A database schema should consist of structures and semantic integrity constraints. Se mantic integrity constraints (SICs) are invariant restrictions on the static states of the stored data and the state transitions caused by the primitive operations: insertion, dele tion, or update. Traditionally, database design has been carried out on an ad hoc basis and focuses on structure and efficiency. Although the E-R model is the popular concep tual modelling tool, it contains few inherent SICs. Also, although the relational database model is the popular logical data model, a relational database in fourth or fifth normal form may still represent little of the data semantics. Most integrity checking is distributed to the application programs or transactions. This approach to enforcing integrity via the application software causes a number of problems. Recently, a number of systems have been developed for assisting the database design process. However, only a few of those systems try to help a database designer incorporate SICs in a database schema. Furthermore, current SIC representation languages in the literature cannot be used to represent precisely the necessary features for specifying declarative and operational semantics of a SIC, and no modelling tool is available to incorporate SICs. This research solves the above problems by presenting two models and one subsystem. The E-R-SIC model is a comprehensive modelling tool for helping a database designer in corporate SICs in a database schema. It is application domain-independent and suitable for implementation as part of an automated database design system. The SIC Repre sentation model is used to represent precisely these SICs. The SIC elicitation subsystem would verify these general SICs to a certain extent, decompose them into sub-SICs if necessary, and transform them into corresponding ones in the relational model. A database designer using these two modelling tools can describe more data semantics than with the widely used relational model. The proposed SIC elicitation subsystem can provide more modelling assistance for him (her) than current automated database design systems.

A database schema should consist of structures and semantic integrity constraints. Se mantic integrity constraints (SICs) are invariant restrictions on the static states of the stored data and the state transitions caused by the primitive operations: insertion, dele tion, or update. Traditionally, database design has been carried out on an ad hoc basis and focuses on structure and efficiency. Although the E-R model is the popular concep tual modelling tool, it contains few inherent SICs. Also, although the relational database model is the popular logical data model, a relational database in fourth or fifth normal form may still represent little of the data semantics. Most integrity checking is distributed to the application programs or transactions. This approach to enforcing integrity via the application software causes a number of problems. Recently, a number of systems have been developed for assisting the database design process. However, only a few of those systems try to help a database designer incorporate SICs in a database schema. Furthermore, current SIC representation languages in the literature cannot be used to represent precisely the necessary features for specifying declarative and operational semantics of a SIC, and no modelling tool is available to incorporate SICs. This research solves the above problems by presenting two models and one subsystem. The E-R-SIC model is a comprehensive modelling tool for helping a database designer in corporate SICs in a database schema. It is application domain-independent and suitable for implementation as part of an automated database design system. The SIC Repre sentation model is used to represent precisely these SICs. The SIC elicitation subsystem would verify these general SICs to a certain extent, decompose them into sub-SICs if necessary, and transform them into corresponding ones in the relational model. A database designer using these two modelling tools can describe more data semantics than with the widely used relational model. The proposed SIC elicitation subsystem can provide more modelling assistance for him (her) than current automated database design systems. / Business, Sauder School of / Graduate

M. Tech. Electrical Engineering. / Proposes a voice and video service that uses context-awareness and Semantic Web technologies to restrict network access to non-privileged users during crisis situations. The laboratory tests show how the service takes over call adission control from the SIP server, rejects non-privileged calls and drops non-privileged ongoing call sessions. OPNet simulations further show how to proposed service improves network performance based on performance parameters such as end-to-end delay time and throughput.

Indiana University-Purdue University Indianapolis (IUPUI) / Pharmacodynamics (PD) studies the relationship between drug concentration and drug effect on target sites. This field has recently gained attention as studies involving PD Drug-Drug interactions (DDI) assure discovery of multi-targeted drug agents and novel efficacious drug combinations. A PD drug combination could be synergistic, additive or antagonistic depending upon the summed effect of the drug combination at a target site. The PD literature has grown immensely and most of its knowledge is dispersed across different scientific journals, thus the manual identification of PD DDI is a challenge. In order to support an automated means to extract PD DDI, we propose Pharmacodynamics Miner (PD-Miner). PD-Miner is a text-mining tool, which is capable of identifying PD DDI from in vitro PD experiments. It is powered by two major features, i.e., collection of full text articles and in vitro PD ontology. The in vitro PD ontology currently has four classes and more than hundred subclasses; based on these classes and subclasses the full text corpus is annotated. The annotated full text corpus forms a database of articles, which can be queried based upon drug keywords and ontology subclasses. Since the ontology covers term and concept meanings, the system is capable of formulating semantic queries. PD-Miner extracts in vitro PD DDI based upon references to cell lines and cell phenotypes. The results are in the form of fragments of sentences in which important concepts are visually highlighted. To determine the accuracy of the system, we used a gold standard of 5 expert curated articles. PD-Miner identified DDI with a recall of 75% and a precision of 46.55%. Along with the development of PD Miner, we also report development of a semantically annotated in vitro PD corpus. This corpus includes term and sentence level annotations and serves as a gold standard for future text mining.