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 More >

Yujie Zhang¹, Genlin Ji^1,*, Bin Zhao¹, Bo Sheng²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 885-901, 2019, DOI:10.32604/cmc.2019.05612

Abstract The discovery of gradual moving object clusters pattern from trajectory streams allows characterizing movement behavior in real time environment, which leverages new applications and services. Since the trajectory streams is rapidly evolving, continuously created and cannot be stored indefinitely in memory, the existing approaches designed on static trajectory datasets are not suitable for discovering gradual moving object clusters pattern from trajectory streams. This paper proposes a novel algorithm of gradual moving object clusters pattern discovery from trajectory streams using sliding window models. By processing the trajectory data in current window, the mining algorithm can capture 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 More >

SangWook Han¹, JungYeon Seo¹, Dae-Young Kim², SeokHoon Kim³, HwaMin Lee^3,*

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 697-711, 2019, DOI:10.32604/cmc.2019.06071

Abstract Air pollution caused by fine dust is a big problem all over the world and fine dust has a fatal impact on human health. But there are too few fine dust measuring stations and the installation cost of fine dust measuring station is very expensive. In this paper, we propose Cloud-based air pollution information system using R. To measure fine dust, we have developed an inexpensive measuring device and studied the technique to accurately measure the concentration of fine dust at the user’s location. And we have developed the smartphone application to provide air pollution 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 More >

Guojian Li¹, Qiang Wang¹, Yongze Cao¹, Kai Wang¹, Jiaojiao Du¹, Jicheng He¹

CMC-Computers, Materials & Continua, Vol.30, No.3, pp. 195-206, 2012, DOI:10.3970/cmc.2012.030.195

Abstract This paper studies the influence of Ag atomic segregation on the structural evolutions of the mixed (PdAg)₃₀₉ clusters during the heating processes by using molecular dynamics with a general embedded atom method. The results show that the Ag atomic segregation makes the cluster exhibit a segregate-melting stage in which the energy does not monotonic increase with the increase of temperature. In this stage, the cluster first transforms to form a disorder structure from the initial icosahedron and then a decahedron. By comparing with the cases in the pure Pd₃₀₉, Ag₃₀₉, and core-shell (PdAg)₃₀₉, it is found that More >

Cheng-Hung San¹, Chuang-Pin Chiu¹, Che-Wun Hong^1,2

CMC-Computers, Materials & Continua, Vol.26, No.3, pp. 167-186, 2011, DOI:10.3970/cmc.2011.026.167

Abstract An improvement in the catalytic process of oxygen reduction reactions is of prime importance for further progress in low temperature fuel cell performance. This paper intends to investigate this problem from a fundamental quantum mechanics viewpoint. For this purpose, a hybrid density functional theory is employed to analyze the catalytic mechanism of the oxygen reduction at the fuel cell cathode. Major steps in the oxygen reduction that include the oxygen adsorption on solid metal clusters (e.g. Cu and Pt) and complete four proton transfer steps are simulated. Proton transfer processes from hydroniums to the adsorbed 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 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 >

J.E. Lee¹and S.J. Kim²

CMES-Computer Modeling in Engineering & Sciences, Vol.86, No.2, pp. 93-112, 2012, DOI:10.3970/cmes.2012.086.093

Abstract As the option trading nowadays has become popular, it is important to simulate efficiently large amounts of option pricings. The purpose of this paper is to show valuations of large amount of options, using network distribute computing resources. We valuated 108 options simultaneously on the self-made cluster computer system which is very inexpensive, compared to the supercomputer or the GPU adopting system. For the numerical valuations of options, we developed the option pricing software to solve the Black-Scholes partial differential equation by the finite element method. This yielded accurate values of options and the Greeks More >