The Experts below are selected from a list of 60579 Experts worldwide ranked by ideXlab platform
Alex T. Chow - One of the best experts on this subject based on the ideXlab platform.
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Turbulence structures in non-uniform flows
Advances in Water Resources, 2008Co-Authors: Shu-qing Yang, Alex T. ChowAbstract:This study investigates turbulence structures in steady and non-uniform flows. Equations of Reynolds shear stress and turbulent velocity fluctuations are derived and their physical interpretations are explained. The theoretical results show that, different from previous studies, the variation of water surface can generate the wall-normal velocity, resulting in deviations of Reynolds shear stress and turbulence intensities from those in uniform flows. A self-Similarity Relationship is found between the Reynolds shear stress and turbulence intensities in non-uniform flows. The existence of self-Similarity indicates that the effect of non-uniformity does not influence the mixing length. An empirical equation has been proposed to express the Relationship based on experimental data available in the literature. Good agreement is achieved between the measured and predicted turbulence intensities by applying the self-Similarity Relationship.
Hemant K Jain - One of the best experts on this subject based on the ideXlab platform.
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manufacturing service composition model based on synergy effect a social network analysis approach
Applied Soft Computing, 2018Co-Authors: Minglun Ren, Lei Ren, Hemant K JainAbstract:Abstract Service social network is an umbrella term used to describe several interaction and collaboration phenomena that are shaping the future of how services are provided on the cloud manufacturing platform. Social Relationship plays an important role when services are orchestrated with each other to build manufacturing business process, a role which has not been adequately investigated in previous research. The existing manufacturing service composition methods consider functional qualifications and Quality of Service (QoS) as major competitiveness factors. It is difficult to adopt them to situations where synergy effect is required and social Relationships have significant impact on ensuring effective resources, information and knowledge hand-off in the complex task process. Focusing on the social collaboration feature of manufacturing services, a service composition method based on synergy effect is proposed. According to the data of service interaction and cooperation on the cloud platform, we extract and describe service social network and five kinds of Relationships, namely interactive transaction, co-community, physical distance, resource-related, social Similarity Relationship. Based on the calculation of these Relationships strength, the service synergy network is derived through the weighted aggregation. A service selection model that maximizes the overall synergy effect based on collaboration requirement is presented. The validity and advantages of our model and algorithm is validated through simulation experiment of intelligent automobile cloud manufacturing. The results show that our approach is not only efficient, but also finds better service scheme in line with the actual manufacturing scenario.
Ronald R. Yager - One of the best experts on this subject based on the ideXlab platform.
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Drawing reasonable conclusions from information under Similarity modelled contexts
International Journal of Granular Computing Rough Sets and Intelligent Systems, 2009Co-Authors: Ronald R. YagerAbstract:We are interested in the process of making reasonable conclusions about the value of a variable. We indicate that reasonableness generally depends on the information we have about the variable as well as the context in which we shall use the assumed value. In order to include a wide range of imprecise and uncertain information, we use granular computing technologies such as fuzzy sets, Dempster-Shafer belief structures and probability theory to represent our knowledge and conclusions. While context is a very diverse idea, in order to provide some structure, we restrict ourselves to the special case where context can be modelled using a Similarity Relationship. Within this framework, we suggest a measure of the reasonableness of drawing conclusions from information in the context of a Similarity Relationship. We look at the properties of this measure and investigate its performance in a number of special cases.
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Measures of specificity over continuous spaces under Similarity relations
Fuzzy Sets and Systems, 2008Co-Authors: Ronald R. YagerAbstract:We introduce the concept of specificity and indicate its importance as a measure of uncertainty for information represented using fuzzy sets or possibility distributions. We provide formal measures of specificity for variables whose domain is an interval of the real line. Similarity relations are discussed and formalized. The class of width-based Similarity relations is introduced. We extend the measure of specificity to allow for the effect of an underlying Similarity Relationship. The manifestation of this extension for a number of different Similarity relations is investigated. Particularly notable results are obtained for width-based Similarity Relationships. More generally we note the connection between the size of a granule of information and its uncertainty. Motivated by this we investigate the effect of a Similarity Relationship on the perception of distance in the underlying space and use this to develop an extension of the specificity measure.
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Entropy measures under Similarity relations
International Journal of General Systems, 1992Co-Authors: Ronald R. YagerAbstract:We discuss the Shannon measure of entropy. An extension of this measure is provided for situations in which the underlying items of concern have a Similarity Relationship in addition to a probability distribution defined on them
Tao Peng - One of the best experts on this subject based on the ideXlab platform.
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CloudCom - A Novel Method for Mining SaaS Software Tag via Community Detection in Software Services Network
Lecture Notes in Computer Science, 2009Co-Authors: Li Qin, Weifeng Pan, Tao PengAbstract:The number of online software services based on SaaS paradigm is increasing. However, users usually find it hard to get the exact software services they need. At present, tags are widely used to annotate specific software services and also to facilitate the searching of them. Currently these tags are arbitrary and ambiguous since mostly of them are generated manually by service developers. This paper proposes a method for mining tags from the help documents of software services. By extracting terms from the help documents and calculating the Similarity between the terms, we construct a software Similarity network where nodes represent software services, edges denote the Similarity Relationship between software services, and the weights of the edges are the Similarity degrees. The hierarchical clustering algorithm is used for community detection in this software Similarity network. At the final stage, tags are mined for each of the communities and stored as ontology.
Shu-qing Yang - One of the best experts on this subject based on the ideXlab platform.
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The prediction of turbulence intensities in unsteady flow
2014Co-Authors: Ishraq Alfadhli, Shu-qing Yang, Muttucumaru SivakumarAbstract:This study investigates the distribution of turbulence intensities in unsteady non-uniform flows. Yang and Chow's (2008) work was extended to express this distribution based on the Relationship between Reynolds shear stress and turbulence intensities in unsteady flow. It was found a self-Similarity Relationship between Reynolds shear stress and turbulence intensities in unsteady flow. This Relationship has been developed as empirical equations based on experimental data available in the literature. By applying the self-Similarity Relationship, good agreements between the measured and predicted turbulence intensities have been achieved.
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Turbulence structures in non-uniform flows
Advances in Water Resources, 2008Co-Authors: Shu-qing Yang, Alex T. ChowAbstract:This study investigates turbulence structures in steady and non-uniform flows. Equations of Reynolds shear stress and turbulent velocity fluctuations are derived and their physical interpretations are explained. The theoretical results show that, different from previous studies, the variation of water surface can generate the wall-normal velocity, resulting in deviations of Reynolds shear stress and turbulence intensities from those in uniform flows. A self-Similarity Relationship is found between the Reynolds shear stress and turbulence intensities in non-uniform flows. The existence of self-Similarity indicates that the effect of non-uniformity does not influence the mixing length. An empirical equation has been proposed to express the Relationship based on experimental data available in the literature. Good agreement is achieved between the measured and predicted turbulence intensities by applying the self-Similarity Relationship.