An empirical method for assessing the research relevance gap

There has been much debate on the relevance to firms of the academic research produced by business schools. However, what has not received as much attention is how the relevance of the research to businesses should be measured in a systematic and empirical way. We develop a systematic method to test for the relevance of academic research to businesses. Our method models as a vector autoregressive process the interests of the academic and practitioner communities in some new topic, as expressed by the number of articles published in the academic and the practitioner literature on that topic per calendar quarter, and then studies Granger causality between the academic and practitioner interest processes. This method can be used by academics to empirically demonstrate the impact of their intellectual contributions on practitioners and thence on the business world. We employ our approach to two relatively new and important topics, Real Options and Economic Value Added.     

Toward a situation model in a cognitive architecture

The ability to coherently represent information that is situationally relevant is vitally important to perform any complex task, especially when that task involves coordinating with team members. This paper introduces an approach to dynamically represent situation information within the ACT-R cognitive architecture in the context of a synthetic teammate project. The situation model represents the synthetic teammate’s mental model of the objects, events, actions, and relationships encountered in a complex task simulation. The situation model grounds textual information from the language analysis component into knowledge usable by the agent-environment interaction component. The situation model is a key component of the synthetic teammate as it provides the primary interface between arguably distinct cognitive processes modeled within the synthetic teammate (e.g., language processing and interactions with the task environment). This work has provided some evidence that reasoning about complex situations requires more than simple mental representations and requires mental processes involving multiple steps. Additionally, the work has revealed an initial method for reasoning across the various dimensions of situations. One purpose of the research is to demonstrate that this approach to implementing a situation model provides a robust capability to handle tasks in which an agent must construct a mental model from textual information, reason about complex relationships between objects, events, and actions in its environment, and appropriately communicate with task participants using natural language. In this paper we describe an approach for modeling situationally relevant information, provide a detailed example, discuss challenges faced, and present research plans for the situation model.     

Email Surveillance Using Non-negative Matrix Factorization

In this study, we apply a non-negative matrix factorization approach for the extraction and detection of concepts or topics from electronic mail messages. For the publicly released Enron electronic mail collection, we encode sparse term-by-message matrices and use a low rank non-negative matrix factorization algorithm to preserve natural data non-negativity and avoid subtractive basis vector and encoding interactions present in techniques such as principal component analysis. Results in topic detection and message clustering are discussed in the context of published Enron business practices and activities, and benchmarks addressing the computational complexity of our approach are provided. The resulting basis vectors and matrix projections of this approach can be used to identify and monitor underlying semantic features (topics) and message clusters in a general or high-level way without the need to read individual electronic mail messages. Michael W. Berry is a Professor and Interim Department Head in the Department of Computer Science at the University of Tennessee and a faculty member in the Graduate School in Genome Science and Technology Program at the University of Tennessee and Oak Ridge National Laboratory. His research interests include information retrieval, data mining, scientific computing, computational science, and numerical linear algebra. He is a member of the Society for Industrial and Applied Mathematics (SIAM), Association for Computing Machinery (ACM), and the Computer Society of the Institute of Electrical and Electronics (IEEE). Professor Berry is on the editorial boards of “Computing in Science and Engineering” (IEEE Computer Society and the American Institute of Physics) and the SIAM Journal of Scientific Computing. Murray Browne is a Research Associate in the Department of Computer Science at the University of Tennessee. He is a member of the American Society for Information Science and Technology and has published numerous essays, book reviews, newspaper articles, and feature stories.     

The methods of fostering creativity through mathematical problem solving

Which methods could be used to foster mathematical creativity in school situations? The following topics are treated with the respect to this question: 1. “Open-ended approach” and “From problem to problem”, 2. Relation to mathematical creativity, 3. Teacher’s belief and the mathematics textbook.     

Notre Dame's Father Hesburgh

Abstract

Two topics that generated the most discussion throughout the Leadership Project are peer and mentoring relationships and their impact on leadership. Are the next generation of leaders in higher education connecting with each other? Are they connecting with mentors? And are these important things for them to do? In the articles that follow, two of the young leaders profiled in this survey—Michael Rao and Ted Mitchell—begin to explore these questions, with Rao focusing on peer relationships and Mitchell on the importance of mentoring.     

