Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

A tudásreprezentáció és a tudásmegosztás információtechnológiai megoldásai a személyazonosság-menedzsment területén (Knowledge Representation and Sharing for Identity Management Domain)

A személyazonosság-menedzsment napjaink fontos kutatási területe mind elméleti, mind gyakorlati szempontból. A szakterületen megvalósuló együttműködés, elektronikus tudásáramoltatás és csere hosszú távon csak úgy képzelhető el, hogy az azonos módon történő értelmezést automatikus eszközök támogatják. A szerző cikkében azokat a kutatási tevékenységeket foglalja össze, amelyeket - felhasználva a tudásmenedzsment, a mesterséges intelligencia és az információtechnológia eszközeit - a személyazonosság-menedzsment terület fogalmi leképezésére, leírására használt fel. Kutatási célja olyan közös fogalmi bázis kialakítása volt személyazonosság-menedzsment területre, amely lehetővé teszi az őt körülvevő multidimenzionális környezet kezelését. A kutatás kapcsolódik a GUIDE kutatási projekthez is, amelynek a szerző résztvevője. ______________ Identity management is an important research field from theoretical and practical aspects as well. The task itself is not new, identification and authentication was necessary always in public administration and business life. Information Society offers new services for citizens, which dramatically change the way of administration and results additional risks and opportunities. The goal of the demonstrated research was to formulate a common basis for the identity management domain in order to support the management of the surrounding multidimensional environment. There is a need for capturing, mapping, processing knowledge concerning identity management in order to support reusability, interoperability; to help common sharing and understanding the domain and to avoid inconsistency. The paper summarizes research activities for the identification, conceptualisation and representation of domain knowledge related to identity management, using the results of knowledge management, artificial intelligence and information technology. I utilized the experiences of Guide project, in which I participate. The paper demonstrates, that domain ontologies could offer a proper solution for identity management domain conceptualisation.

A study on uncertain dynamic disaster management tasks, knowledge sharing, and task performance

Each disaster presents itself with a unique set of characteristics that are hard to determine a priori. Thus disaster management tasks are inherently uncertain, requiring knowledge sharing and quick decision making that involves coordination across different levels and collaborators. While there has been an increasing interest among both researchers and practitioners in utilizing knowledge management to improve disaster management, little research has been reported about how to assess the dynamic nature of disaster management tasks, and what kinds of knowledge sharing are appropriate for different dimensions of task uncertainty characteristics. ^ Using combinations of qualitative and quantitative methods, this research study developed the dimensions and their corresponding measures of the uncertain dynamic characteristics of disaster management tasks and tested the relationships between the various dimensions of uncertain dynamic disaster management tasks and task performance through the moderating and mediating effects of knowledge sharing. ^ Furthermore, this research work conceptualized and assessed task uncertainty along three dimensions: novelty, unanalyzability, and significance; knowledge sharing along two dimensions: knowledge sharing purposes and knowledge sharing mechanisms; and task performance along two dimensions: task effectiveness and task efficiency. Analysis results of survey data collected from Miami-Dade County emergency managers suggested that knowledge sharing purposes and knowledge sharing mechanisms moderate and mediate uncertain dynamic disaster management task and task performance. Implications for research and practice as well directions for future research are discussed.^

The Effect of Authentic Literacy Experiences as Book Buddies with Hispanic Fourth Graders on Preservice Teachers’ Literacy Content Knowledge and Reading Maturity

From a sociocultural perspective, individuals learn best from contextualized experiences. In preservice teacher education, contextualized experiences include authentic literacy experiences, which include a real reader and writer and replicate real life communication. To be prepared to teach well, preservice teachers need to gain literacy content knowledge and possess reading maturity. The purpose of this study was to examine the effect of authentic literacy experiences as Book Buddies with Hispanic fourth graders on preservice teachers’ literacy content knowledge and reading maturity. The study was a pretest/posttest design conducted over 12 weeks. Preservice teacher participants, the focus of the study, were elementary education majors taking the third of four required reading courses in non-probabilistic convenience groups, 43 (n = 33 experimental, n = 10 comparison) Elementary Education majors. The Survey of Preservice Teachers’ Knowledge of Teaching and Technology (SPTKTT), specifically designed for preservice teachers majoring in elementary or early childhood education and the Reading Maturity Survey (RMS) were used in this study. Preservice teachers chose either the experimental or comparison group based on the opportunity to earn extra credit points (experimental = 30 points, comparison = 15). After exchanging introductory letters preservice teachers and Hispanic fourth graders each read four books. After reading each book preservice teachers wrote letters to their student asking higher order thinking questions. Preservice teachers received scanned copies of their student’s unedited letters via email which enabled them to see their student’s authentic answers and writing levels. A series of analyses of covariance were used to determine whether there were significant differences in the dependent variables between the experimental and comparison groups. This quasi-experimental study tested two hypotheses. Using the appropriate pretest scores as covariates for adjusting the posttest means of the subcategory Literacy Content Knowledge (LCK), of the SPTKTT and the RMS, the mean adjusted posttest scores from the experimental group and comparison group were compared. No significant differences were found on the LCK dependent variable using the .05 level of significance, which may be due to Type II error caused by the small sample size. Significant differences were found on RMS using the .05 level of significance.

