Alanoud Alhussain¹, Heba Kurdi^1,*, Lina Altoaimy²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 805-815, 2019, DOI:10.32604/cmc.2019.05848

Abstract Edge devices in Internet of Things (IoT) applications can form peers to communicate in peer-to-peer (P2P) networks over P2P protocols. Using P2P networks ensures scalability and removes the need for centralized management. However, due to the open nature of P2P networks, they often suffer from the existence of malicious peers, especially malicious peers that unite in groups to raise each other's ratings. This compromises users' safety and makes them lose their confidence about the files or services they are receiving. To address these challenges, we propose a neural network-based algorithm, which uses the advantages of a machine learning algorithm to… More >

Yong Xie¹, Fang Xu², Xiang Li¹, Songsong Zhang¹, Xiaodan Zhang^1,*, Muhammad Israr³

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 903-924, 2019, DOI:10.32604/cmc.2019.05309

Abstract Wireless sensor networks (WSNs) are the major contributors to big data acquisition. The authenticity and integrity of the data are two most important basic requirements for various services based on big data. Data aggregation is a promising method to decrease operation cost for resource-constrained WSNs. However, the process of data acquisitions in WSNs are in open environments, data aggregation is vulnerable to more special security attacks with hiding feature and subjective fraudulence, such as coalition attack. Aimed to provide data authenticity and integrity protection for WSNs, an efficient and secure identity-based aggregate signature scheme (EIAS) is proposed in this paper.… More >

Murat Cancan^{1, *}

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 777-786, 2019, DOI:10.32604/cmc.2019.06596

Abstract Topological indices enable to gather information for the underlying topology of chemical structures and networks. Novel harmonic indices have been defined recently. All degree based topological indices are defined by using the classical degree concept. Recently two novel degree concept have been defined in graph theory: ve-degree and ev-degree. Ve-degree Zagreb indices have been defined by using ve-degree concept. The prediction power of the ve-degree Zagreb indices is stronger than the classical Zagreb indices. Dominating oxide, silicate and oxygen networks are important network models in view of chemistry, physics and information science. Physical and mathematical properties of dominating oxide, silicate… More >

Demin Gao^{1, 2, *}, Shuo Zhang¹, Fuquan Zhang¹, Xijian Fan¹, Jinchi Zhang^1,∗

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 649-667, 2019, DOI:10.32604/cmc.2019.05195

Abstract For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a… More >

Nehal Al-Otaiby¹, Heba Kurdi^1,*, Shiroq Al-Megren¹

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 397-404, 2019, DOI:10.32604/cmc.2019.06236

Abstract Trust has become an increasingly important issue given society’s growing reliance on electronic transactions. Peer-to-peer (P2P) networks are among the main electronic transaction environments affected by trust issues due to the freedom and anonymity of peers (users) and the inherent openness of these networks. A malicious peer can easily join a P2P network and abuse its peers and resources, resulting in a large-scale failure that might shut down the entire network. Therefore, a plethora of researchers have proposed trust management systems to mitigate the impact of the problem. However, due to the problem’s scale and complexity, more research is necessary.… More >

Khader M. Hamdia², Hamid Ghasemi³, Xiaoying Zhuang^4,5, Naif Alajlan¹, Timon Rabczuk^1,2,*

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 79-87, 2019, DOI:10.32604/cmc.2019.05882

Abstract In this study, machine learning representation is introduced to evaluate the flexoelectricity effect in truncated pyramid nanostructure under compression. A Non-Uniform Rational B-spline (NURBS) based IGA formulation is employed to model the flexoelectricity. We investigate 2D system with an isotropic linear elastic material under plane strain conditions discretized by 45×30 grid of B-spline elements. Six input parameters are selected to construct a deep neural network (DNN) model. They are the Young's modulus, two dielectric permittivity constants, the longitudinal and transversal flexoelectric coefficients and the order of the shape function. The outputs of interest are the strain in the stress direction… More >

Manal Hazazi¹, Afnan Almousa¹, Heba Kurdi^1,2,*, Shiroq Al-Megren¹, Shada Alsalamah¹

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 15-29, 2019, DOI:10.32604/cmc.2019.06221

Abstract The underlying premise of peer-to-peer (P2P) systems is the trading of digital resources among individual peers to facilitate file sharing, distributed computing, storage, collaborative applications and multimedia streaming. So-called free-riders challenge the foundations of this system by consuming resources from other peers without offering any resources in return, hindering resource exchange among peers. Therefore, immense effort has been invested in discouraging free-riding and overcoming the ill effects of such unfair use of the system. However, previous efforts have all fallen short of effectively addressing free-riding behaviour in P2P networks. This paper proposes a novel approach based on utilising a credit… More >

Cosmin Anitescu¹, Elena Atroshchenko², Naif Alajlan³, Timon Rabczuk^3,*

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 345-359, 2019, DOI:10.32604/cmc.2019.06641

Abstract We present a method for solving partial differential equations using artificial neural networks and an adaptive collocation strategy. In this procedure, a coarse grid of training points is used at the initial training stages, while more points are added at later stages based on the value of the residual at a larger set of evaluation points. This method increases the robustness of the neural network approximation and can result in significant computational savings, particularly when the solution is non-smooth. Numerical results are presented for benchmark problems for scalar-valued PDEs, namely Poisson and Helmholtz equations, as well as for an inverse… More >

Lili Pan¹, Jiaohua Qin^1,*, Hao Chen², Xuyu Xiang¹, Cong Li¹, Ran Chen¹

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 297-313, 2019, DOI:10.32604/cmc.2019.04097

Abstract Image retrieval for food ingredients is important work, tremendously tiring, uninteresting, and expensive. Computer vision systems have extraordinary advancements in image retrieval with CNNs skills. But it is not feasible for small-size food datasets using convolutional neural networks directly. In this study, a novel image retrieval approach is presented for small and medium-scale food datasets, which both augments images utilizing image transformation techniques to enlarge the size of datasets, and promotes the average accuracy of food recognition with state-of-the-art deep learning technologies. First, typical image transformation techniques are used to augment food images. Then transfer learning technology based on deep… More >

Igor Grešovnik^1,2, Tadej Kodelja¹, Robert Vertnik^2,3, Bojan Senčič^3,2,3, Božidar Šarler^1,2,4

CMC-Computers, Materials & Continua, Vol.30, No.1, pp. 19-38, 2012, DOI:10.3970/cmc.2012.030.019

Abstract Artificial neural networks (ANNs) are employed as an alternative to physical modeling for calculation of the relations between the production path process parameters (melting of scrap steel and alloying, continuous casting, hydrogen removal, reheating, rolling, and cooling on a cooling bed) and the final product mechanical properties (elongation, tensile strength, yield stress, hardness after rolling, necking) of steel semi products. They provide a much faster technique of response evaluation complementary to physical modeling. The Štore Steel company process path for production of steel bars is used as an example for demonstrating the approach. The applied ANN is of a multilayer… More >