EXTENDED CLUSTERING COEFFICIENTS：GENERALIZATION OF CLUSTERING COEFFICIENTS IN SMALL-WORLD NETWORKS

The clustering coefficient C of a network, which is a measure of direct connectivity between neighbors of the various nodes, ranges from 0 （for no connectivity） to 1 （for full connectivity）. We define extended clustering coefficients C（h） of a small-world network based on nodes that are at distance h from a source node, thus generalizing distance-1 neighborhoods employed in computing the ordinary clustering coefficient C = C（1）. Based on known results about the distance distribution Pδ（h） in a network, that is, the probability that a randomly chosen pair of vertices have distance h, we derive and experimentally validate the law Pδ（h）C（h） ≤ c log N / N, where c is a small constant that seldom exceeds 1. This result is significant because it shows that the product Pδ（h）C（h） is upper-bounded by a value that is considerably smaller than the product of maximum values for Pδ（h） and C（h）. Extended clustering coefficients and laws that govern them offer new insights into the structure of small-world networks and open up avenues for further exploration of their properties.     

Random evolving networks under the diameter and average connectivity constraint

In this paper, under the constraint that the average distance and the average degree （k） remain approximately constant, we studied a random scale-free network model. We found that, if the network maintains the form of its degree distribution and the maximal degree kc is N-dependent cutoff function kc（N）〈 N, the degree distribution would be approximately power-law with an exponent between 2 and 3. The distribution exponent has little relationship with the average degree, denoted by （k）. The diameter constraint can be interpreted as an environmental selection pressure, which could explain the scale-free nature of networks. The numerical results indicate that, under the diameter constraint, the preferential attachment can produce the cutoff function kc（N）〈 N and power-law degree distribution.     

Hume'sAbstract exhumed

‘As it is now clear that Hume is the Author of theAbstract, this short work can be enthusiastically recommended to those who wish to consider Hume's own account of the chief argument of theTreatise’ (Norton, 1993a). This ‘simplification’ of Hume'sAbstract aims to make it more accessible to a wider audience, especially to readers who do not have English as their first language. Some of Hume's own invented terms have been translated, many of his longer sentences divided, and most of his expressions simplified. The sequence of his arguments is preserved. Where needed, his arguments have been set out in traditional form. Topic headings have been added and some definitions appended. To ease reference to theAbstract, as published in Hume (1740b), the page numbers have been inserted near their correct position in square brackets.     

A perishable inventory system with service facilities, <Emphasis Type="Italic">MAP</Emphasis> arrivals and <Emphasis Type="Italic">PH</Emphasis> — Service times

We consider a continuous review perishable （s,S） inventory system with a service facility consisting of a waiting hall of finite capacity and a single server. We assume two types of customers, ordinary and negative, arrive according to a Markovian Arrival Process （MAP）. An ordinary customer joins the queue and a negative customer instead of joining the queue removes one ordinary customer from the queue. The removal rule adopted in this paper is RCE （removal of a customer from the end）. The individual customer＇s unit demand is satisfied after a random time of service which is assumed to have a phase-type distribution. The life time of each item and the lead time of the reorders have been assumed to be independent exponential distributions. The joint probability distribution of the number of customers in the system and the inventory level is obtained for the steady state case. Various stationary system performance measures are computed and the total expected cost rate is calculated. The results are illustrated numerically.     

The Ore-Sato Theorem and Shift Exponents in the q-Difference Case

The authors translate the main results in the paper entitled "Multiplicative Decomposition of Multivariate q-Hypergeometric Terms" from Chinese into English. The paper is written by Shaoshi Chen, Ruyong Feng, Guofeng Fu and Jing Kang, and published in Journal of Mathematics and Systems Science, 32(8), 1019–1032, 2012. Some minor simpli?cation and modi?cation are made during the translation. Based on the results in the above paper, a special form is derived for q-shift exponents appearing in the q-shift quotients of a q-hypergeometric term.     

The M/M/1 queue with working vacations and vacation interruptions

In this paper, we study the M/M/1 queue with working vacations and vacation interruptions. The working vacation is introduced recently, during which the server can still provide service on the original ongoing work at a lower rate. Meanwhile, we introduce a new policy：, the server can come back from the vacation to the normal working level once some indices of the system, such as the number of customers, achieve a certain value in the vacation period. The server may come back from the vacation without completing the vacation. Such policy is called vacation interruption. We connect the above mentioned two policies and assume that if there are customers in the system after a service completion during the vacation period, the server will come back to the normal working level. In terms of the quasi birth and death process and matrix-geometric solution method, we obtain the distributions and the stochastic decomposition structures for the number of customers and the waiting time and provide some indices of systems.     