Control of a production-inventory system with returns under imperfect advance return information

We consider a production-inventory system with product returns that are announced in advance by the customers. Demands and announcements of returns occur according to independent Poisson processes. An announced return is either actually returned or cancelled after a random return lead time. We consider both lost sale and backorder situations. Using a Markov decision formulation, the optimal production policy, with respect to the discounted cost over an infinite horizon, is characterized for situations with and without advance return information. We give insights in the potential value of this information. Also some attention is paid to combining advance return and advance demand information. Further applications of the model as well as topics for further research are indicated.     

Book Review

Dynamics of One—Dimensional Maps by A. N. Sharkovsky, S. F. Kolyada, A. G. Sivak and Y. V. Fedorenko, Publisher: Kluwer Academic Publishers, Format: Hardcover, Publication Date: April 1997, 260 Pages. ISBN: 07923-4532-0, Price: $196=00. This is a nice and interesting introductory book on the dynamics of 1—dimensional maps. As stated by the authors, the book has two main goals. The first is to introduce the readers to the fundamentals of the theory of 1—dimensional dynamical systems. The second is to provide to the readers a comprehensive view of the problems appearing in the theory of dynamical systems and to describe the methods used to solve these problems in the case of 1—dimensional maps. The first chapter of this book is an elementary introduction to the theory of 1—dimensional maps. It contains an exposition of basic concepts of the theory of dynamical systems and a list of examples illustrating various situations encountered in the study of 1—dimensional maps. The second chapter deals with symbolic dynamics. It contains in particular a presentation of the kneading theory. The third chapter is on the Sharkovsky theorem, one of the most important early results in the theory of 1—dimensional maps. Chapter 4 contains, to a certain degree of details, a classification theory of 1—dimensional maps with zero entropy that mainly reflects the research interests of the authors. Chapter 5 is an introductory lecture to unimodal maps. Chapter 6 is on the aspect of 1—dimensional dynamics that is related to measure theory. Existence theorems on absolutely continuous invariant measures are discussed. Chapter 7 is on the problem of structure stability, and Chapter 8 is on fundamentals of 1—dimensional families of maps: bifurcation periodic doubling and universality.BOOK REVIEW This book touches a variety of topics, introduces basic concepts and presents many important early results that are fundamentally important to the study of 1—dimensional maps, Most of the materials the book covers have a distinctively topological flavor that occurs rather commonly in the study of dynamical systems up to the early 1980's. A substantial part of the text can be used directly in an introductory course on dynamical systems. On the other hand, readers should be reminded that there have been explosive new developments in the study of 1—dimensional maps since this book was written. One should definitely find books and survey articles that are more recent for an up—to—date view on this subject     

A network-based approach for increasing discrimination in data envelopment analysis

Data envelopment analysis (DEA) is known to produce more than one efficient decision-making unit (DMU). This paper proposes a network-based approach for further increasing discrimination among these efficient DMUs. The approach treats the system under study as a directed and weighted network in which nodes represent DMUs and the direction and strength of the links represent the relative relationship among DMUs. In constructing the network, the observed node is set to point to its referent DMUs as suggested by DEA. The corresponding lambda values for these referent DMUs are taken as the strength of the network link. The network is weaved by not only the full input/output model, but also by models of all possible input/output combinations. Incorporating these models into the system basically introduces the merits of each DMU under various situations into the system and thus provides the key information for further discrimination. Once the network is constructed, the centrality concept commonly used in social network analysis—specifically, eigenvector centrality—is employed to rank the efficient DMUs. The network-based approach tends to rank high the DMUs that are not specialized and have balanced strengths.     

Book Review

An Introduction to Difference Equations. Second Edition by Saber N. Elaydi, New York: Springer—Verlag, 1999. ISBN 0-387-98830-0. $54.95. Gone are the days when difference equations arose mainly in the context of sections of flows or as finite difference approximations to PDE's. Today difference equations have come into their own, both as objects of intrinsic mathematical interest and as dynamical models in their own right. Discrete models form an important part of dynamical systems theory independently from their continuous cousins. In Saber Elaydi's book dynamicists have the long awaited discrete counterpart to standard textbooks such as Hirsch and Smale (“Differential Equations, Dynamical Systems, and Linear Algebra”). The first edition of this book appeared in 1996. The second edition includes substantial new material including appendices on global stability and periodic solutions, a section on applications to mathematical biology, and a new chapter entitled “Applications to Continued Fractions and Orthogonal Polynomials”. Additional material on Birkhoff's theory now appears in the chapter on asymptotic behavior. The initial chapter covers first order equations, including equilibria, cobwebbing, stability, cycles, and the bifurcations of the discrete logistic equation. Chapter 2 moves on to higher order linear equations and briefly treats the difference calculus (for an in—depth treatment, see “Difference Equations: Theory and Applications. Second Edition” by Ronald E. Mickens, New York: Van Nostrand Reinhold, 1990). The subsequent chapters include systems of difference equations, stability theory, Z—transforms, control theory, oscillation theory, asymptotic behavior, and applications to continued fractions and orthogonal polynomials.

