Intermediate pyrolysis studies of aquatic biomass and potential applications in the BtVB-process

Aquatic biomass is seen as one of the major feedstocks to overcome difficulties associated with 1st generation biofuels, such as competition with food production, change of land use and further environmental issues. Although, this finding is widely accepted only little work has been carried out to investigate thermo-chemical conversion of algal specimen to produce biofuels, power and heat. This work aims at contributing fundamental knowledge for thermo-chemical processing of aquatic biomass via intermediate pyrolysis. Therefore, it was necessary to install and commission an analytical pyrolysis apparatus which facilitates intermediate pyrolysis process conditions as well as subsequent separation and detection of pyrolysates (Py- GC/MS). In addition, a methodology was established to analyse aquatic biomass under intermediate conditions by Thermo-Gravimetric Analysis (TGA). Several microalgae (e.g. Chlamydomonas reinhardtii, Chlorella vulgaris) and macroalgae specimen (e.g. Fucus vesiculosus) from main algal divisions and various natural habitats (fresh and saline water, temperate and polar climates) were chosen and their thermal degradation under intermediate pyrolysis conditions was studied. In addition, it was of interest to examine the contribution of biochemical constituents of algal biomass onto the chemical compounds contained in pyrolysates. Therefore, lipid and protein fractions were extracted from microalgae biomass and analysed separately. Furthermore, investigations of residual algal materials obtained by extraction of high valuable compounds (e.g. lipids, proteins, enzymes) were included to evaluate their potential for intermediate pyrolysis processing. On basis of these thermal degradation studies, possible applications of algal biomass and from there derived materials in the Bio-thermal Valorisation of Biomass-process (BtVB-process) are presented. It was of interest to evaluate the combination of the production of high valuable products and bioenergy generation derived by micro- and macro algal biomass.

A comprehensive solution to procedural knowledge acquisition using information extraction

Procedural knowledge is the knowledge required to perform certain tasks. It forms an important part of expertise, and is crucial for learning new tasks. This paper summarises existing work on procedural knowledge acquisition, and identifies two major challenges that remain to be solved in this field; namely, automating the acquisition process to tackle bottleneck in the formalization of procedural knowledge, and enabling machine understanding and manipulation of procedural knowledge. It is believed that recent advances in information extraction techniques can be applied compose a comprehensive solution to address these challenges. We identify specific tasks required to achieve the goal, and present detailed analyses of new research challenges and opportunities. It is expected that these analyses will interest researchers of various knowledge management tasks, particularly knowledge acquisition and capture.

Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing

Procedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable instructions have been useful learning resources for human, they are not interpretable by machines. Automatically acquiring procedural knowledge in machine interpretable formats from instructions has become an increasingly popular research topic due to their potential applications in process automation. However, it has been insufficiently addressed. This paper presents an approach and an implemented system to assist users to automatically acquire procedural knowledge in structured forms from instructions. We introduce a generic semantic representation of procedures for analysing instructions, using which natural language techniques are applied to automatically extract structured procedures from instructions. The method is evaluated in three domains to justify the generality of the proposed semantic representation as well as the effectiveness of the implemented automatic system.

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.

KnoFuss:a comprehensive architecture for knowledge fusion

We propose a knowledge fusion architecture KnoFuss based on the application of problem-solving methods technology, which allows methods for subtasks of the fusion process to be combined and the best methods to be selected, depending on the domain and task at hand.

Supply chain knowledge management:a literature review

This paper aims to contribute to the debate on the role of knowledge management in supply chain management by reviewing the published literature. A total of 58 selected referred journal articles were systematically analyzed. This review identifies various theoretical and methodological characteristics of the way in which knowledge management applications are proposed in the supply chain context. The review shows that little evidence exists of the positive relation between the use of IT solutions and firms’ performance. Some issues remain unexplored such as the problem of knowledge obsolescence in supply chain management. A deeper understanding of the knowledge accumulation process could give new insights. The paper concludes with some future directions for theory construction and empirical research.

Before and after modelling:risk knowledge management is required

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

Knowledge elicitation supported by simulation

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself.

Transferring knowledge of manufacturing techniques in multinational corporations:preliminary findings

With the growth of the multinational corporation (MNC) 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 this regard, with techniques such as the Toyota Production System (TPS) for transferring the ethos of Japanese manufacturing and maintaining quality and control in overseas subsidiaries. A great deal 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. The research on which this paper is based therefore examines how, from the perspective of the subsidiary, knowledge of manufacturing techniques is transferred from the parent company. 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, Denso 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. The aim of this paper is to present the preliminary findings from the case analyses. The research contributes to our understanding of knowledge transfer in relation to the circumstances of the selection between adaptation and replication of knowledge in the subsidiary from its parent. In particular this understanding relates to transfer across different flows and levels in the organisational hierarchy, how the whole process is managed, and also how modification takes place.