“EII META—MODEL” ON INTEGRATION FRAMEWORK FOR VIABLE ENTERPRISE SYSTEMS——CITY PLANNING METAPHOR BASED ON STRUCTURAL SIMILARITY

Enterprise systems must have the structure to adapt the change of business environment.When rebuilding enterprise system to meet the extended operational boundaries,the concept of IT city planning is applicable and effective.The aim of this paper is to describe the architectural approach from the integrated imformation infrastructure(In3) standpoint and to propose for applying the “City Planning” concept for rebuilding “inter-application spaghetti” enterprise systems.This is mainly because the portion of infrastructure has increased with the change of information systems from centralized systems to distributed and open systems.As enterprise systems have involved heterogeneity or architectural black box in them,it may be required the integration framework (meta-architecture)as a discipline based on heterogeneity that can provide comprehensive view of the enterprise systems.This paper proposes “EII Meta-model” as the integration framework that can optimize the overall enterprise systems from the IT city planning point of view.EII Meta-model consists of “Integrated Information Infrastructure Map(In3-Map)”,“Service&#183;Framework” and “IT Scenario”.It would be applicable and effective for the viable enterprise,because it has the mechanism to adapt the change.Finally,we illustrate a case of information system in an online securities company and demonstrate spplicability and effectiveness of EII Meta-model to meet their business goals.     

A multi-objective robust operation model for electronic market enabled supply Chain with uncertain demands

A multi-objective robust operation model is proposed in this paper for an electronic market enablexi supply chain consisting of multi-supplier and multi-customer with uncertain demands. Suppliers in this supply chain provide many kinds of products to different customers directly or through electronic market. Uncertain demands are described as a scenario set with certain probability;, the supply chain operation model is constructed by using the robust optimization method based on scenario analyses. The operation model we proposed is a multi-objective programming problem satisfying several conflict objectives, such as meeting the demands of all customers, minimizing the system cost, the availabilities of suppliers＇ capacities not below a certain level, and robustness of decision to uncertain demands. The results of numerical examples proved that the solution of the model is most conservative; however, it can ensure the robustness of the operation of the supply chain effectively.     

Data crystallization applied for designing new products

It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable events. This is realized by data crystallization, where dummy items, corresponding to potential existence ofunobservable events, are inserted to the given data. These dummy items and their relations with observable events are visualized by applying KeyGraph to the data with dummy items, like the crystallization of snow where dusts are involved in the formation of crystallization of water molecules. For tuning the granularity level of structure to be visualized, the tool of data crystallization is integrated with human＇s process of understanding significant scenarios in the real world. This basic method is expected to be applicable for various real world domains where previous methods of chance-discovery lead human to successful decision making. In this paper, we apply the data crystallization with human-interactive annealing （DCHA） to the design of products in a real company. The results show its effect to industrial decision making.     

FUZZY SATISFYING INTERACTIVE MULTIOBJECTIVE THERMAL POWER DISPATCH： SWT APPROACH

In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution. In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz. cost, NOx emission, SOx emission and COx emission are minimized simultaneously. The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner. Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain. Exploiting fuzzy decision making theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off （SWT） functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker＇s preferences to non-inferior solutions through optimal weight patterns. The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses. Decoupled load flow analysis is performed to find the transmission losses. The validity of the proposed method is demonstrated on 11-bus, 17-lines IEEE system, comprising of three generators.     

Expert discovery and knowledge mining in complex multi-agent systems

Complex problem solving requires diverse expertise and multiple techniques. In order to solve such problems, complex multi-agent systems that include both of human experts and autonomous agents are required in many application domains. Most complex multi-agent systems work in open domains and include various heterogeneous agents. Due to the heterogeneity of agents and dynamic features of working environments, expertise and capabilities of agents might not be well estimated and presented in these systems. Therefore, how to discover useful knowledge from human and autonomous experts, make more accurate estimation for experts＇ capabilities and find out suitable expert（s） to solve incoming problems （＂Expert Mining＂） are important research issues in the area of multi-agent system. In this paper, we introduce an ontology-based approach for knowledge and expert mining in hybrid multi-agent systems. In this research, ontologies are hired to describe knowledge of the system. Knowledge and expert mining processes are executed as the system handles incoming problems. In this approach, we embed more self-learning and self-adjusting abilities in multi-agent systems, so as to help in discovering knowledge of heterogeneous experts of multi-agent systems.     