A long-term energy efficiency prediction model for the Brazilian automotive industry

According to law number 12.715/2012, Brazilian government instituted guidelines for a program named Inovar-Auto. In this context, energy efficiency is a survival requirement for Brazilian automotive industry from September 2016. As proposed by law, energy efficiency is not going to be calculated by models only. It is going to be calculated by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in market will be a key factor on profits of each automaker. Energy efficiency and its consequences should be taken into consideration in all of its aspects. In this scenario, emerges the following question: which is the efficiency curve of one automaker for long term, allowing them to adequate to rules, keep balancing on investment in technologies, increasing energy efficiency without affecting competitiveness of product lineup? Among several variables to be considered, one can highlight the analysis of manufacturing costs, customer value perception and market share, which characterizes this problem as a multi-criteria decision-making. To tackle the energy efficiency problem required by legislation, this paper proposes a framework of multi-criteria decision-making. The proposed framework combines Delphi group and Analytic Hierarchy Process to identify suitable alternatives for automakers to incorporate in main Brazilian vehicle segments. A forecast model based on artificial neural networks was used to estimate vehicle sales demand to validate expected results. This approach is demonstrated with a real case study using public vehicles sales data of Brazilian automakers and public energy efficiency data.

Um modelo para aferir o nível de maturidade na adoção de SOA

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Ferramenta de gestão de conhecimento colectivo : KNOEY - Knowledge Embraces You

Mestrado em Ciências Empresariais

Knowledge-based management systems for the police force

Knowledge-Based Management Systems enable new ways to process and analyse knowledge to gain better insights to solve a problem and aid in decision making. In the police force such systems provide a solution for enhancing operations and improving client administration in terms of knowledge management. The main objectives of every police officer is to ensure the security of life and property, promote lawfulness, and avert and distinguish wrongdoing. The administration of knowledge and information is an essential part of policing, and the police ought to be proactive in directing both explicit and implicit knowledge, whilst adding to their abilities in knowledge sharing. In this paper the potential for a knowledge based system for the Mauritius police was analysed, and recommendations were also made, based on requirements captured from interviews with several long standing officers, and surveying of previous works in the area.

Improvement of radiology services based on the process management approach

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.

Systemic Model for Diagnosis of the Micro, Small and Medium Enterprises from Two Cities from the Countryside of the State of So Paulo in Brazil

This article presents a proposal of a systemic model composed for the micro and small companies (MSE) of the region of Ribeiro Preto and the agents which influenced their environment. The proposed model was based on Stafford Beer`s (Diagnosing the system for organizations. Chichester, Wiley, 1985) systemic methodologies VSM (Viable System Model) and on Werner Ulrich`s (1983) CSH (Critical Systems Heuristics). The VSM is a model for the diagnosis of the structure of an organization and of its flows of information through the application of the cybernetics concepts (Narvarte, In El Modelo del Sistema Viable-MSV: experiencias de su aplicacin en Chile. Proyecto Cerebro Colectivo del IAS, Santiago, 2001). On the other hand, CSH focus on the context of the social group applied to the systemic vision as a counterpoint to the organizational management view considered by the VSM. MSE of Ribeiro Preto and Sertozinho had been analyzed as organizations inserted in systems that relate and integrate with other systems concerning the public administration, entities of representation and promotion agencies. The research questions: which are the bonds of interaction among the subsystems in this process and who are the agents involved? The systemic approach not only diagnosed a social group, formed by MSE of Ribeiro Preto and Sertozinho, public authorities and support entities, but could also delineate answers that aimed the clarification of obscure questions generating financial assistance to the formularization of efficient actions for the development of this system.

What is the value of firms' prior knowledge? Building organisational knowledge capabilities

A firm's prior knowledge facilitates the absorption of new knowledge, thereby renewing a firm's systematic search, transfer and absorption capabilities. The rapidly expanding field of biotechnology is characterised by the convergence of disparate sciences and technologies. This paper, the shift from proteinbased to DNA-based diagnostic technologies, quantifies the value of a firm's prior knowledge and its relation to future knowledge development. Four dimensions of diagnostic and four dimensions of knowledge in biotechnology firms are analysed. A simple scaled matrix method is developed to quantify the positive and negative heuristic values of prior scientific and technological knowledge that is useful for the acquisition and absorption of new knowledge.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Phenomenological turbulence and innovation in knowledge systems

Most considerations of knowledge management focus on corporations and, until recently, considered knowledge to be objective, stable, and asocial. In this paper we wish to move the focus away from corporations, and examine knowledge and national innovation systems. We argue that the knowledge systems in which innovation takes place are phenomenologically turbulent, a state not made explicit in the change, innovation and socio-economic studies of knowledge literature, and that this omission poses a serious limitation to the successful analysis of innovation and knowledge systems. To address this lack we suggest that three evolutionary processes must be considered: self-referencing, self-transformation and self-organisation. These processes, acting simultaneously, enable system cohesion, radical innovation and adaptation. More specifically, we argue that in knowledge-based economies the high levels of phenomenological turbulence drives these processes. Finally, we spell out important policy principles that derive from these processes.