Jing Wang^1,*, Xiaohe Qiu¹, Yuanfei Tu¹

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 227-244, 2019, DOI:10.32604/cmc.2019.05281

Abstract The MDS-MAP (multidimensional scaling-MAP) localization algorithm utilize almost merely connectivity information, and therefore it is easy to implement in practice of wireless sensor networks (WSNs). Anisotropic networks with energy hole, however, has blind communication spots that cause loss of information in the merging phase of MDSMAP. To enhance the positioning accuracy, the authors propose an MDS-MAP (CH) algorithm which can improve the clustering and merging strategy. In order to balance the effect of energy consumption and the network topology stabilization, we present a weighted clustering scheme, which considers the residual energy, the degree of connectivity nodes and node density. As… More >

Assia Maamar^1,*, Khelifa Benahmed²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we propose a hybrid approach to… More >

Yongzheng Lin¹, Hong Liu^{1, ∗}, Zhenxiang Chen², Kun Zhang², Kun Ma²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 245-257, 2019, DOI:10.32604/cmc.2019.04322

Abstract Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find… More >

Wentao Zhao¹, Pan Li^1,*, Chengzhang Zhu^1,2, Dan Liu¹, Xiao Liu¹

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 817-832, 2019, DOI:10.32604/cmc.2019.05957

Abstract The defense techniques for machine learning are critical yet challenging due to the number and type of attacks for widely applied machine learning algorithms are significantly increasing. Among these attacks, the poisoning attack, which disturbs machine learning algorithms by injecting poisoning samples, is an attack with the greatest threat. In this paper, we focus on analyzing the characteristics of positioning samples and propose a novel sample evaluation method to defend against the poisoning attack catering for the characteristics of poisoning samples. To capture the intrinsic data characteristics from heterogeneous aspects, we first evaluate training data by multiple criteria, each of… More >

Yuqing Yang^1,2, Dequn Zhou^1,*, Xiaojiang Yang^1,3,4

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 625-633, 2019, DOI:10.32604/cmc.2019.05246

Abstract Massive open online courses (MOOC) have recently gained worldwide attention in the field of education. The manner of MOOC provides a new option for learning various kinds of knowledge. A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups. However, most current algorithms mainly focus on the final grade of the learners, which may result in an improper classification. To overcome the shortages of the existing algorithms, a novel multi-feature weighting based K-means (MFWK-means) algorithm is proposed in this paper. Correlations between the widely used feature grade and other… More >

Sunil Kr. Jha¹, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 443-459, 2017, DOI:10.3970/cmes.2017.113.443

Abstract Microbial population and enzyme activities are the significant indicators of soil strength. Soil microbial dynamics characterize microbial population and enzyme activities. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, like rock phosphate solubilization, bacterial population, and ACC-deaminase activity. More specifically, optimized subtractive clustering (SC) and Wang and Mendel's (WM) fuzzy inference systems (FIS) have been implemented with the objective to achieve the best estimation accuracy of microbial dynamics. Experimental measurements were performed using controlled pot experiment using minimal salt media with rock phosphate as sole carbon source inoculated with… More >

R.D. Phillips¹, M.S. Hossain¹, L.T. Watson^1,2, R.H. Wynne³, Naren Ramakrishnan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.97, No.2, pp. 175-197, 2014, DOI:10.3970/cmes.2014.097.175

Abstract Clusters, typically mined by modeling locality of attribute spaces, are often evaluated for their ability to demonstrate ‘enrichment’ of categorical features. A cluster enrichment procedure evaluates the membership of a cluster for significant representation in predefined categories of interest. While classical enrichment procedures assume a hard clustering definition, this paper introduces a new statistical test that computes enrichments for soft clusters. Application of the new test to several scientific datasets is given. More >

Zone-Ching Lin¹, Chen-Hsing Cheng²

CMES-Computer Modeling in Engineering & Sciences, Vol.68, No.1, pp. 25-54, 2010, DOI:10.3970/cmes.2010.068.025

Abstract This study considers loadings on the multi-layer web frame structure and uses a novel method of the modified analytical hierarchy process (AHP) combined with modified theory of inventive problem solving (TRIZ) clustering to perform the creative structure design. The engineering knowledge of multi-layer web frame structure comprises such issues as vibration, yielding and buckling strength. Using the modified AHP, this study firstly applies the ratios of occurrence numbers of related keywords on different hierarchies to analyze the techniques and functions of multi-layer web frame structure, and finds out the priority order of feasible design decisions. Furthermore, this study also proposes… More >

A. Aimi¹, M. Diligenti¹, F. Lunardini¹, A. Salvadori²

CMES-Computer Modeling in Engineering & Sciences, Vol.4, No.1, pp. 31-50, 2003, DOI:10.3970/cmes.2003.004.031

Abstract This paper is devoted to the study of a new application of the Panel Clustering Method [Hackbusch and Sauter (1993); Hackbusch and Nowak (1989)]. By considering a classical 3D Neumann screen problem in its boundary integral formulation discretized with the Galerkin BEM, which requires the evaluation of double integrals with hypersingular kernel, we recall and use some recent results of analytical evaluation of the inner hypersingular integrals. Then we apply the Panel Clustering Method (PCM) for the evaluation of the outer integral. For this approach error estimate is shown. Numerical examples and comparisons with classical PCM technique are presented. More >

Chuanli Wang^1,2, En Zhu¹, Xinwang Liu¹, Jiaohua Qin², Jianping Yin^3,*, Kaikai Zhao⁴

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 409-421, 2019, DOI:10.32604/cmc.2019.06206

Abstract Multiple kernel clustering based on local kernel alignment has achieved outstanding clustering performance by applying local kernel alignment on each sample. However, we observe that most of existing works usually assume that each local kernel alignment has the equal contribution to clustering performance, while local kernel alignment on different sample actually has different contribution to clustering performance. Therefore this assumption could have a negative effective on clustering performance. To solve this issue, we design a multiple kernel clustering algorithm based on self-weighted local kernel alignment, which can learn a proper weight to clustering performance for each local kernel alignment. Specifically,… More >