Jieren Cheng¹, Jun Li^{2, *}, Naixue Xiong³, Meizhu Chen², Hao Guo², Xinzhi Yao²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2247-2262, 2020, DOI:10.32604/cmc.2020.011668

Abstract Nowadays, as lightweight mobile clients become more powerful and widely used, more and more information is stored on lightweight mobile clients, user sensitive data privacy protection has become an urgent concern and problem to be solved. There has been a corresponding rise of security solutions proposed by researchers, however, the current security mechanisms on lightweight mobile clients are proven to be fragile. Due to the fact that this research field is immature and still unexplored in-depth, with this paper, we aim to provide a structured and comprehensive study on privacy protection using trusted execution environment (TEE) for lightweight mobile clients.… More >

Shaozhang Niu^{1, *}, Xiangxiang Li¹, Maosen Wang¹, Yueying Li²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2233-2245, 2020, DOI:10.32604/cmc.2020.09471

Abstract In recent years, images have played a more and more important role in our daily life and social communication. To some extent, the textual information contained in the pictures is an important factor in understanding the content of the scenes themselves. The more accurate the text detection of the natural scenes is, the more accurate our semantic understanding of the images will be. Thus, scene text detection has also become the hot spot in the domain of computer vision. In this paper, we have presented a modified text detection network which is based on further research and improvement of Connectionist… More >

Anjie Peng¹, Kang Deng¹, Shenghai Luo¹, Hui Zeng^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2217-2231, 2020, DOI:10.32604/cmc.2020.011006

Abstract The multi-purpose forensics is an important tool for forge image detection. In this paper, we propose a universal feature set for the multi-purpose forensics which is capable of simultaneously identifying several typical image manipulations, including spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG compression. To eliminate the influences caused by diverse image contents on the effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from the residual group to purely measure neighborhood correlations in a linear way. Besides that, we also combine autoregressive coefficient and… More >

Qiqiang Chen^{1, *}, Xinxin Gan², Wei Huang¹, Jingjing Feng¹, H. Shim³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2201-2215, 2020, DOI:10.32604/cmc.2020.011191

Abstract Automatic road damage detection using image processing is an important aspect of road maintenance. It is also a challenging problem due to the inhomogeneity of road damage and complicated background in the road images. In recent years, deep convolutional neural network based methods have been used to address the challenges of road damage detection and classification. In this paper, we propose a new approach to address those challenges. This approach uses densely connected convolution networks as the backbone of the Mask R-CNN to effectively extract image feature, a feature pyramid network for combining multiple scales features, a region proposal network… More >

Fengchang Xue^{1, *}, Juan Tian¹, Wei Wang², Yanran Zhang¹, Gohar Ali³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2189-2199, 2020, DOI:10.32604/cmc.2020.06513

Abstract For the challenge of parameter calibration in the process of SWMM (storm water management model) model application, we use particle Swarm Optimization (PSO) and Sequence Quadratic Programming (SQP) in combination to calibrate the parameters and get the optimal parameter combination in this research. Then, we compare and analyze the simulation result with the other two respectively using initial parameters and parameters obtained by PSO algorithm calibration alone. The result shows that the calibration result of PSO-SQP combined algorithm has the highest accuracy and shows highly consistent with the actual situation, which provides a scientific and effective new idea for parameter… More >

Rashad Bantan¹, Amal S. Hassan², Mahmoud Elsehetry^{3, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2169-2187, 2020, DOI:10.32604/cmc.2020.011497

Abstract In this article, we offer a new adapted model with three parameters, called Zubair Lomax distribution. The new model can be very useful in analyzing and modeling real data and provides better fits than some others new models. Primary properties of the Zubair Lomax model are determined by moments, probability weighted moments, Renyi entropy, quantile function and stochastic ordering, among others. Maximum likelihood method is used to estimate the population parameters, owing to simple random sample and ranked set sampling schemes. The behavior of the maximum likelihood estimates for the model parameters is studied using Monte Carlo simulation. Criteria measures… More >

Huifang Qian¹, Xuan Zhou^{1, *}, Mengmeng Zheng¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2153-2167, 2020, DOI:10.32604/cmc.2020.011843

Abstract The core technology in an intelligent video surveillance system is that detecting and recognizing abnormal behaviors timely and accurately. The key breakthrough point in recognizing abnormal behaviors is how to obtain the effective features of the picture, so as to solve the problem of recognizing them. In response to this difficulty, this paper introduces an adjustable jump link coefficients model based on the residual network. The effective coefficients for each layer of the network can be set after using this model to further improving the recognition accuracy of abnormal behavior. A convolution kernel of 1×1 size is added to reduce… More >

Xiaoyu Li¹, Qinsheng Zhu^{2, *}, Yiming Huang¹, Yong Hu², Qingyu Meng², Chenjing Su¹, Qing Yang², Shaoyi Wu², Xusheng Liu³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2143-2151, 2020, DOI:10.32604/cmc.2020.010865

Abstract Quantum correlation shows a fascinating nature of quantum mechanics and plays an important role in some physics topics, especially in the field of quantum information. Quantum correlations of the composite system can be quantified by resorting to geometric or entropy methods, and all these quantification methods exhibit the peculiar freezing phenomenon. The challenge is to find the characteristics of the quantum states that generate the freezing phenomenon, rather than only study the conditions which generate this phenomenon under a certain quantum system. In essence, this is a classification problem. Machine learning has become an effective method for researchers to study… More >

Dan Ma^{1, 2}, Hongyu Duan², Qi Zhang^{3, *}, Jixiong Zhang¹, Wenxuan Li², Zilong Zhou², Weitao Liu⁴

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2123-2141, 2020, DOI:10.32604/cmc.2020.011430

Abstract Gas fracturing, which overcomes the limitation of hydraulic fracturing, is a potential alternative technology for the development of unconventional gas and oil resources. However, the mechanical principle of gas fracturing has not been learned comprehensively when the fluid is injected into the borehole. In this paper, a damagebased model of coupled thermal-flowing-mechanical effects was adopted to illustrate the mechanical principle of gas fracturing. Numerical simulation tools Comsol Multiphysics and Matlab were integrated to simulate the coupled process during the gas fracturing. Besides, the damage evolution of drilling areas under several conditions was fully analyzed. Simulation results indicate that the maximum… 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

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 how the battery voltage changes.… More >