The chapters are composed of short sections, each of which ends with a nice selection of exercises. Answers to the odd—numbered problems appear in the back of the book. The core chapters include sections of applications to various fields such as population biology, economics, and physics. Several famous examples and topics are treated in the applications, including Gambler's Ruin, the Nicholson—Bailey host/parasitoid model, the heat equation, and Markov chains. Many discrete models are noninvertible, yet as many frustrated modelers know, most of the old standard treatments of linearization and the Stable Manifold Theorem., coming as they do from the context of sections of flows, require invertibility. Commendably, Elaydi avoids the needless assumption of invertibility in his stability theorems, and also in the Stable Manifold Theorem. However, invertibility is assumed in the Hartman—Grobman Theorem, where indeed it is necessary to establish conjugacy between the map and its linearization (see “An Introduction to Structured Population Dynamics”, CBMS—NSF Regional Conference Series in Applied Mathematics, Vol. 71, SIAM, Philadelphia, 1998 by J. M. Gushing, for an example of a noninvertible map for which the conjugacy fails. Readers may be interested to know that in this reference a weaker version of the Hartman—Grobman Theorem is proved that does not require invertibility but does establish the desired correspondence between types of hyperbolic equilibria in maps and their linearizations.)

This book is in Springer's Undergraduate Texts in Mathematics series and is indeed a very readable and appropriate text for advanced undergraduates or beginning graduate students. According to the author, the main prerequisites for such a course are calculus and linear algebra, with basic advanced calculus and complex analysis needed only for some topics in the later chapters. This is true; however in most situations the book would be best appreciated by students with a bit more mathematical maturity than is engendered by today's calculus and beginning linear algebra courses.Elaydi's book is a valuable reference for anyone who models discrete systems. It is so well written and well designed, and the content is so interesting to me, that I had a difficult time putting it down. I am pleased to own a copy for reference purposes, and am looking forward to using it to teach a senior topics course in difference equations.     

A fuzzy rough set approach to emergency material demand prediction over two universes

Emergency decision-making is still an important issue of unconventional emergency events management. Although many studies are developed on this topic, they remain political and qualitative, and it is difficult to make them operational in practice. Therefore, this article considers a fuzzy rough set over two universes model and approach for solving such a difficulty. As is well known, an exact and scientific emergency material demand prediction can make a quick and efficient emergency rescue and realize the optimal effect. Considering the main characteristics of emergency decision-making with insufficient risk identification, incomplete and inaccuracy of available information and uncertainty of decision-making environment, the fuzzy rough set theory over two universes is used to emergency material demand prediction. We propose a model and approach to emergency material demand prediction, i.e., the fuzzy rough set model of emergency material demand prediction over two universes. We present decision rules and computing methods for the proposed model by using the risk decision-making principle of classical operational research. Finally, the validity of the approach and the applied process of the proposed model is tested by a numerical example with the background of earthquake emergency material demand forecasting.     

O.R. and Public Expenditure Planning and Control

The problems of public expenditure planning and control to which O.R. can make a contribution are identified. Suggestions are made for research by those in O.R. both within government and in universities. Recent work in the Treasury on financial models and information systems are discussed in terms of how such work might be applied elsewhere and extended to include measures of achievement. The topics covered include planning for uncertainty and theory development by O.R. in models of inflation and social justice.     

Generalised magnetic polarizability tensors

We present a new complete asymptotic expansion for the low‐frequency time‐harmonic magnetic field perturbation caused by the presence of a conducting (permeable) object as its size tends to zero for the eddy current regime of Maxwell's equations. The new asymptotic expansion allows the characterisation of the shape and material properties of such objects by a new class of generalised magnetic polarizability tensors, and we provide an explicit formula for their calculation. Our result will have important implications for metal detectors since it will improve small object discrimination, and for situations where the background field varies over the inclusion, this information will be useable, and indeed useful, in identifying their shape and material properties. Thus, improving the ability of metal detectors to locate landmines and unexploded ordnance, sort metals in recycling processes, and ensure food safety as well as enhancing security screening at airports and public events.     