Soft Systems Methodology: Other Voices

This issue of Systemic Practice and Action Research, celebrating the work of Peter Checkland, in the particular nature and development of soft systems methodology (SSM), would not have happened unless the work was seen by others as being important. No significant contribution to thinking happens without a secondary literature developing. Not surprisingly, many commentaries have accompanied the ongoing development of SSM. Some of these are insightful, some full of errors, and some include both insight and absurdity. Checkland (1999, p. A42) opines, in the recently published 30-year retrospective, that "SSM has been ill-served by its commentators." Scrutiny of the secondary literature on SSM provides support for this view and also identifies some general characteristics and trends that are important to the development of SSM and, incidentally, reinforces some existing conclusions.     

Scheduling problems — An overview

There seems to be a significant gap between the theoretical and the practical aspects ofscheduling problems in the job shop environment. Theoretically, scheduling systems are designed onthe basis of an optimum approach to the scheduling model. However in the practice, the optimum thatis built into the scheduling applications seems to face some challenges when dealing with the dynamiccharacter of a scheduling system, for instance machine breakdown or change of orders. Schedulingsystems have become quite complex in the past few years. Competitive business environments andshorter product life cycles are the imminent challenges being faced by many companies these days.These challenges push companies to anticipate a demand driven supply chain in their businessenvironment. A demand-driven supply chain incorporates the customer view into the supply chainprocesses. As a consequence of this, scheduling as a core process of the demand-driven supply chainmust also reflect the customer view. In addition, other approaches to solving scheduling problems, forinstance approaches based on human factors, prefer the scheduling system to be more flexible in bothdesign and implementation. After discussion of these factors, the authors propose the integration of adifferent set of criteria for the development of“ scheduling systems which not only appears to have abetter flexibility but also increased customer-focus.     

系统论视域下的英文媒体新词语监测研究

本文从系统论的视角,对国内语言资源监测研究重新定位,指出国内英文媒体也属于语言资源的一部分,完整的语言资源监测研究系统还应包括对国内英文使用情况的监测。选取新词语作为监测对象,提出了国内主流英文媒体语料库建设和新词语提取方法。     

CUSTOMER EQUITY： MAKING MARKETING STRATEGY FINANCIALLY ACCOUNTABLE

1. Introduction The long-term value of a firm is largelydetermined by the value of the company’scustomer relationships, which result in thefirm’s ‘customer equity’ (Blattberg andDeighton 1996), defined by Rust, Lemon andZeithaml (2000, p.4…     

A NESTED PARTITIONS FRAMEWORK FOR SOLVING LARGE-SCALE MULTICOMMODITY FACILITY LOCATION PROBLEMS

Large-scale multicommodity facility location problems are generally intractable with respect to standard mixed-integer programming (MIP) tools such as the direct application of general-purpose Branch & Cut (BC) commercial solvers i.e. CPLEX. In this paper, the authors investigate a nested partitions (NP) framework that combines meta-heuristics with MIP tools (including branch-and-cut). We also consider a variety of alternative formulations and decomposition methods for this problem class. Our results show that our NP framework is capable of efficiently producing very high quality solutions to multicommodity facility location problems. For large-scale problems in this class, this approach is significantly faster and generates better feasible solutions than either CPLEX (applied directly to the given MIP) or the iterative Lagrangian-based methods that have generally been regarded as the most effective structure-based techniques for optimization of these problems. We also briefly discuss some other large-scale MIP problem classes for which this approach is expected to be very effective. This work is supported partly by the National Science Foundation under grant DMI-0100220, DMI-0217924, by the Air Force of Scientific Research under grant F49620-01-1-0222, by Rockwell Automation, and by John Deere Horicon Works. Leyuan Shi is a Professor of the Department of Industrial Engineering at University of Wisconsin-Madison. She received her Ph.D. in Applied Mathematics from Harvard University in 1992, her M.S. in Engineering from Harvard University in 1990, her M.S. in Applied Mathematics from Tsinghua University in 1985, and her B.S. in Mathematics from Nanjing Normal University in 1982. Dr. Shi has been involved in undergraduate and graduate teaching, as well as research and professional service. Dr. Shi’s research is devoted to the theory and applications of large-scale optimization algorithms, discrete event simulation and modeling and analysis of discrete dynamic systems. She has published many papers in these areas. Her work has appeared in Discrete Event Dynamic Systems, Operations Research, Management Science, IEEE Trans., and, IIE Trans. She is currently a member of the editorial board for Journal of Manufacturing & Service Operations Management, is an Associate Editor of Journal of Discrete Event Dynamic Systems, and an Associate Editor of INFORMS Journal on Computing. Dr. Shi is a member of IEEE and INFORMS. Robert R. Meyer received a B.S. in Mathematics from Caltech and an M.S. and a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. He is currently Professor of Computer Sciences at the University of Wisconsin-Madison, where he has been on the faculty since 1973. He has co-edited six volumes of optimization conference proceedings and written more than 80 articles focusing on areas such as nonlinear network optimization, parallel decomposition algorithms for large-scale optimization, genetic algorithms, and theory and applications of discrete optimization. Mehmet Bozbay is a research assistant in the Department of Industrial Engineering at University of Wisconsin-Madison. He is currently working towards his Ph.D. degree in Industrial Engineering. He received M.S. degrees in Industrial Engineering and Computer Sciences from University of Wisconsin-Madison, and a B.S. degree in Mathematics from Beloit College. He has been dealing with real-life supply chain optimization problems for the last 4 years. He is a member of INFORMS. Andrew J. Miller is an Assistant Professor of the Department of Industrial Engineering at the University of Wisconsin—Madison. He received his Ph.D. in Industrial Engineering from the Georgia Institute of Technology in 1999, his M.S. in Operations Research from the Georgia Institute of Technology in 1996, and his B.S. in Mathematics from Furman University in 1994. Dr. Miller has been involved in research, undergraduate and graduate teaching, and professional service, as well as in some software prototyping and development. Dr. Miller’s research focuses on theoretical and computational aspects of mixed integer programming, and on its application to areas in production planning, supply chain design, and other fields. He has published several papers in these areas, including articles in Mathematical Programming, Operations Research, and European Journal of Operations Research. He has refereed numerous articles for the journals mentioned above, as well as for Management Science, Annals of Operations Research, and others. Dr. Miller is a member of INFORMS and of the Mathematical Programming Society.     