An analysis of the role of soft systems methodology in the change process and the contribution of the facilitator within this process

This research aims to examine the effectiveness of Soft Systems Methodology (SSM) to enable systemic change within local goverment and local NHS environments and to examine the role of the facilitator within this process. Checkland's Mode 2 variant of Soft Systems Methodology was applied on an experimental basis in two environments, Herefordshire Health Authority and Sand well Health Authority. The Herefordshire application used SSM in the design of an Integrated Care Pathway for stroke patients. In Sandwell, SSM was deployed to assist in the design of an Infonnation Management and Technology (IM&T) Strategy for the boundary-spanning Sandwell Partnership. Both of these environments were experiencing significant organisational change as the experiments unfurled. The explicit objectives of the research were: To examine the evolution and development of SSM and to contribute to its further development. To apply the Soft Systems Methodology to change processes within the NHS. To evaluate the potential role of SSM in this wider process of change. To assess the role of the researcher as a facilitator within this process. To develop a critical framework through which the impact of SSM on change might be understood and assessed. In developing these objectives, it became apparent that there was a gap in knowledge relating to SSM. This gap concerns the evaluation of the role of the approach in the change process. The case studies highlighted issues in stakeholder selection and management; the communicative assumptions in SSM; the ambiguous role of the facilitator; and the impact of highly politicised problem environments on the effectiveness of the methodology in the process of change. An augmented variant on SSM that integrates an appropriate (social constructivist) evaluation method is outlined, together with a series of hypotheses about the operationalisation of this proposed method.

Knowledge management in support of enterprise risk management

Risk management and knowledge management have so far been studied almost independently. The evolution of risk management to the holistic view of Enterprise Risk Management requires the destruction of barriers between organizational silos and the exchange and application of knowledge from different risk management areas. However, knowledge management has received little or no attention in risk management. This paper examines possible relationships between knowledge management constructs related to knowledge sharing, and two risk management concepts: perceived quality of risk control and perceived value of enterprise risk management. From a literature review, relationships with eight knowledge management variables covering people, process and technology aspects were hypothesised. A survey was administered to risk management employees in financial institutions. The results showed that the perceived quality of risk control is significantly associated with four knowledge management variables: perceived quality of risk knowledge sharing, perceived quality of communication among people, web channel functionality, and risk management information system functionality. However, the relationships of the knowledge management variables to the perceived value of enterprise risk management are not significant. We conclude that better knowledge management is associated with better risk control, but that more effort needs to be made to break down organizational silos in order to support true Enterprise Risk Management.

Knowledge management for more sustainable water systems

The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included.

An empirical examination of the strategic decision-making process:the relationship between context, process, and outcomes

Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.

Managing project risk using combined analytic hierarchy process and risk map

The main purpose of the study is to develop an integrated framework for managing project risks by analyzing risk across project, work package and activity levels, and developing responses. Design/methodology/approach: The study first reviews the literature of various contemporary risk management frameworks in order to identify gaps in project risk management knowledge. Then it develops a conceptual risk management framework using combined analytic hierarchy process (AHP) and risk map for managing project risks. The proposed framework has then been applied to a 1500 km oil pipeline construction project in India in order to demonstrate its effectiveness. The concerned project stakeholders were involved through focus group discussions for applying the proposed risk management framework in the project under study. Findings: The combined AHP and risk map approach is very effective to manage project risks across project, work package and activity levels. The risk factors in project level are caused because of external forces such as business environment (e.g. customers, competitors, technological development, politics, socioeconomic environment). The risk factors in work package and activity levels are operational in nature and created due to internal causes such as lack of material and labor productivity, implementation issues, team ineffectiveness, etc. Practical implications: The suggested model can be applied to any complex project and helps manage risk throughout the project life cycle. Originality/value: Both business and operational risks constitute project risks. In one hand, the conventional project risk management frameworks emphasize on managing business risks and often ignore operational risks. On the other hand, the studies that deal with operational risk often do not link them with business risks. However, they need to be addressed in an integrated way as there are a few risks that affect only the specific level. Hence, this study bridges the gaps. © 2010 Elsevier B.V. All rights reserved.

Representing the assessment process for psychodynamic psychotherapy within a computerized model of human classification

This research describes a computerized model of human classification which has been constructed to represent the process by which assessments are made for psychodynamic psychotherapy. The model assigns membership grades (MGs) to clients so that the most suitable ones have high values in the therapy category. Categories consist of a hierarchy of components, one of which, ego strength, is analysed in detail to demonstrate the way it has captured the psychotherapist's knowledge. The bottom of the hierarchy represents the measurable factors being assessed during an interview. A questionnaire was created to gather the identified information and was completed by the psychotherapist after each assessment. The results were fed into the computerized model, demonstrating a high correlation between the model MGs and the suitability ratings of the psychotherapist (r = .825 for 24 clients). The model has successfully identified the relevant data involved in assessment and simulated the decision-making process of the expert. Its cognitive validity enables decisions to be explained, which means that it has potential for therapist training and also for enhancing the referral process, with benefits in cost effectiveness as well as in the reduction of trauma to clients. An adapted version measuring client improvement would give quantitative evidence for the benefit of therapy, thereby supporting auditing and accountability. © 1997 The British Psychological Society.