Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

Adaptive modelling, estimation and fusion from data: a neurofuzzy approach

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input. This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

Rotulagem como mecanismo de compartilhamento de informações com agentes da cadeia produtiva do café

The Agroindustrial System coffee after decades of state regulation has become a decentralized economic activity. This situation compelled most of the actors in the production chain to resort to self r egulatory systems offered by certification agencies, which have specific criteria and procedures. However the diversity criteria of the agencies do not offer resources able to ensure efficient management of the governance structure. There is a need to reduce the asymmetry of information, which is possible through the sharing of data compatible with the production tracking feature. This work is supported in this contextualized problem, based on Transaction Cost Theory and the use of qualitative and quantitative research methodologies. The first part of the work seeks to know the procedures required by leading regulatory agencies in Brazil, with perspective to emphasize the similarities and compatibilities between them, which was reached after analysis of standards and comparison of similarities. Next is registered the operation and the coffee traceability of the structure, in order to identify, through observation, documental and bibliographical analysis, the systems in place and traceable information in line with the recommendations of the coffee certification. Finally, he sought to create a labeling model that allows to generate and share information about the product from the field to the sale for consumption. The information obtained in the previous steps were the basis for data collection with the production chain agents through a structured questionnaire administered to 618 agents of the production chain, whose answers were treated by multivariate methods of statistical analysis. The results showed that actors in the chain are in favor of inclusion and sharing information related to rural production and economic and environmental data. This knowledge enabled develop a labeling model where the information sharing agents is an efficient mechanism to mitigate the governance problems identified.

Information integration and management through the design and construction phases of a project life cycle

Information management is a key aspect of successful construction projects. Having inaccurate measurements and conflicting data can lead to costly mistakes, and vague quantities can ruin estimates and schedules. Building information modeling (BIM) augments a 3D model with a wide variety of information, which reduces many sources of error and can detect conflicts before they occur. Because new technology is often more complex, it can be difficult to effectively integrate it with existing business practices. In this paper, we will answer two questions: How can BIM add value to construction projects? and What lessons can be learned from other companies that use BIM or other similar technology? Previous research focused on the technology as if it were simply a tool, observing problems that occurred while integrating new technology into existing practices. Our research instead looks at the flow of information through a company and its network, seeing all the actors as part of an ecosystem. Building upon this idea, we proposed the metaphor of an information supply chain to illustrate how BIM can add value to a construction project. This paper then concludes with two case studies. The first case study illustrates a failure in the flow of information that could have prevented by using BIM. The second case study profiles a leading design firm that has used BIM products for many years and shows the real benefits of using this program.

ASSESSING INFORMATION CONFLICTS DURING THE PROJECT LIFE CYCLE

The objective of this research is to investigate the consequences of sharing or using information generated in one phase of the project to subsequent life cycle phases. Sometimes the assumptions supporting the information change, and at other times the context within which the information was created changes in a way that causes the information to become invalid. Often these inconsistencies are not discovered till the damage has occurred. This study builds on previous research that proposed a framework based on the metaphor of ‘ecosystems’ to model such inconsistencies in the 'supply chain' of life cycle information (Brokaw and Mukherjee, 2012). The outcome of such inconsistencies often results in litigation. Therefore, this paper studies a set of legal cases that resulted from inconsistencies in life cycle information, within the ecosystems framework. For each project, the errant information type, creator and user of the information and their relationship, time of creation and usage of the information in the life cycle of the project are investigated to assess the causes of failure of precise and accurate information flow as well as the impact of such failures in later stages of the project. The analysis shows that the misleading information is mostly due to lack of collaboration. Besides, in all the studied cases, lack of compliance checking, imprecise data and insufficient clarifications hinder accurate and smooth flow of information. The paper presents findings regarding the bottleneck of the information flow process during the design, construction and post construction phases. It also highlights the role of collaboration as well as information integration and management during the project life cycle and presents a baseline for improvement in information supply chain through the life cycle of the project.

Impact of educational posters on the lay knowledge of school teachers regarding emergency management of dental injuries

The purpose of this study was to investigate the knowledge of school teachers about the emergency management of dental trauma, after an educational poster campaign. A total of 1000 questionnaires were sent to 100 schools in the area where the poster had been distributed. This was compared to another 100 schools (1000 questionnaires) in an area, Where the poster had not been distributed. The questionnaire surveyed demographic data, basic knowledge of emergency management of tooth fracture, luxation and avulsion injuries. A total of 511 questionnaires were returned (25.5%) and analyzed. Results showed differences between the two assessed areas. Teachers, who worked in the area with poster distribution, had better knowledge in handling tooth injuries. For the management of tooth fractures the portion of teachers, who knew the correct handling procedure, was 78.9% (area with poster campaign) vs 72.1% (area with no poster campaign), for the management of tooth luxation it was 87% vs 84% and for the management of tooth avulsion it was 71% vs 54%. In the area with the poster campaign 49% (n = 90 out of 185) of the teachers stated to have gained some knowledge about this topic beforehand. Out of these, 75 teachers (75/90 = 83%), had gained their information from the educational poster. Out of the 75 teachers, who had seen a poster on this topic, 68 (68/75 = 91%) would have managed such an emergency correctly. The present study shows the positive effect of educational poster campaigns. It therefore should encourage professionals in this field to embark on similar projects.

