The learning dynamics of a universal approximator

The learning properties of a universal approximator, a normalized committee machine with adjustable biases, are studied for on-line back-propagation learning. Within a statistical mechanics framework, numerical studies show that this model has features which do not exist in previously studied two-layer network models without adjustable biases, e.g., attractive suboptimal symmetric phases even for realizable cases and noiseless data.

Instantiating deformable models with a neural net

Deformable models are an attractive approach to recognizing objects which have considerable within-class variability such as handwritten characters. However, there are severe search problems associated with fitting the models to data which could be reduced if a better starting point for the search were available. We show that by training a neural network to predict how a deformable model should be instantiated from an input image, such improved starting points can be obtained. This method has been implemented for a system that recognizes handwritten digits using deformable models, and the results show that the search time can be significantly reduced without compromising recognition performance. © 1997 Academic Press.

Combining the wavelet transform and forecasting models to predict gas forward prices

This paper presents a forecasting technique for forward energy prices, one day ahead. This technique combines a wavelet transform and forecasting models such as multi- layer perceptron, linear regression or GARCH. These techniques are applied to real data from the UK gas markets to evaluate their performance. The results show that the forecasting accuracy is improved significantly by using the wavelet transform. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

Editorial

This special issue of the Journal of the Operational Research Society is dedicated to papers on the related subjects of knowledge management and intellectual capital. These subjects continue to generate considerable interest amongst both practitioners and academics. This issue demonstrates that operational researchers have many contributions to offer to the area, especially by bringing multi-disciplinary, integrated and holistic perspectives. The papers included are both theoretical as well as practical, and include a number of case studies showing how knowledge management has been implemented in practice that may assist other organisations in their search for a better means of managing what is now recognised as a core organisational activity. It has been accepted by a growing number of organisations that the precise handling of information and knowledge is a significant factor in facilitating their success but that there is a challenge in how to implement a strategy and processes for this handling. It is here, in the particular area of knowledge process handling that we can see the contributions of operational researchers most clearly as is illustrated in the papers included in this journal edition. The issue comprises nine papers, contributed by authors based in eight different countries on five continents. Lind and Seigerroth describe an approach that they call team-based reconstruction, intended to help articulate knowledge in a particular organisational. context. They illustrate the use of this approach with three case studies, two in manufacturing and one in public sector health care. Different ways of carrying out reconstruction are analysed, and the benefits of team-based reconstruction are established. Edwards and Kidd, and Connell, Powell and Klein both concentrate on knowledge transfer. Edwards and Kidd discuss the issues involved in transferring knowledge across frontières (borders) of various kinds, from those borders within organisations to those between countries. They present two examples, one in distribution and the other in manufacturing. They conclude that trust and culture both play an important part in facilitating such transfers, that IT should be kept in a supporting role in knowledge management projects, and that a staged approach to this IT support may be the most effective. Connell, Powell and Klein consider the oft-quoted distinction between explicit and tacit knowledge, and argue that such a distinction is sometimes unhelpful. They suggest that knowledge should rather be regarded as a holistic systemic property. The consequences of this for knowledge transfer are examined, with a particular emphasis on what this might mean for the practice of OR Their view of OR in the context of knowledge management very much echoes Lind and Seigerroth's focus on knowledge for human action. This is an interesting convergence of views given that, broadly speaking, one set of authors comes from within the OR community, and the other from outside it. Hafeez and Abdelmeguid present the nearest to a 'hard' OR contribution of the papers in this special issue. In their paper they construct and use system dynamics models to investigate alternative ways in which an organisation might close a knowledge gap or skills gap. The methods they use have the potential to be generalised to any other quantifiable aspects of intellectual capital. The contribution by Revilla, Sarkis and Modrego is also at the 'hard' end of the spectrum. They evaluate the performance of public–private research collaborations in Spain, using an approach based on data envelopment analysis. They found that larger organisations tended to perform relatively better than smaller ones, even though the approach used takes into account scale effects. Perhaps more interesting was that many factors that might have been thought relevant, such as the organisation's existing knowledge base or how widely applicable the results of the project would be, had no significant effect on the performance. It may be that how well the partnership between the collaborators works (not a factor it was possible to take into account in this study) is more important than most other factors. Mak and Ramaprasad introduce the concept of a knowledge supply network. This builds on existing ideas of supply chain management, but also integrates the design chain and the marketing chain, to address all the intellectual property connected with the network as a whole. The authors regard the knowledge supply network as the natural focus for considering knowledge management issues. They propose seven criteria for evaluating knowledge supply network architecture, and illustrate their argument with an example from the electronics industry—integrated circuit design and fabrication. In the paper by Hasan and Crawford, their interest lies in the holistic approach to knowledge management. They demonstrate their argument—that there is no simple IT solution for organisational knowledge management efforts—through two case study investigations. These case studies, in Australian universities, are investigated through cultural historical activity theory, which focuses the study on the activities that are carried out by people in support of their interpretations of their role, the opportunities available and the organisation's purpose. Human activities, it is argued, are mediated by the available tools, including IT and IS and in this particular context, KMS. It is this argument that places the available technology into the knowledge activity process and permits the future design of KMS to be improved through the lessons learnt by studying these knowledge activity systems in practice. Wijnhoven concentrates on knowledge management at the operational level of the organisation. He is concerned with studying the transformation of certain inputs to outputs—the operations function—and the consequent realisation of organisational goals via the management of these operations. He argues that the inputs and outputs of this process in the context of knowledge management are different types of knowledge and names the operation method the knowledge logistics. The method of transformation he calls learning. This theoretical paper discusses the operational management of four types of knowledge objects—explicit understanding; information; skills; and norms and values; and shows how through the proposed framework learning can transfer these objects to clients in a logistical process without a major transformation in content. Millie Kwan continues this theme with a paper about process-oriented knowledge management. In her case study she discusses an implementation of knowledge management where the knowledge is centred around an organisational process and the mission, rationale and objectives of the process define the scope of the project. In her case they are concerned with the effective use of real estate (property and buildings) within a Fortune 100 company. In order to manage the knowledge about this property and the process by which the best 'deal' for internal customers and the overall company was reached, a KMS was devised. She argues that process knowledge is a source of core competence and thus needs to be strategically managed. Finally, you may also wish to read a related paper originally submitted for this Special Issue, 'Customer knowledge management' by Garcia-Murillo and Annabi, which was published in the August 2002 issue of the Journal of the Operational Research Society, 53(8), 875–884.

