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  • Open Access

    ARTICLE

    A Direct Data-Cluster Analysis Method Based on Neutrosophic Set Implication

    Sudan Jha1, Gyanendra Prasad Joshi2, Lewis Nkenyereya3, Dae Wan Kim4, *, Florentin Smarandache5

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1203-1220, 2020, DOI:10.32604/cmc.2020.011618

    Abstract Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine… More >

  • Open Access

    ARTICLE

    Success Rate Queue-Based Relocation Algorithm of Sensory Network to Overcome Non-Uniformly Distributed Obstacles

    Sooyeon Park1, Moonseong Kim2, Woochan Lee1, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1181-1201, 2020, DOI:10.32604/cmc.2020.011245

    Abstract With the recent development of big data technology that collects and analyzes various data, the technology that continuously collects and analyzes the observed data is also drawing attention. Moreover, its importance is growing in data collection in areas where people cannot access. In general, it is not easy to properly deploy IoT wireless devices for data collection in these areas, and it is also inappropriate to use general wheelbased mobile devices for relocation. Recently, researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions. The majority of studies, however, so far… More >

  • Open Access

    ARTICLE

    Three-Dimensional Isogeometric Analysis of Flexoelectricity with MATLAB Implementation

    Hamid Ghasemi1, Harold S. Park2, Xiaoying Zhuang3, 4, *, Timon Rabczuk5, 6

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1157-1179, 2020, DOI:10.32604/cmc.2020.08358

    Abstract Flexoelectricity is a general electromechanical phenomenon where the electric polarization exhibits a linear dependency to the gradient of mechanical strain and vice versa. The truncated pyramid compression test is among the most common setups to estimate the flexoelectric effect. We present a three-dimensional isogeometric formulation of flexoelectricity with its MATLAB implementation for a truncated pyramid setup. Besides educational purposes, this paper presents a precise computational model to illustrate how the localization of strain gradients around pyramidal boundary shapes contributes in generation of electrical energy. The MATLAB code is supposed to help learners in the Isogeometric Analysis and Finite Elements Methods… More >

  • Open Access

    ARTICLE

    A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

    Fahd N. Al-Wesabi1, 2, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1137-1156, 2020, DOI:10.32604/cmc.2020.011151

    Abstract Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach embeds and detects the watermark… More >

  • Open Access

    ARTICLE

    Context Based Adoption of Ranking and Indexing Measures for Cricket Team Ranks

    Raja Sher Afgun Usmani1, Syed Muhammad Saqlain Shah1, *, Muhammad Sher Ramzan2, Abdullah Saad AL-Malaise AL-Ghamdi2, Anwar Ghani1, Imran Khan1, Farrukh Saleem2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1113-1136, 2020, DOI:10.32604/cmc.2020.010789

    Abstract There is an international cricket governing body that ranks the expertise of all the cricket playing nations, known as the International Cricket Council (ICC). The ranking system followed by the ICC relies on the winnings and defeats of the teams. The model used by the ICC to implement rankings is deficient in certain key respects. It ignores key factors like winning margin and strength of the opposition. Various measures of the ranking concept are presented in this research. The proposed methods adopt the concepts of h-Index and PageRank for presenting more comprehensive ranking metrics. The proposed approaches not only rank… More >

  • Open Access

    ARTICLE

    Towards Improving the Intrusion Detection through ELM (Extreme Learning Machine)

    Iftikhar Ahmad1, *, Rayan Atteah Alsemmeari1

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1097-1111, 2020, DOI:10.32604/cmc.2020.011732

    Abstract An IDS (intrusion detection system) provides a foremost front line mechanism to guard networks, systems, data, and information. That’s why intrusion detection has grown as an active study area and provides significant contribution to cyber-security techniques. Multiple techniques have been in use but major concern in their implementation is variation in their detection performance. The performance of IDS lies in the accurate detection of attacks, and this accuracy can be raised by improving the recognition rate and significant reduction in the false alarms rate. To overcome this problem many researchers have used different machine learning techniques. These techniques have limitations… More >

  • Open Access

    ARTICLE

    Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection

    Machiraju Jayalakshmi1, *, S. Nagaraja Rao2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710

    Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

  • Open Access

    ARTICLE

    Mitigating and Monitoring Smart City Using Internet of Things

    Sudan Jha1, Lewis Nkenyereye2, *, Gyanendra Prasad Joshi3, Eunmok Yang4

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1059-1079, 2020, DOI:10.32604/cmc.2020.011754

    Abstract The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus… More >

  • Open Access

    ARTICLE

    DL-HAR: Deep Learning-Based Human Activity Recognition Framework for Edge Computing

    Abdu Gumaei1, 2, *, Mabrook Al-Rakhami1, 2, Hussain AlSalman2, Sk. Md. Mizanur Rahman3, Atif Alamri1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1033-1057, 2020, DOI:10.32604/cmc.2020.011740

    Abstract Human activity recognition is commonly used in several Internet of Things applications to recognize different contexts and respond to them. Deep learning has gained momentum for identifying activities through sensors, smartphones or even surveillance cameras. However, it is often difficult to train deep learning models on constrained IoT devices. The focus of this paper is to propose an alternative model by constructing a Deep Learning-based Human Activity Recognition framework for edge computing, which we call DL-HAR. The goal of this framework is to exploit the capabilities of cloud computing to train a deep learning model and deploy it on lesspowerful… More >

  • Open Access

    ARTICLE

    Second Law Analysis and Optimization of Elliptical Pin Fin Heat Sinks Using Firefly Algorithm

    Nawaf N. Hamadneh1, Waqar A. Khan2, Ilyas Khan3, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1015-1032, 2020, DOI:10.32604/cmc.2020.011476

    Abstract One of the most significant considerations in the design of a heat sink is thermal management due to increasing thermal flux and miniature in size. These heat sinks utilize plate or pin fins depending upon the required heat dissipation rate. They are designed to optimize overall performance. Elliptical pin fin heat sinks enhance heat transfer rates and reduce the pumping power. In this study, the Firefly Algorithm is implemented to optimize heat sinks with elliptical pin-fins. The pin-fins are arranged in an inline fashion. The natureinspired metaheuristic algorithm performs powerfully and efficiently in solving numerical global optimization problems. Based on… More >

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