Chengzhang Zhu^{1, 2}, Wentao Zhao^{2, *}, Qian Li¹, Pan Li², Qiaobo Da³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 317-333, 2019, DOI:10.32604/cmc.2019.05677

Abstract Detecting collaborative fraudsters who manipulate opinions in social media is becoming extremely important in order to provide reliable information, in which, however, the diversity in different groups of collaborative fraudsters presents a significant challenge to existing collaborative fraudsters detection methods. These methods often detect collaborative fraudsters as the largest group of users who have the strongest relation with each other in the social media, consequently overlooking the other groups of fraudsters that are with strong user relation yet small group size. This paper introduces a novel network embedding-based framework NEST and its instance BEST to address this issue. NEST detects… More >

Assia Maamar^1,*, Khelifa Benahmed²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we propose a hybrid approach to… More >

Sultan Noman Qasem^1,2, Amar Nazar³, Attia Qamar⁴, Shahaboddin Shamshirband^5,6,*, Ahmad Karim⁴

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 713-727, 2019, DOI:10.32604/cmc.2019.05617

Abstract Brain tumor is one of the most dangerous disease that causes due to uncontrollable and abnormal cell partition. In this paper, we have used MRI brain scan in comparison with CT brain scan as it is less harmful to detect brain tumor. We considered watershed segmentation technique for brain tumor detection. The proposed methodology is divided as follows: pre-processing, computing foreground applying watershed, extract and supply features to machine learning algorithms. Consequently, this study is tested on big data set of images and we achieved acceptable accuracy from K-NN classification algorithm in detection of brain tumor. More >

Zhe Liu¹, Charlie Maere^1,*, Yuqing Song¹

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 669-686, 2019, DOI:10.32604/cmc.2019.04590

Abstract Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsfield filter. 2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to track the growing region changes… More >

Xiaoliang Wang^{1, *}, Wenhua Song¹, Bowei Zhang¹, Brandon Mausler², Frank Jiang^{1, 3}

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 135-147, 2019, DOI:10.32604/cmc.2019.05687

Abstract Nowadays, the number of vehicles in China has increased significantly. The increase of the number of vehicles has also led to the increasingly complex traffic situation and the urgent safety measures in need. However, the existing early warning devices such as geomagnetic, ultrasonic and infrared detection have some shortcomings like difficult installation and maintenance. In addition, geomagnetic detection will damage the road surface, while ultrasonic and infrared detection will be greatly affected by the environment. Considering the shortcomings of the existing solutions, this paper puts forward a solution of early warning for vehicle turning meeting based on image acquisition and… More >

Y. Zhang^1,2, Z.H. Xiang^1,3

CMC-Computers, Materials & Continua, Vol.26, No.1, pp. 19-36, 2011, DOI:10.3970/cmc.2011.026.019

Abstract Vibration based damage detection methods play an important role in the maintenance of beam structures such as bridges. However, most of them require the accurate measurement of structural mode shapes, which may not be easily satisfied in practice. Since the measurement of frequencies is more accurate than that of mode shapes, this paper proposes a frequency shift curve (FSC) method, based on the equivalence between the FSC due to auxiliary mass and the mode shape square, which has been demonstrated to be effective in structural damage detection. Two damage indices based on the FSC are developed, which are called the… More >

Ligang Zheng^1,*, Chao Song²

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 529-539, 2018, DOI: 10.3970/cmc.2018.03780

Abstract There is a steep increase in data encoded as symmetric positive definite (SPD) matrix in the past decade. The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of matrices, which we sometimes call SPD manifold. One of the fundamental problems in the application of SPD manifold is to find the nearest neighbor of a queried SPD matrix. Hashing is a popular method that can be used for the nearest neighbor search. However, hashing cannot be directly applied to SPD manifold due to its non-Euclidean intrinsic geometry. Inspired by the idea… More >

Bo Xiao¹, Zhen Wang², Qi Liu^3,*, Xiaodong Liu³

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 365-379, 2018, DOI: 10.3970/cmc.2018.01830

Abstract In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also come along with it. Therefore, more research work has been devoted to the problem of outlier detection in big data. However, the existing available methods have high computation time, the improved algorithm of outlier detection is presented, which has higher performance to detect outlier. In this paper, an improved algorithm is proposed. The SMK-means is a fusion algorithm which… More >

Yue Zhang¹, Dengpan Ye², Junjun Gan¹, Zhenyu Li³, Qingfeng Cheng^1,*

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 151-167, 2018, DOI: 10.3970/cmc.2018.02464

Abstract In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the embedding of the secret messages.… More >

Xiaonian Wu^1,*, Chuyun Zhang³, Runlian Zhang², Yujue Wang², Jinhua Cui⁴

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 61-72, 2018, DOI: 10.3970/cmc.2018.02449

Abstract There are two key issues in distributed intrusion detection system, that is, maintaining load balance of system and protecting data integrity. To address these issues, this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation. A data allocation strategy based on capacity and workload is introduced to achieve local load balance, and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster. Moreover, data integrity is protected by using session reassemble and session partitioning. The simulation results show that the new model enjoys favorable advantages such as… More >