Modeling geometric rules in object based models:an XML / GML approach

Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

Ethnic diversity as a multilevel construct:the combined effects of dissimilarity, group diversity, and societal status on learning performance in work groups

The authors present a model of the multilevel effects of diversity on individual learning performance in work groups. For ethnically diverse work groups, the model predicts that group diversity elicits either positive or negative effects on individual learning performance, depending on whether a focal individual’s ethnic dissimilarity from other group members is high or low. By further considering the societal status of an individual’s ethnic origin within society (Anglo versus non-Anglo for our U.K. context), the authors hypothesize that the model’s predictions hold more strongly for non-Anglo group members than for Anglo group members. We test this model with data from 412 individuals working on a 24-week business simulation in 87 four- to seven-person groups with varying degrees of ethnic diversity. Two of the three hypotheses derived from the model received full support and one hypothesis received partial support. Implications for theory development, methods, and practice in applied group diversity research are discussed.

Automatic refinement of constructive solid geometry models

Geometric information relating to most engineering products is available in the form of orthographic drawings or 2D data files. For many recent computer based applications, such as Computer Integrated Manufacturing (CIM), these data are required in the form of a sophisticated model based on Constructive Solid Geometry (CSG) concepts. A recent novel technique in this area transfers 2D engineering drawings directly into a 3D solid model called `the first approximation'. In many cases, however, this does not represent the real object. In this thesis, a new method is proposed and developed to enhance this model. This method uses the notion of expanding an object in terms of other solid objects, which are either primitive or first approximation models. To achieve this goal, in addition to the prepared subroutine to calculate the first approximation model of input data, two other wireframe models are found for extraction of sub-objects. One is the wireframe representation on input, and the other is the wireframe of the first approximation model. A new fast method is developed for the latter special case wireframe, which is named the `first approximation wireframe model'. This method avoids the use of a solid modeller. Detailed descriptions of algorithms and implementation procedures are given. In these techniques utilisation of dashed line information is also considered in improving the model. Different practical examples are given to illustrate the functioning of the program. Finally, a recursive method is employed to automatically modify the output model towards the real object. Some suggestions for further work are made to increase the domain of objects covered, and provide a commercially usable package. It is concluded that the current method promises the production of accurate models for a large class of objects.

Computer interpretation of engineering drawings as solid models

Much of the geometrical data relating to engineering components and assemblies is stored in the form of orthographic views, either on paper or computer files. For various engineering applications, however, it is necessary to describe objects in formal geometric modelling terms. The work reported in this thesis is concerned with the development and implementation of concepts and algorithms for the automatic interpretation of orthographic views as solid models. The various rules and conventions associated with engineering drawings are reviewed and several geometric modelling representations are briefly examined. A review of existing techniques for the automatic, and semi-automatic, interpretation of engineering drawings as solid models is given. A new theoretical approach is then presented and discussed. The author shows how the implementation of such an approach for uniform thickness objects may be extended to more general objects by introducing the concept of `approximation models'. Means by which the quality of the transformations is monitored, are also described. Detailed descriptions of the interpretation algorithms and the software package that were developed for this project are given. The process is then illustrated by a number of practical examples. Finally, the thesis concludes that, using the techniques developed, a substantial percentage of drawings of engineering components could be converted into geometric models with a specific degree of accuracy. This degree is indicative of the suitability of the model for a particular application. Further work on important details is required before a commercially acceptable package is produced.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

