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  • Open Access

    ARTICLE

    The Quantum Approximate Algorithm for Solving Traveling Salesman Problem

    Yue Ruan1, *, Samuel Marsh2, Xilin Xue1, Zhihao Liu3, Jingbo Wang2, *

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1237-1247, 2020, DOI:10.32604/cmc.2020.010001

    Abstract The Quantum Approximate Optimization Algorithm (QAOA) is an algorithmic framework for finding approximate solutions to combinatorial optimization problems. It consists of interleaved unitary transformations induced by two operators labelled the mixing and problem Hamiltonians. To fit this framework, one needs to transform the original problem into a suitable form and embed it into these two Hamiltonians. In this paper, for the well-known NP-hard Traveling Salesman Problem (TSP), we encode its constraints into the mixing Hamiltonian rather than the conventional approach of adding penalty terms to the problem Hamiltonian. Moreover, we map edges (routes) connecting each pair of cities to qubits,… More >

  • Open Access

    ARTICLE

    Prediction of Web Services Reliability Based on Decision Tree Classification Method

    Zhichun Jia1, 2, Qiuyang Han1, Yanyan Li1, Yuqiang Yang1, Xing Xing1, 2, *

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722

    Abstract With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values. However, because the network and… More >

  • Open Access

    ARTICLE

    A MV-Based Steganographic Algorithm for H.264/AVC without Distortion

    Hongqiong Tang1, 2, Xiaoyuan Yang1, 2, *, Yingnan Zhang1, Ke Niu1, 2

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1205-1219, 2020, DOI:10.32604/cmc.2020.010075

    Abstract H.264/AVC video is one of the most popular multimedia and has been widely used as the carriers of video steganography. In this paper, a novel motion vector (MV) based steganographic algorithm is proposed for the H.264/AVC compressed video without distortion. Four modules are introduced to eliminate the distortion caused by the modifications of motion vectors and guarantee the security of the algorithm. In the embedding block, the motion vector space encoding is used to embed a (2n+1)-ary notational number into an n-dimension vector composed of motion vectors generated from the selection block. Scrambling is adopted to disturb the order of… More >

  • Open Access

    ARTICLE

    Applying ANN, ANFIS and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO2

    Amin Bemani1, Alireza Baghban2, Shahaboddin Shamshirband3, 4, *, Amir Mosavi5, 6, 7, Peter Csiba7, Annamaria R. Varkonyi-Koczy5, 7

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1175-1204, 2020, DOI:10.32604/cmc.2020.07723

    Abstract In the present work, a novel machine learning computational investigation is carried out to accurately predict the solubility of different acids in supercritical carbon dioxide. Four different machine learning algorithms of radial basis function, multi-layer perceptron (MLP), artificial neural networks (ANN), least squares support vector machine (LSSVM) and adaptive neuro-fuzzy inference system (ANFIS) are used to model the solubility of different acids in carbon dioxide based on the temperature, pressure, hydrogen number, carbon number, molecular weight, and the dissociation constant of acid. To evaluate the proposed models, different graphical and statistical analyses, along with novel sensitivity analysis, are carried out.… More >

  • Open Access

    ARTICLE

    Ant Colony Optimization for Multi-Objective Multicast Routing

    Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3, *

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1159-1173, 2020, DOI:10.32604/cmc.2020.09176

    Abstract In the distributed networks, many applications send information from a source node to multiple destination nodes. To support these applications requirements, the paper presents a multi-objective algorithm based on ant colonies to construct a multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, it is able to find a better solution with fast convergence speed and high reliability. More >

  • Open Access

    ARTICLE

    Exact Solution of Non-Newtonian Blood Flow with Nanoparticles through Porous Arteries: A Comparative Study

    Wafaa Alharbi1, Abdulrahman Aljohani1, Essam El-Zahar2, 3, *, Abdelhalim Ebaid1

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1143-1157, 2020, DOI:10.32604/cmc.2020.08875

    Abstract In this paper, the mathematical model describing the third-grade nonNewtonian blood flow suspended with nanoparticles through porous arteries is exactly solved. The present physical model was solved in the research literature via the optimal homotopy analysis method and the collocation method, where the obtained solution was compared with the numerical fourth-order Runge-Kutta solution. However, the present paper only introduces a new approach to obtain the exact solution of the concerned system and implements such exact solution as a reference to validate the published approximate solutions. Several remarks on the previously published results are observed and discussed in detail through tables… More >

  • Open Access

    ARTICLE

    An Efficient Image Analysis Framework for the Classification of Glioma Brain Images Using CNN Approach

    Ravi Samikannu1, *, Rohini Ravi2, Sivaram Murugan3, Bakary Diarra4

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1133-1142, 2020, DOI:10.32604/cmc.2020.08578

    Abstract The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours. The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work. The non-active cells in brain region are known to be benign and they will never cause the death of the patient. These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels. The Magnetic Resonance (MR) image contrast is improved by the cost map construction technique. The deep learning algorithm for differentiating the normal brain… More >

  • Open Access

    ARTICLE

    Computing Topological Invariants of Triangular Chandelier Lattice

    Nazeran Idrees1, *, Raghisa Khalid1, Fozia Bashir Farooq2, Sumiya Nasir3

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1119-1132, 2020, DOI:10.32604/cmc.2020.08166

    Abstract A numerical parameter mathematically derived from the graph structure is a topological index. The topological index is the first actual choice in QSAR research and these indices are used to build the correlation model between the chemical structures of various chemicals compounds. Here, we investigate some old degree-based topological indices like Randic index, sum connectivity index, ABC index, GA index, 1st and 2nd Zagreb indices, modified second Zagreb index, redefined version of 1st, 2nd and 3rd Zagreb indices, hyper and augmented Zagreb indices, forgotten index and symmetric division degree index, and some new degree-based indices like SK index, SK1 index,… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content

    Muhammad Zubair Asghar1, Fazli Subhan2, Muhammad Imran1, Fazal Masud Kundi1, Adil Khan3, Shahboddin Shamshirband4, 5, *, Amir Mosavi6, 7, 8, Peter Csiba8, Annamaria R. Varkonyi Koczy8

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1093-1118, 2020, DOI:10.32604/cmc.2020.07709

    Abstract Emotion detection from the text is a challenging problem in the text analytics. The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions. However, most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets, resulting in performance degradation. To overcome this issue, this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset. The experimental results show the performance of different machine… More >

  • Open Access

    ARTICLE

    3-Dimensional Bag of Visual Words Framework on Action Recognition

    Shiqi Wang1, Yimin Yang1, *, Ruizhong Wei1, Qingming Jonathan Wu2

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1081-1091, 2020, DOI:10.32604/cmc.2020.09648

    Abstract Human motion recognition plays a crucial role in the video analysis framework. However, a given video may contain a variety of noises, such as an unstable background and redundant actions, that are completely different from the key actions. These noises pose a great challenge to human motion recognition. To solve this problem, we propose a new method based on the 3-Dimensional (3D) Bag of Visual Words (BoVW) framework. Our method includes two parts: The first part is the video action feature extractor, which can identify key actions by analyzing action features. In the video action encoder, by analyzing the action… More >

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