Cognitive Semantic Study of the Preposition ‘Min’ in the Quran

The preposition ‘min’ is semantically more complex than what the traditional lexicaAl-syntactic approaches held it to be adverb or adverbial of place and time. This paper attempts to investigate the semantic complexity of the preposition ‘min’ from cognitive linguistic perspective to find out its semantic classification and linguistic symmetric patterns. Data has been taken from the Quran to investigate the claim of conceptual metaphor theory that sensorimotor neural structures generates the preposition ‘min’ on the image schema of source-path-goal. The findings reveal that the source-pathgoal image schema is not only at work in the use of preposition ‘min’ in spatio-geometric sense, but also to map the abstract concepts, emotional states and relationship with supernatural entities in spatial terms in the Quran. However, the data also show idiosyncratic behaviour of preposition, attaining different semantic arguments in different linguistic contexts, which strengthen the argument that language use cannot be abridged to static mapping in the human conceptual system. This paper recommends future research on the same preposition or other prepositions to investigate further the source-path-goal image schema in the Quran and Arabic language.

Fuzzy Logic and Neural Network Application in Medical Information

Medical practitioner often makes decisions based on incomplete, vague, or uncertain information. Recently fuzzy based techniques have shown a more promising way to handle imprecise data. The approach consists in using the capacities of the commercial database management system while adding a supplementary layer assuring the interface between fuzzy queries. Such a fuzzy relational database management system (FRDBMS) deals more effectively in many applications enhancing the efficiency of processing fuzzy queries even in relational database management system (RDBMS). The implementation from RDBMS to FRDBMS requires knowledge of legacy database, knowledge about fuzzy logic and mapping from crisp to fuzzy values. Software layer is used with RDBMS to convert to FRDBMS, where fuzzy information is to be designed with care. The main feature of FRDBMS is linguistic fuzzy modeling, where the interpretability of the obtained model is the main requirement, together with its accuracy. The research of moving from RDBMS to FRDBMS is limited and not much work has been carried out. The research work presented in this thesis shows fuzzy RDBMS implementation using our developed FDSL Tool, where input to this tool is fuzzy SQL query and output is fuzzy linguistic value results. The FDSL Tool can be used with many fuzzy expert system applications. The developed Fuzzy Model is tested successfully on heart and diabetes datasets. Our implementation achieved an accuracy higher than other contemporary setups working on the same datasets as considered in this work. The improved results were attributed due to the incorporation of linguistic data and its implementation in metadata function.