From biomedical literature to knowledge:mining protein-protein interactions

To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.

Transferring knowledge of manufacturing techniques within a subsidiary of a multi-national corporation

With the growth of the multi-national corporation (MNCs) has come the need to understand how parent companies transfer knowledge to, and manage the operations of, their subsidiaries. This is of particular interest to manufacturing companies transferring their operations overseas. Japanese companies in particular have been pioneering in the development of techniques such as Kaizen, and elements of the Toyota Production System (TPS) such as Kanban, which can be useful tools for transferring the ethos of Japanese manufacturing and maintaining quality and control in overseas subsidiaries. Much has been written about the process of transferring Japanese manufacturing techniques but much less is understood about how the subsidiaries themselves – which are required to make use of such techniques – actually acquire and incorporate them into their operations. This research therefore takes the perspective of the subsidiary in examining how knowledge of manufacturing techniques is transferred from the parent company within its surrounding (subsidiary). There is clearly a need to take a practice-based view to understanding how the local managers and operatives incorporate this knowledge into their working practices. A particularly relevant theme is how subsidiaries both replicate and adapt knowledge from parents and the circumstances in which replication or adaptation occurs. However, it is shown that there is a lack of research which takes an in-depth look at these processes from the perspective of the participants themselves. This is particularly important as much knowledge literature argues that knowledge is best viewed as enacted and learned in practice – and therefore transferred in person – rather than by the transfer of abstract and de-contextualised information. What is needed, therefore, is further research which makes an in-depth examination of what happens at the subsidiary level for this transfer process to occur. There is clearly a need to take a practice-based view to understanding how the local managers and operatives incorporate knowledge about manufacturing techniques into their working practices. In depth qualitative research was, therefore, conducted in the subsidiary of a Japanese multinational, Gambatte Corporation, involving three main manufacturing initiatives (or philosophies), namely 'TPS‘, 'TPM‘ and 'TS‘. The case data were derived from 52 in-depth interviews with project members, moderate-participant observations, and documentations and presented and analysed in episodes format. This study contributes to our understanding of knowledge transfer in relation to the approaches and circumstances of adaptation and replication of knowledge within the subsidiary, how the whole process is developed, and also how 'innovation‘ takes place. This study further understood that the process of knowledge transfer could be explained as a process of Reciprocal Provider-Learner Exchange that can be linked to the Experiential Learning Theory.

Networks of learning : how motorsport companies collaborate and share knowledge:evidence from the UK and Italian motorsport industries

The motorsport industry is a high value-added and highly innovative business sector. The UK’s leading racing car manufacturers are world class centres of research, development and engineering. However, individual firms in the sector do not have the range and depth of capabilities to compete independently in motorsport’s dynamic and competitive environment. Industry attention has therefore progressively focused on how networks of collaborating firms can work together to develop new products, improve business processes and reduce costs. This report presents findings from a three year Cardiff Business School study which examined the ways in which firms collaborate as part of wider networks. The research involved gathering data from over 120 firms in the UK and Italian motorsport sectors.

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

An integrated environment for semantic knowledge work

In this demonstration, we will present a semantic environment called the K-Box. The K-Box supports the lightweight integration of knowledge tools, with a focus on semantic tools, but with the flexibility to integrate natural language and conventional tools. We discuss the implementation of the framework, and two existing applications, including details of a new application for developers of semantic workflows. The demonstration will be of interest to developers and researchers of ontology-based knowledge management systems, and semantic desktops, and to analysts working with cross-media information. © 2011 ACM.

Ontology-based knowledge capture and sharing in enterprise organisations

Despite years of effort in building organisational taxonomies, the potential of ontologies to support knowledge management in complex technical domains is under-exploited. The authors of this chapter present an approach to using rich domain ontologies to support sense-making tasks associated with resolving mechanical issues. Using Semantic Web technologies, the authors have built a framework and a suite of tools which support the whole semantic knowledge lifecycle. These are presented by describing the process of issue resolution for a simulated investigation concerning failure of bicycle brakes. Foci of the work have included ensuring that semantic tasks fit in with users’ everyday tasks, to achieve user acceptability and support the flexibility required by communities of practice with differing local sub-domains, tasks, and terminology.

Semantic annotation for knowledge management:requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Form follows function:model-driven engineering for clinical trials

We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge. © 2007 Informa UK Ltd All rights reserved.

