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 More >

SangWook Han¹, JungYeon Seo¹, Dae-Young Kim², SeokHoon Kim³, HwaMin Lee^3,*

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 697-711, 2019, DOI:10.32604/cmc.2019.06071

Abstract Air pollution caused by fine dust is a big problem all over the world and fine dust has a fatal impact on human health. But there are too few fine dust measuring stations and the installation cost of fine dust measuring station is very expensive. In this paper, we propose Cloud-based air pollution information system using R. To measure fine dust, we have developed an inexpensive measuring device and studied the technique to accurately measure the concentration of fine dust at the user’s location. And we have developed the smartphone application to provide air pollution More >

Paolina Centonze^1,*

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223

Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and… More >

Weihong Han¹, Zhihong Tian^1,*, Zizhong Huang², Lin Zhong³, Yan Jia²

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 167-180, 2019, DOI:10.32604/cmc.2019.05192

Abstract Network Security Situation Awareness System YHSAS acquires, understands and displays the security factors which cause changes of network situation, and predicts the future development trend of these security factors. YHSAS is developed for national backbone network, large network operators, large enterprises and other large-scale network. This paper describes its architecture and key technologies: Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis, Knowledge Representation and Management of Super Large-Scale Network Security, Multi-Level, Multi-Granularity and Multi-Dimensional Network Security Index Construction Method, Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology, and so on. The 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 More >

Wei Guo^1,2, Chen Zeng^1,2, Hongye Gou^3,*, Yao Hu^1,2, Hengchao Xu⁴, Longlong Guo^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 491-515, 2019, DOI:10.32604/cmes.2019.06162

Abstract CRTS-II slab ballastless track on bridge is a unique system in China high speed railway. The application of longitudinal continuous track system has obviously changed dynamic characteristics of bridge structure. The bridge system and CRTS-II track system form a complex nonlinear system. To investigate the seismic response of high speed railway (HSR) simply supported bridge-track system, nonlinear models of three-span simply supported bridge with piers of different height and CRTS-II slab ballastless track system are established. By seismic analysis, it is found that shear alveolar in CRTS-II track system is more prone to be damaged… More >

Zhijian Qiu¹, Jinchi Lu¹, Ahmed Elgamal^1,*, Lei Su², Ning Wang³, Abdullah Almutairi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 629-656, 2019, DOI:10.32604/cmes.2019.05759

Abstract The OpenSees computational platform has allowed unprecedented opportunities for conducting seismic nonlinear soil-structure interaction simulations. On the geotechnical side, capabilities such as coupled solid-fluid formulations and nonlinear incremental-plasticity approaches allow for representation of the involved dynamic/seismic responses. This paper presents recent research that facilitated such endeavors in terms of response of ground-foundation-structure systems using advanced material modeling techniques and high-performance computing resources. Representative numerical results are shown for large-scale soil-structure systems, and ground modification liquefaction countermeasures. In addition, graphical user interface enabling tools for routine usage of such 3D simulation environments are presented, as an More >

Ying Zhou^1,*, Peng Chen¹

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 759-777, 2019, DOI:10.32604/cmes.2019.04383

Abstract This paper proposes a novel three-dimensional (3D) isolation system for facilities and presents the numerical simulation approach for the isolated system under earthquake excitations and impact effect using the OpenSees (Open System for Earthquake Engineering Simulation) software frame work. The 3D isolators combine the quasi-zero stiffness (QZS) system in the vertical direction and lead rubber bearing in the horizontal direction. Considering the large aspect ratio of the isolated facility, linear viscous dampers are designed in the vertical direction to diminish the overturning effect. The vertical QZS isolation system is characterized by a cubic force-displacement relation,… More >

Junjun Jiang¹, Congqing Wang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.1, pp. 105-121, 2019, DOI:10.32604/cmes.2019.06277

Abstract Aircraft skin health concerns whether the aircraft can fly safely. In this paper, an improved mechanical structure of the aircraft skin inspection robot was introduced. Considering that the aircraft skin surface is a curved environment, we assume that the curved environment is equivalent to an inclined plane with a change in inclination. Based on this assumption, the Cartesian dynamics model of the robot is established using the Lagrange method. In order to control the robot’s movement position accurately, a position backstepping control scheme for the aircraft skin inspection robot was presented. According to the dynamic More >

Jin Yang¹, Tao Li¹, Gang Liang^1,*, Wenbo He², Yue Zhao³

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.1, pp. 1-23, 2019, DOI:10.32604/cmes.2019.04727

Abstract Deep Learning presents a critical capability to be geared into environments being constantly changed and ongoing learning dynamic, which is especially relevant in Network Intrusion Detection. In this paper, as enlightened by the theory of Deep Learning Neural Networks, Hierarchy Distributed-Agents Model for Network Risk Evaluation, a newly developed model, is proposed. The architecture taken on by the distributed-agents model are given, as well as the approach of analyzing network intrusion detection using Deep Learning, the mechanism of sharing hyper-parameters to improve the efficiency of learning is presented, and the hierarchical evaluative framework for Network More >