove object region in boundary region, and K-means clustering algorithm is used to continue to simplify the background dictionary. Finally, the saliency map is obtained by calculating the reconstruction error. Compared with the mainstream algorithms, the accuracy and efficiency of this algorithm are better than those of More >

Sun-Taag Choe, We-Duke Cho^*, Jai-Hoon Kim, and Ki-Hyung Kim

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 679-691, 2020, DOI:10.32604/iasc.2020.010102

Abstract Recent research on activity recognition in wearable devices has identified a key challenge: k-nearest neighbors (k-NN) algorithms have a high operational time complexity. Thus, these algorithms are difficult to utilize in embedded wearable devices. Herein, we propose a method for reducing this complexity. We apply a clustering algorithm for learning data and assign labels to each cluster according to the maximum likelihood. Experimental results show that the proposed method achieves effective operational levels for implementation in embedded devices; however, the accuracy is slightly lower than that of a traditional k-NN algorithm. Additionally, our method provides More >

Yudong Wang^{1, 2}, Jie Tan^{1, *}, Zhenjie Liu¹, Allah Ditta³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2111-2122, 2020, DOI:10.32604/cmc.2020.011098 - 16 September 2020

Abstract Batteries are often packed together to meet voltage and capability needs. However, due to variations in raw materials, different ages of equipment, and manual operation, there is inconsistency between batteries, which leads to reduced available capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack similar batteries together. The conventional approach to screening batteries is based on their capacity, voltage and internal resistance, which disregards how batteries perform during manufacturing. In the battery discharge process, real time discharge voltage curves (DVCs) are collected as a set of unlabeled time series, which reflect More >

Peng Tang^∗, Yu Wang, Ning Shen

Computer Systems Science and Engineering, Vol.35, No.4, pp. 237-246, 2020, DOI:10.32604/csse.2020.35.237

Abstract In today’s modern society, the physical fitness of college students is gradually declining. In this paper, a prediction model for college students’ physical fitness is established, in which support vector regression (SVR) and k-means clustering are combined together for the prediction of college students’ fitness. Firstly, the physical measurement data of college students are classified according to gender and class characteristics. Then, the k-means clustering method is used to classify the physical measurement data of college students. Next, the physical characteristics of college students are extracted by SVR to establish the prediction model of physical More >

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 More >

Hussein Shahata Abdallah^{1, *}, Mohamed H. Khafagy¹, Fatma A. Omara²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1303-1320, 2020, DOI:10.32604/cmc.2020.011313 - 20 August 2020

Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the… More >

Xinliang Tang¹, Man Zhang¹, Pingping Yu¹, Wei Liu², Ning Cao^{3, *}, Yunfeng Xu⁴

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1725-1739, 2020, DOI:10.32604/cmc.2020.010272 - 30 June 2020

Abstract In a large-scale wireless sensor network (WSN), densely distributed sensor nodes process a large amount of data. The aggregation of data in a network can consume a great amount of energy. To balance and reduce the energy consumption of nodes in a WSN and extend the network life, this paper proposes a nonuniform clustering routing algorithm based on the improved K-means algorithm. The algorithm uses a clustering method to form and optimize clusters, and it selects appropriate cluster heads to balance network energy consumption and extend the life cycle of the WSN. To ensure that 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 - 10 June 2020

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… More >

Jiaohua Qin¹, Yusi Cao¹, Xuyu Xiang^{1, *}, Yun Tan¹, Lingyun Xiang², Jianjun Zhang³

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 389-399, 2020, DOI:10.32604/cmc.2020.07819 - 30 March 2020

Abstract With the massive growth of images data and the rise of cloud computing that can provide cheap storage space and convenient access, more and more users store data in cloud server. However, how to quickly query the expected data with privacy-preserving is still a challenging in the encryption image data retrieval. Towards this goal, this paper proposes a ciphertext image retrieval method based on SimHash in cloud computing. Firstly, we extract local feature of images, and then cluster the features by K-means. Based on it, the visual word codebook is introduced to represent feature information More >

Shuyu Li¹, Guozheng Zhang^{1, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 223-241, 2020, DOI:10.32604/cmc.2020.07499 - 30 March 2020

Abstract With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different… More >