A personal data framework for exchanging knowledge about users in new financial services

Personal data is a key asset for many companies, since this is the essence in providing personalized services. Not all companies, and specifically new entrants to the markets, have the opportunity to access the data they need to run their business. In this paper, we describe a comprehensive personal data framework that allows service providers to share and exchange personal data and knowledge about users, while facilitating users to decide who can access which data and why. We analyze the challenges related to personal data collection, integration, retrieval, and identity and privacy management, and present the framework architecture that addresses them. We also include the validation of the framework in a banking scenario, where social and financial data is collected and properly combined to generate new socio-economic knowledge about users that is then used by a personal lending service.

Knowledge-based systems /

"UILU-ENG 80 1704."

Knowledge management systems:finding a way with technology

Purpose - To consider the role of technology in knowledge management in organizations, both actual and desired. Design/methodology/approach - Facilitated, computer-supported group workshops were conducted with 78 people from ten different organizations. The objective of each workshop was to review the current state of knowledge management in that organization and develop an action plan for the future. Findings - Only three organizations had adopted a strongly technology-based "solution" to knowledge management problems, and these followed three substantially different routes. There was a clear emphasis on the use of general information technology tools to support knowledge management activities, rather than the use of tools specific to knowledge management. Research limitations/implications - Further research is needed to help organizations make best use of generally available software such as intranets and e-mail for knowledge management. Many issues, especially human, relate to the implementation of any technology. Participation was restricted to organizations that wished to produce an action plan for knowledge management. The findings may therefore represent only "average" organizations, not the very best practice. Practical implications - Each organization must resolve four tensions: Between the quantity and quality of information/knowledge, between centralized and decentralized organization, between head office and organizational knowledge, and between "push" and "pull" processes. Originality/value - Although it is the group rather than an individual that determines what counts as knowledge, hardly any previous studies of knowledge management have collected data in a group context.

Scaling up question-answering to linked data

Linked Data semantic sources, in particular DBpedia, can be used to answer many user queries. PowerAqua is an open multi-ontology Question Answering (QA) system for the Semantic Web (SW). However, the emergence of Linked Data, characterized by its openness, heterogeneity and scale, introduces a new dimension to the Semantic Web scenario, in which exploiting the relevant information to extract answers for Natural Language (NL) user queries is a major challenge. In this paper we discuss the issues and lessons learned from our experience of integrating PowerAqua as a front-end for DBpedia and a subset of Linked Data sources. As such, we go one step beyond the state of the art on end-users interfaces for Linked Data by introducing mapping and fusion techniques needed to translate a user query by means of multiple sources. Our first informal experiments probe whether, in fact, it is feasible to obtain answers to user queries by composing information across semantic sources and Linked Data, even in its current form, where the strength of Linked Data is more a by-product of its size than its quality. We believe our experiences can be extrapolated to a variety of end-user applications that wish to scale, open up, exploit and re-use what possibly is the greatest wealth of data about everything in the history of Artificial Intelligence. © 2010 Springer-Verlag.

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.

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. © 2010 The authors.

Using the Agglomerative Method of Hierarchical Clustering as a Data Mining Tool in Capital Market

The purpose of this paper is to explain the notion of clustering and a concrete clustering method- agglomerative hierarchical clustering algorithm. It shows how a data mining method like clustering can be applied to the analysis of stocks, traded on the Bulgarian Stock Exchange in order to identify similar temporal behavior of the traded stocks. This problem is solved with the aid of a data mining tool that is called XLMiner™ for Microsoft Excel Office.

Towards the Problems of an Evaluation of Data Uncertainty in Decision Support Systems

The question of forming aim-oriented description of an object domain of decision support process is outlined. Two main problems of an estimation and evaluation of data and knowledge uncertainty in decision support systems – straight and reverse, are formulated. Three conditions being the formalized criteria of aimoriented constructing of input, internal and output spaces of some decision support system are proposed. Definitions of appeared and hidden data uncertainties on some measuring scale are given.