Engineering of a novel Saccharomyces cerevisiae wine strain with a respiratory phenotype at high external glucose concentrations

The recently described respiratory strain Saccharomyces cerevisiae KOY.TM6*P is, to our knowledge, the only reported strain of S. cerevisiae which completely redirects the flux of glucose from ethanol fermentation to respiration, even at high external glucose concentrations (27). In the KOY.TM6*P strain, portions of the genes encoding the predominant hexose transporter proteins, Hxt1 and Hxt7, were fused within the regions encoding transmembrane (TM) domain 6. The resulting chimeric gene, TM6*. encoded a chimera composed of the amino-terminal half of Hxt1 and the carboxy-terminal half of Hxt7. It was subsequently integrated into the genome of an hxt null strain. In this study, we have demonstrated the transferability of this respiratory phenotype to the V5 hxt1-7Δ strain, a derivative of a strain used in enology. We also show by using this mutant that it is not necessary to transform a complete hxt null strain with the TM6* construct to obtain a nonethanol-producing phenotype. The resulting V5.TM6*P strain, obtained by transformation of the V5 hxt1-7Δ strain with the TM6* chimeric gene, produced only minor amounts of ethanol when cultured on external glucose concentrations as high as 5%. Despite the fact that glucose flux was reduced to 30% in the V5.TM6*P strain compared with that of its parental strain, the V5.TM6*P strain produced biomass at a specific rate as high as 85% that of the V5 wild-type strain. Even more relevant for the potential use of such a strain for the production of heterologous proteins and also of low-alcohol beverages is the observation that the biomass yield increased 50% with the mutant compared to its parental strain. Copyright © 2005, American Society for Microbiology. All Rights Reserved.

Process re-engineering for effective implementation of projects

Time, cost and quality are the prime objectives of any project. Unfortunately, today’s project management does not always ensure the realisation of these objectives. The main reasons of project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation, under-estimation and mis-estimation. An overall organisational approach with the application of appropriate management philosophies, tools and techniques can only solve the problem. The present study establishes a methodology for achieving success in implementing projects using a business process re-engineering (BPR) framework. Internal performance characteristics are introspected through condition diagnosis that identifies and prioritises areas of concern requiring attention. Process re-engineering emerges as a most critical area for immediate attention. Project process re-engineering is carried out by eliminating non-value added activities, taking up activities concurrently by applying information systems rigorously and applying risk management techniques throughout the project life cycle. The overall methodology is demonstrated through applications to cross country petroleum pipeline project organisation in an Indian scenario.

The handbook of engineering self-aware and self-expressive systems

When faced with the task of designing and implementing a new self-aware and self-expressive computing system, researchers and practitioners need a set of guidelines on how to use the concepts and foundations developed in the Engineering Proprioception in Computing Systems (EPiCS) project. This report provides such guidelines on how to design self-aware and self-expressive computing systems in a principled way. We have documented different categories of self-awareness and self-expression level using architectural patterns. We have also documented common architectural primitives, their possible candidate techniques and attributes for architecting self-aware and self-expressive systems. Drawing on the knowledge obtained from the previous investigations, we proposed a pattern driven methodology for engineering self-aware and self-expressive systems to assist in utilising the patterns and primitives during design. The methodology contains detailed guidance to make decisions with respect to the possible design alternatives, providing a systematic way to build self-aware and self-expressive systems. Then, we qualitatively and quantitatively evaluated the methodology using two case studies. The results reveal that our pattern driven methodology covers the main aspects of engineering self-aware and self-expressive systems, and that the resulted systems perform significantly better than the non-self-aware systems.

Systemological Knowledge-based Technology for Solving Complete Ill-structured Problems

Original method and technology of systemological «Unit-Function-Object» analysis for solving complete ill-structured problems is proposed. The given visual grapho-analytical UFO technology for the fist time combines capabilities and advantages of the system and object approaches and can be used for business reengineering and for information systems design. UFO- technology procedures are formalized by pattern-theory methods and developed by embedding systemological conceptual classification models into the system-object analysis and software tools. Technology is based on natural classification and helps to investigate deep semantic regularities of subject domain and to take proper account of system-classes essential properties the most objectively. Systemological knowledge models are based on method which for the first time synthesizes system and classification analysis. It allows creating CASE-toolkit of a new generation for organizational modelling for companies’ sustainable development and competitive advantages providing.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.