KFTKGA: Knowledge Flow Tracer and Growth Analyzer for Community Learning

The advances in building learning technology now have to emphasize on the aspect of the individual learning besides the popular focus on the technology per se. Unlike the common research where a great deal has been on finding ways to build, manage, classify, categorize and search knowledge on the server, there is an interest in our work to look at the knowledge development at the individual’s learning. We build the technology that resides behind the knowledge sharing platform where learning and sharing activities of an individual take place. The system that we built, KFTGA (Knowledge Flow Tracer and Growth Analyzer), demonstrates the capability of identifying the topics and subjects that an individual is engaged with during the knowledge sharing session and measuring the knowledge growth of the individual learning on a specific subject on a given time space.

Implementação de um ambiente computacional para ensino à distância

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Measuring conflict and agreement between two prioritized knowledge bases in possibilistic logic.

In this paper we investigate the relationship between two prioritized knowledge bases by measuring both the conflict and the agreement between them.First of all, a quantity of conflict and two quantities of agreement are defined. The former is shown to be a generalization of the well-known Dalal distance which is the hamming distance between two interpretations. The latter are, respectively, a quantity of strong agreement which measures the amount ofinformation on which two belief bases “totally” agree, and a quantity of weak agreement which measures the amount of information that is believed by onesource but is unknown to the other. All three quantity measures are based on the weighted prime implicant, which represents beliefs in a prioritized belief base. We then define a degree of conflict and two degrees of agreement based on our quantity of conflict and quantities of agreement. We also consider the impact of these measures on belief merging and information source ordering.

Measuring the blame of each formula for inconsistent prioritized knowledge bases.

It is increasingly recognized that identifying the degree of blame or responsibility of each formula for inconsistency of a knowledge base (i.e. a set of formulas) is useful for making rational decisions to resolve inconsistency in that knowledge base. Most current techniques for measuring the blame of each formula with regard to an inconsistent knowledge base focus on classical knowledge bases only. Proposals for measuring the blames of formulas with regard to an inconsistent prioritized knowledge base have not yet been given much consideration. However, the notion of priority is important in inconsistency-tolerant reasoning. This article investigates this issue and presents a family of measurements for the degree of blame of each formula in an inconsistent prioritized knowledge base by using the minimal inconsistent subsets of that knowledge base. First of all, we present a set of intuitive postulates as general criteria to characterize rational measurements for the blames of formulas of an inconsistent prioritized knowledge base. Then we present a family of measurements for the blame of each formula in an inconsistent prioritized knowledge base under the guidance of the principle of proportionality, one of the intuitive postulates. We also demonstrate that each of these measurements possesses the properties that it ought to have. Finally, we use a simple but explanatory example in requirements engineering to illustrate the application of these measurements. Compared to the related works, the postulates presented in this article consider the special characteristics of minimal inconsistent subsets as well as the priority levels of formulas. This makes them more appropriate to characterizing the inconsistency measures defined from minimal inconsistent subsets for prioritized knowledge bases as well as classical knowledge bases. Correspondingly, the measures guided by these postulates can intuitively capture the inconsistency for prioritized knowledge bases.

Computational approaches to finding and measuring inconsistency in arbitrary knowledge bases

There is extensive theoretical work on measures of inconsistency for arbitrary formulae in knowledge bases. Many of these are defined in terms of the set of minimal inconsistent subsets (MISes) of the base. However, few have been implemented or experimentally evaluated to support their viability, since computing all MISes is intractable in the worst case. Fortunately, recent work on a related problem of minimal unsatisfiable sets of clauses (MUSes) offers a viable solution in many cases. In this paper, we begin by drawing connections between MISes and MUSes through algorithms based on a MUS generalization approach and a new optimized MUS transformation approach to finding MISes. We implement these algorithms, along with a selection of existing measures for flat and stratified knowledge bases, in a tool called mimus. We then carry out an extensive experimental evaluation of mimus using randomly generated arbitrary knowledge bases. We conclude that these measures are viable for many large and complex random instances. Moreover, they represent a practical and intuitive tool for inconsistency handling.

Measuring the economic value of pollination services: principles, evidence and knowledge gaps

An increasing degree of attention is being given to the ecosystem services which insect pollinators supply, and the economic value of these services. Recent research suggests that a range of factors are contributing to a global decline in pollination services, which are often used as a “headline” ecosystem service in terms of communicating the concept of ecosystem services, and how this ties peoples׳ well-being to the condition of ecosystems and the biodiversity found therein. Our paper offers a conceptual framework for measuring the economic value of changes in insect pollinator populations, and then reviews what evidence exists on the empirical magnitude of these values (both market and non-market). This allows us to highlight where the largest gaps in knowledge are, where the greatest conceptual and empirical challenges remain, and where research is most needed.

Development, reliability and validity of an instrument measuring the attitudes and knowledge of emergency department staff regarding the emergency nurse practitioner role

Introduction: The Emergency Department (ED) at The Northern Hospital is currently participating in the Victorian Department of Human Services funded Emergency Nurse Practitioner Project. This project aims to develop, implement and evaluate the Emergency Nurse Practitioner role in Victorian EDs. This led to a need to develop a specific data collection tool called The Northern Emergency Nurse Practitioner Staff Survey to examine the knowledge and attitudes of ED medical and nursing staff. This paper describes the development of The Northern Emergency Nurse Practitioner Staff Survey and presents the results of reliability and validity studies. Method: Twenty-five items were developed and piloted on a sample of 58 ED medical and nursing staff. Content and face validity were established by expert panel review. Reliability was established by tests of unidimensionality, exploratory factor analysis and internal consistency. Results: Four items were discarded because of low item to total correlation. Exploratory factor analysis of the remaining items revealed five factors with eigenvalues >1 and acceptable correlation coefficients that explained 76.7% of the variance. Cronbach’s coefficent α for these items was 0.926 indicating a high degree of internal consistency. The factors were titled to reflect the content domain of the items in each factor and the factors arranged in a logical sequence to form the final version of The Northern Emergency Nurse Practitioner Survey.

Strategies for measuring the knowledge economy in the Caribbean

Includes bibliography

Measuring Knowledge Management: A Strategic Approach to Library Information Services

In the study of theoretical trends in Administration, the management of information follows the development of theories of Administration; constant-adaptations are suffered. Information Science area understands and concerns itself with the changes wrought in these endeavour of the knowledge society as new forms of communication and integration. The libraries interact in ways that maximize access to information and facilitate the improvement on their structural environment as strategic approach for your services. The research aims at identifying the requirements and specifications of an information system for knowledge management in the public’s library environment and proposes to achieve a pre-defined structure for the implementation of administration management. The research is conducted with public’s library of the metropolitan region of the North’s Portugal. Portugal libraries are institutions that operate in the social process of their communities reflecting the society and its organic sphere of informational performance. These libraries have developed the organizational theories to make a framework easily for effective management practices and have been using their produced knowledge in the optimization of their actions. In the improvement of systems, theoretical administrative trends become management decisions and result in the ultimate success of the organization. In order to achieve its objectives the study verified an economy based on knowledge management, and its production emphasizes the human capital that permeates the condition of the information in support for the development of communities.