Using an Action Research Framework to Explore Assessment: A South African Case Study

This article is a reflection of my first experience with action research in trying to devise a system of assessment that would benefit both first and second language speakers of English in an assessment system that is plagued by its separatist past. In this paper, I discuss an action research study on oral assessment implemented at two tertiary institutions in South Africa. The actual details of each phase of the assessments are not reported on, but the methods used to facilitate the processes are. The findings and adaptations after each phase of the assessments are discussed to show the effectiveness of using an action research methodology.

PHASE TRANSITION IN SEQUENCE UNIQUE RECONSTRUCTION

In this paper, sequence unique reconstruction refers to the property that a sequence is uniquely reconstructable from all its K-tuples. We propose and study the phase transition behavior of the probability P（K） of unique reconstruction with regard to tuple size K in random sequences （iid model）. Based on Monte Carlo experiments, artificial proteins generated from lid model exhibit a phase transition when P（K） abruptly jumps from a low value phase （e.g. 〈 0.1） to a high value phase （e.g. 〉 0.9）. With a generalization to any alphabet, we prove that for a random sequence of length L, as L is large enough, P（K） undergoes a sharp phase transition when p ≤ 0.1015 where p = P （two random letters match）. Besides, formulas are derived to estimate the transition points, which may be of practical use in sequencing DNA by hybridization. Concluded from our study, most proteins do not deviate greatly from random sequences in the sense of sequence unique reconstruction, while there are some ＂stubborn＂ proteins which only become uniquely reconstructable at a very large K and probably have biological implications.     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

绿色生产研究进展与展望:基于文献计量分析

基于比较视角理清绿色生产研究的演变路径、研究框架及趋势,并形成值得中国发展借鉴的"技术路径"和"发展模式"具有重要价值.本研究运用Citespace和VOSviewer软件,对1985-2018年Web of Science和中国知网收录的1082篇国际学者发表的英文文献、1513篇中国学者发表的中英文文献所呈现的关键词、主题等进行对比分析,结果发现:1)从发文量看,国际与中国绿色生产研究的发文量呈逐年上升趋势,自2008年起,中国绿色生产研究的发文量和上升趋势显著高于国际绿色生产研究.2)从高频关键词看,国际绿色生产研究多与工业绩效、可持续发展相联系;中国绿色生产研究与精益生产、循环低碳发展联系紧密.3)从研究热点看,国际绿色生产研究关注的是宏观+微观角度下的环境污染物质、污染治理、行为与治理主体多元化.中国绿色生产研究关注的是宏观视角下的发展战略、生产方式优化和"工业-环境-政策"一体化.4)从高频关键词聚类看,国际和中国绿色生产研究均可以基于"个体-组织-社会"系统逻辑视角呈现聚焦主题.国际绿色生产研究的主题为个体绿色态度与行为、工业技术发展与生态共生、绿色生产与可持续发展、政府监督与政策引导.中国绿色生产研究的主题为个体绿色消费、企业管理与审核、绿色生产与可持续发展和环保机构及相关法规制定.最后,本研究分别提出国际与中国绿色生产研究未来展望,以期为绿色生产实践提供借鉴.