Semantic Web Technologies in Support of Service Oriented Architecture Governance

As Service Oriented Architecture (SOA) deployments gradually mature they also grow in size and complexity. The number of service providers, services, and service consumers increases, and so do the dependencies among these entities and the various artefacts that describe how services operate, or how they are meant to operate under specific conditions. Appropriate governance over the various phases and activities associated with the service lifecycle is therefore indispensable in order to prevent a SOA deployment from dissolving into an unmanageable infrastructure. The employment of Semantic Web technologies for describing and reasoning about service properties and governance requirements has the potential to greatly enhance the effectiveness and efficiency of SOA Governance solutions by increasing the levels of automation in a wide-range of tasks relating to service lifecycle management. The goal of the proposed research work is to investigate the application of Semantic Web technologies in the context of service lifecycle management, and propose a concrete theoretical and technological approach for supporting SOA Governance through the realisation of semantically-enhanced registry and repository solutions

Organic Farming in Europe by 2010: Scenarios for the future

How will organic farming in Europe evolve by the year 2010? The answer provides a basis for the development of different policy options and for anticipating the future relative competitiveness of organic and conventional farming. The authors tackle the question using an innovative approach based on scenario analysis, offering the reader a range of scenarios that encompass the main possible evolutions of the organic farming sector. This book constitutes an innovative and reliable decision-supporting tool for policy makers, farmers and the private sector. Researchers and students operating in the field of agricultural economics will also benefit from the methodological approach adopted for the scenario analysis

Multi-agent knowledge integration mechanism using particle swarm optimization

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

Fuzzy Transfer Pricing World: On the Analysis of Transfer Pricing with Fuzzy Logic Techniques

The arm’s length analysis of international transfer prices of multinational firms lacks sound methodological approach of the so-called function and risk analysis. In practice, such analyses are descriptive. Derived from Zadeh’s mathematical theory of fuzzy sets, this paper investigates a quantitative approach to identify the function and risk pattern of related parties of multinational companies. We illustrate our fuzzy logic approach with a simple case.

Practitioner Perceptions of the A3 Method for Process Improvement in Health Care

The focus of this article is to present students’ perceptions of the recently developed A3 method, a structured problem-solving approach based on lean concepts and tools that have been adapted to the health care environment. The students were all employees of a large health care provider and were enrolled in a customized health care executive MBA Program. Each student was required to complete an individual A3 Project in order to improve a process at the department for which they worked. At the end of the semester the students presented their A3 projects to their peers who voted on the best projects. A survey measuring perceptions of the A3 method for problem solving in health care was administered and from it we present propositions for A3 implementation. These propositions are applicable both to health care practitioners and to academic researchers

Fuzzy Dynamic Discrimination Algorithms for Distributed Knowledge Management Systems

A reduction of the algorithmic complexity of the fuzzy inference engine has the following property: the inputs (the fuzzy rules and the fuzzy facts) can be divided in two parts, one being relatively constant for a long a time (the fuzzy rule or the knowledge model) when it is compared to the second part (the fuzzy facts) for every inference cycle. The occurrence of certain transformations over the constant part makes sense, in order to decrease the solution procurement time, in the case that the second part varies, but it is known at certain moments in time. The transformations attained in advance are called pre-processing or knowledge compilation. The use of variables in a Business Rule Management System knowledge representation allows factorising knowledge, like in classical knowledge based systems. The language of the first-degree predicates facilitates the formulation of complex knowledge in a rigorous way, imposing appropriate reasoning techniques. It is, thus, necessary to define the description method of fuzzy knowledge, to justify the knowledge exploiting efficiency when the compiling technique is used, to present the inference engine and highlight the functional features of the pattern matching and the state space processes. This paper presents the main results of our project PR356 for designing a compiler for fuzzy knowledge, like Rete compiler, that comprises two main components: a static fuzzy discrimination structure (Fuzzy Unification Tree) and the Fuzzy Variables Linking Network. There are also presented the features of the elementary pattern matching process that is based on the compiled structure of fuzzy knowledge. We developed fuzzy discrimination algorithms for Distributed Knowledge Management Systems (DKMSs). The implementations have been elaborated in a prototype system FRCOM (Fuzzy Rule COMpiler).Fuzzy Unification Tree, Dynamic Discrimination of Fuzzy Sets, DKMS, FRCOM

Technological Evolution and the Devolution of Corporate Financial Reporting

My claim is that the technology link to the recent disclosure scandals is no coincidence. To be sure, cheating tempts all who seek wealth, in whatever line of business they find themselves. I want to show, however, how the rapid pace of innovation at a number of levels offered motive, opportunity, and rationalization for a downshift in financial reporting norms, which in turn made outright fraud more probable

Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving

To take into account the experience feedback on solving complex problems in business is deemed as a way to improve the quality of products and processes. Only a few academic works, however, are concerned with the representation and the instrumentation of experience feedback systems. We propose, in this paper, a model of experiences and mechanisms to use these experiences. More specifically, we wish to encourage the reuse of already performed expert analysis to propose a priori analysis in the solving of a new problem. The proposal is based on a representation in the context of the experience of using a conceptual marker and an explicit representation of the analysis incorporating expert opinions and the fusion of these opinions. The experience feedback models and inference mechanisms are integrated in a commercial support tool for problem solving methodologies. The results obtained to this point have already led to the definition of the role of ‘‘Rex Manager’’ with principles of sustainable management for continuous improvement of industrial processes in companies

Knowledge Management in E-Learning Systems

Current knowledge management systems focus on knowledge acquisition, storage, retrieval and maintenance. Yet, for that knowledge to be operational, to become knowledge rather than information, requires internalization and learning. E- learning systems and courseware, on the other hand, are all too often monolithic and inert and fail to facilitate the development and sharing of knowledge. In this paper we discuss some aspects about knowledge providing and present our research in this field through an e-learning system for major risks management.Knowledge, management, e-learning, information, data, simulation, case study