Fazal Qudus Khan¹, Saim Rasheed¹, Maged Alsheshtawi¹, Tarig Mohamed Ahmed^{1, 2}, Sadeeq Jan^{3, *}

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 777-796, 2020, DOI:10.32604/cmc.2020.010959

Abstract Computing students face the problem with time and quality of the work while managing their graduation/senior projects. Rapid Application Development (RAD) model is based on continual user involvement for the process of requirement gathering via prototyping. After each iteration, the developers can validate the requirements that are completed in the iteration. Managing a project with RAD is easier but not flexible. On the other hand, Agile project management techniques focus on flexibility, agility, teamwork and quality based on user stories. Continual user involvement is avoided, which requires extensive maintenance time for fixing iteration and release of the story points. This… More >

V. Manikandan^{1, *}, M. Sivaram¹, Amin Salih Mohammed², V. Porkodi³

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 753-776, 2020, DOI:10.32604/cmc.2020.010267

Abstract Wireless Sensor Networks (WSNs) comprises low power devices that are randomly distributed in a geographically isolated region. The energy consumption of nodes is an essential factor to be considered. Therefore, an improved energy management technique is designed in this investigation to reduce its consumption and to enhance the network’s lifetime. This can be attained by balancing energy clusters using a meta-heuristic Firefly algorithm model for network communication. This improved technique is based on the cluster head selection technique with measurement of the tour length of fireflies. Time Division Multiple Access (TDMA) scheduler is also improved with the characteristics/behavior of fireflies… More >

Muhammad Hasnain¹, Seung Ryul Jeong^{2, *}, Muhammad Fermi Pasha³, Imran Ghani⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394

Abstract Performance anomaly detection is the process of identifying occurrences that do not conform to expected behavior or correlate with other incidents or events in time series data. Anomaly detection has been applied to areas such as fraud detection, intrusion detection systems, and network systems. In this paper, we propose an anomaly detection framework that uses dynamic features of quality of service that are collected in a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short term memory, and gated recurrent unit are evaluated. The results reveal that the proposed method effectively detects anomalies in web services with high accuracy.… More >

Yui-Chuin Shiah^{1, *}, Sheng-Chi Huang¹, M. R. Hematiyan²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 701-727, 2020, DOI:10.32604/cmc.2020.010417

Abstract In engineering practice, analysis of interfacial thermal stresses in composites is a crucial task for assuring structural integrity when sever environmental temperature changes under operations. In this article, the directly transformed boundary integrals presented previously for treating generally anisotropic thermoelasticity in two-dimension are fully regularized by a semi-analytical approach for modeling thin multi-layers of anisotropic/isotropic composites, subjected to general thermal loads with boundary conditions prescribed. In this process, an additional difficulty, not reported in the literature, arises due to rapid fluctuation of an integrand in the directly transformed boundary integral equation. In conventional analysis, thin adhesives are usually neglected due… More >

A. Renugambal^{1, *}, K. Selva Bhuvaneswari²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 681-700, 2020, DOI:10.32604/cmc.2020.09519

Abstract In this study, a novel hybrid Water Cycle Moth-Flame Optimization (WCMFO) algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance (MR) image slices. WCMFO constitutes a hybrid between the two techniques, comprising the water cycle and moth-flame optimization algorithms. The optimal thresholds are obtained by maximizing the between class variance (Otsu’s function) of the image. To test the performance of threshold searching process, the proposed algorithm has been evaluated on standard benchmark of ten axial T₂-weighted brain MR images for image segmentation. The experimental outcomes infer that it produces better optimal threshold values at a greater and… More >

Haijun Geng¹, Jiangyuan Yao^{2, *}, Yangyang Zhang³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 665-679, 2020, DOI:10.32604/cmc.2020.09912

Abstract Loop free alternate (LFA) is a routing protection scheme that is currently deployed in commercial routers. However, LFA cannot handle all single network component failure scenarios in traditional networks. As Internet service providers have begun to deploy software defined network (SDN) technology, the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time. Therefore, this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios. First, the deployment of LFA scheme in a hybrid SDN network is described as a 0-1… More >

Caifeng Cheng^{1, 2}, Xiang’e Sun^{1, *}, Deshu Lin³, Yiliu Tu⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 651-664, 2020, DOI:10.32604/cmc.2020.09874

Abstract In actual exploration, the demand for 3D seismic data collection is increasing, and the requirements for data are becoming higher and higher. Accordingly, the collection cost and data volume also increase. Aiming at this problem, we make use of the nature of data sparse expression, based on the theory of compressed sensing, to carry out the research on the efficient collection method of seismic data. It combines the collection of seismic data and the compression in data processing in practical work, breaking through the limitation of the traditional sampling frequency, and the sparse characteristics of the seismic signal are utilized… More >

Zijian Li¹, Chengying Chi^{1, *}, Yunyun Zhan^{2, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 637-650, 2020, DOI:10.32604/cmc.2020.010265

Abstract The translation quality of neural machine translation (NMT) systems depends largely on the quality of large-scale bilingual parallel corpora available. Research shows that under the condition of limited resources, the performance of NMT is greatly reduced, and a large amount of high-quality bilingual parallel data is needed to train a competitive translation model. However, not all languages have large-scale and high-quality bilingual corpus resources available. In these cases, improving the quality of the corpora has become the main focus to increase the accuracy of the NMT results. This paper proposes a new method to improve the quality of data by… More >

Deyin Li^{1, 2}, Mingzhi Cheng³, Yu Yang^{1, 2, *}, Min Lei^{1, 2}, Linfeng Shen⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 623-635, 2020, DOI:10.32604/cmc.2020.09800

Abstract Deep learning networks are widely used in various systems that require classification. However, deep learning networks are vulnerable to adversarial attacks. The study on adversarial attacks plays an important role in defense. Black-box attacks require less knowledge about target models than white-box attacks do, which means black-box attacks are easier to launch and more valuable. However, the state-of-arts black-box attacks still suffer in low success rates and large visual distances between generative adversarial images and original images. This paper proposes a kind of fast black-box attack based on the cross-correlation (FBACC) method. The attack is carried out in two stages.… More >

Jiaye Pan¹, Yi Zhuang^{1, *}, Xinwen Hu^{1, 2}, Wenbing Zhao³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 607-622, 2020, DOI:10.32604/cmc.2020.09853

Abstract Nowadays cloud architecture is widely applied on the internet. New malware aiming at the privacy data stealing or crypto currency mining is threatening the security of cloud platforms. In view of the problems with existing application behavior monitoring methods such as coarse-grained analysis, high performance overhead and lack of applicability, this paper proposes a new fine-grained binary program monitoring and analysis method based on multiple system level components, which is used to detect the possible privacy leakage of applications installed on cloud platforms. It can be used online in cloud platform environments for fine-grained automated analysis of target programs, ensuring… More >