Consumer responses to really new products: examining the impacts of learning strategies and presentation formats on product comprehension and attitude formation

Mental simulations and analogies have been identified as powerful learning tools for RNPs. Furthermore, visuals in advertising have recently been conceptualized as meaningful sources of information as opposed to peripheral cues and thus may help consumers learn about RNPs. The study of visual attention may also contribute to understanding the links between conceptual and perceptual analyses when learning for a RNP. Two conceptual models are developed. the first model consists of causal relationships between the attributes of advertising stimuli for RNPs and consumer responses, as well as mediating influences. The second model focuses on the role of visual attention in product comprehension as a response to advertising stimuli. Two experiments are conducted: a Web-Experiment and an eye-tracking experiment. The first experiment (858 subjects) examines the effect of learning strategies (mental simulation vs. analogy vs. no analogy/no mental simulation) and presentation formats (words vs. pictures) on individual responses. The mediating role of emotions is assessed. The second experiment investigates the effect of learning strategies and presentation formats on product comprehension, along with the role of attention (17 subjects). The findings from experiment 1 indicate that learning strategies and presentation formats can either enhance or undermine the effect of advertising stimuli on individual responses. Moreover, the nature of the product (i.e. hedonic vs. utilitarian vs. hybrid) should be considered when designing communications for RNPs. The mediating role of emotions is verified. Experiment 2 suggests that an increase in attention to the message may either reflect enhanced comprehension or confusion.

Content-based VLE designs improve learning efficiency in constructivist statistics education

Background: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design. © 2011 Wessa et al.

A comparative study of bayesian models for unsupervised sentiment detection

This paper presents a comparative study of three closely related Bayesian models for unsupervised document level sentiment classification, namely, the latent sentiment model (LSM), the joint sentiment-topic (JST) model, and the Reverse-JST model. Extensive experiments have been conducted on two corpora, the movie review dataset and the multi-domain sentiment dataset. It has been found that while all the three models achieve either better or comparable performance on these two corpora when compared to the existing unsupervised sentiment classification approaches, both JST and Reverse-JST are able to extract sentiment-oriented topics. In addition, Reverse-JST always performs worse than JST suggesting that the JST model is more appropriate for joint sentiment topic detection.

New career models in UK professional service firms:from up-or-out to up-and-going-nowhere?

In this paper, we empirically examine how professional service firms are adapting their promotion and career models to new market and institutional pressures, without losing the benefits of the traditional up-or-out tournament. Based on an in-depth qualitative study of 10 large UK based law firms we find that most of these firms do not have a formal up-or-out policy but that the up-or-out rule operates in practice. We also find that most firms have introduced alternative roles and a novel career policy that offers a holistic learning and development deal to associates without any expectation that unsuccessful candidates for promotion to partner should quit the firm. While this policy and the new roles formally contradict the principle of up-or-out by creating permanent non-partner positions, in practice they coexist. We conclude that the motivational power of the up-or-out tournament remains intact, notwithstanding the changes to the internal labour market structure of these professional service firms.

Experiential learning:inspiring the business leaders of tomorrow

Purpose: The complex challenges of sustainable development and the need to embed these issues effectively into the education of future business leaders has never been more urgent. The purpose of this paper is to discuss different approaches taken by two UK signatories to the UN Principles for Responsible Management Education (PRME). Design/methodology/approach: The two approaches examined are: MSc Entrepreneurship students opting for placements with social enterprises; and MBA students undertaking workshops using "live" case studies. A content analysis of the experiences of students from their written reflective narratives is presented. This is supplemented by reflections of the facilitators and tutors. Findings: The analysis reveals that the opportunity to work with social entrepreneurs and/or "responsible" business professionals provides the business students with inspirational role models and positive social learning opportunities. Research limitations/implications: This paper suggests that experiential learning is an effective way of integrating ethics, responsibility and sustainability into the curriculum but the research draws on the experience of two schools. Further research is important to explore these findings in other contexts. Practical implications: The authors argue that direct exposure to a business culture (and/or behaviour) that is predicated upon ethical/social responsibility and sustainability is an effective means to embed these values in the curriculum. Originality/value: This paper contributes by drawing on social psychological research related to behaviour change to examine how experiential learning on traditional Business Masters programmes can provide students with the knowledge, motivation and skills to contribute positively to society, in a way that more traditional pedagogies cannot. © Emerald Group Publishing Limited.