Conserved Quantities and Symmetries Related to Stochastic Dynamical Systems

The present article focuses on the three topics related to the notions of "conserved quantities" and "symmetries" in stochastic dynamical systems described by stochastic differential equations of Stratonovich type. The first topic is concerned with the relation between conserved quantities and symmetries in stochastic Hamilton dynamical systems, which is established in a way analogous to that in the deterministic Hamilton dynamical theory. In contrast with this, the second topic is devoted to investigate the procedures to derive conserved quantities from symmetries of stochastic dynamical systems without using either the Lagrangian or Hamiltonian structure. The results in these topics indicate that the notion of symmetries is useful for finding conserved quantities in various stochastic dynamical systems. As a further important application of symmetries, the third topic treats the similarity method to stochastic dynamical systems. That is, it is shown that the order of a stochastic system can be reduced, if the system admits symmetries. In each topic, some illustrative examples for stochastic dynamical systems and their conserved quantities and symmetries are given.     

基于双向改进余弦相似度的话题发现算法

话题发现是网络社交平台上进行热点话题预测的一个重要研究问题。针对已有话题发现算法大多基于传统余弦相似度衡量文本数据间的相似性,无法识别各维度取值成比例变化时数据对象间的差异,文本数据相似度计算结果不准确,影响话题发现正确率的问题,提出基于双向改进余弦相似度的话题发现算法(TABOC),首先从方向和取值两个角度改进余弦相似度,提出双向改进余弦相似度,能够区分各维度取值成比例变化的数据对象,保留传统余弦相似度在方向判别上的优势,提高衡量文本相似度的准确性;进一步定义集合的双向改进余弦特征向量和双向改进余弦特征向量的加法等相关定义定理,舍弃无关信息,直接计算新合并集合的特征向量,减小话题发现过程中的时间和空间消耗;还结合增量聚类框架,高效处理新增数据。采用百度贴吧数据进行实验表明,TABOC算法进行话题发现是有效可行的,算法正确率和时间效率总体上优于其他对比算法。     

Forecasting and operational research: a review

From its foundation, operational research (OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scope of OR's interest in forecasting, research from an OR perspective remains vigorous. OR has been more receptive than other disciplines to the specialist research published in the forecasting journals, capitalizing on some of their key findings. In this paper, we identify the particular topics of OR interest over the past 25 years. After a brief summary of the current research in forecasting methods, we examine those topic areas that have grabbed the attention of OR researchers: computationally intensive methods and applications in operations and marketing. Applications in operations have proved particularly important, including the management of inventories and the effects of sharing forecast information across the supply chain. The second area of application is marketing, including customer relationship management using data mining and computer-intensive methods. The paper concludes by arguing that the unique contribution that OR can continue to make to forecasting is through developing models that link the effectiveness of new forecasting methods to the organizational context in which the models will be applied. The benefits of examining the system rather than its separate components are likely to be substantial.     

A cohesive element approach for viscoelastic interface properties

This paper introduces a time dependent extension of the nonlinear traction separation law for an interface element. The constitutive equations of the load history dependent behaviour of the material are depicted and derived according to a generalized Maxwell‐model. This finite linear, viscoelastic approach allows the consideration of long term loading and time dependent material behaviour in thin layers. The implementation of the presented element formulation and the material approach are verified by numerical examples. The paper gives an outlook on further work and research topics. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

基于文本信息的上市中小企业财务困境预测研究

本文通过网络爬虫获取上市中小企业相关的文本信息,包括以年报为代表的信息披露报告和互联网新闻媒体报道的文本内容,采用词袋方法基于不同特征词词表对这些文本内容进行了量化分析,并以财务变量模型为基础对文本信息量化指标在财务困境预测中的作用进行了实证检验,结果表明由信息披露报告构建的管理层语调变量以及由新闻媒体报道构建的报道倾向变量、负面报道比例变量确实可以提高财务困境模型的拟合度和预测能力,而且在对不同类型文本信息的分析应有不同的侧重点。尽管本文针对的是上市中小企业,但并未考虑市场交易信息,因而可以推广到未上市交易的中小企业。