Sets as graphs

The aim of this thesis is a mutual transfer of computational and structural results and techniques between sets and graphs. We study combinatorial enumeration of sets, canonical encodings, random generation, digraph immersions. We also investigate the underlying structure of sets in algorithmic terms, or in connection with hereditary graphs classes. Finally, we employ a set-based proof-checker to verify two classical results on claw-free graph

HYPERSOLVER: A graphical tool for commonsense set theory

This paper investigates an alternative set theory (due to Aczel) called the Hyperset Theory. Aczel uses a graphical representation for sets and thereby allows the representation of non-well-founded sets. A program, called hypersolver, which can solve systems of equations defined in terms of sets in the universe of this new theory is presented. This may be a useful tool for commonsense reasoning. © 1995

Knowledge sharing framework for sustainability of knowledge capital

Knowledge sharing is one of the most critical elements in a knowledgebased society. With huge concentration on communication facilities, there is a major shift in world-wide access to codified knowledge. Although communication technologies have made great strides in the development of instruments for accessing required knowledge and improving the level of knowledge sharing, there are still many obstacles which diminish the effectiveness of knowledge sharing in an organization or a community. The current challenges include: identification of the most important variables in knowledge sharing, development of an effective knowledge sharing measurement model, development of an effective mechanism for knowledge sharing reporting and calculating knowledge capital that can be created by knowledge sharing. The ability and willingness of individuals to share both their codified and uncodified knowledge have emerged as significant variables in knowledge sharing in an environment where all people have access to communication instruments and have the choice of either sharing their own knowledge or keeping it to themselves.This thesis addresses knowledge sharing variables and identifies the key variables as: willingness to share or gain knowledge, ability to share or gain knowledge, complexity or transferability of the shared knowledge. Different mechanisms are used to measure these key variables. Trust mechanisms are used to measure the willingness and ability of individuals to share or acquire knowledge. By using trust mechanisms, one can rate the behavior of the parties engaged in knowledge sharing and subsequently assign a value to the willingness and ability of individuals to share or obtain knowledge. Also, ontology mechanisms are used to measure the complexity and transferability of a particular knowledge in the knowledge sharing process. The level of similarity between sender and receiver ontologies is used to measure the transferability of a particular knowledge between knowledge sender and receiver. Ontology structure is used to measure the complexity of the knowledge transmitted between knowledge sharing parties.A knowledge sharing framework provides a measurement model for calculating knowledge sharing levels based on trust and ontology mechanisms. It calculates knowledge sharing levels numerically and also uses a Business Intelligence Simulation Model (BISIM) to simulate a community and report the knowledge sharing level between members of the simulated community. The simulated model is able to calculate and report the knowledge sharing and knowledge acquisition levels of each member in addition to the total knowledge sharing level in the community.Finally, in order to determine the advantages of knowledge sharing for a community, capital that can be created by knowledge sharing is calculated by using intellectual capital measurement mechanisms. Created capital is based on knowledge and is related to the role of knowledge sharing in increasing the embedded knowledge of individuals (human capital), improving connections, and embedding knowledge within connections (social capital). Also, market components (such as customers) play a major role in business, and knowledge sharing improves the embedded knowledge within market components that is defined as market capital in this thesis. All these categories of intellectual capital are measured and reported in the knowledge sharing framework