Graduate Studies

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New Processing Model for Operating Systems
(Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2016) Weerakoon, C.; Karunananda, A.; Dias, N.G.J.
The computer plays a vital role in executing programs to solve problems. Further, for each and every such program, a process must be created, and all the required resources should be allocated to the process. In fact, the management of these processes is one of the most important jobs to be accomplished by an operating system. Moreover, by observing different behaviours that the processes display, the researchers have introduced variety of processing models such as two-state model, three-state model, five-state model, and seven-state model to increase the processing power of the computer. Here, the state of a process is related to the current task that the process does, and the term use for a state can be changed from one operating systems to another. Although, they have gained improvements, so far they have failed to produce a processing model to fully utilize the underline hardware architecture. Meanwhile, we made some observations on real world scenarios which revealed that how the human mind works is rather different from how the processing models incorporated in to the computers work till then. Furthermore, the human mind conditionally evolves with the time by drawing associations among the existing and newly arriving data and instructions. Having this insight, the research we conduct introduces a new eight-state processing model, which executes continuously depending on the presented conditions to enhance the processing power of the system. There, one additional state with the name “Terminate” with four new actions such as Ready-to-Ready, Ready-to-Terminate, Exit-to-Ready/Suspend, and Exit-to-Ready have been introduced to the existing seven-state processing model. In addition to those, two of the existing actions such as New-to-Ready/Suspend and New-to-Ready have been modified. In doing these changes, a set of fifteen from twenty four causal relations in Buddhist theory of mind, which can be exploited in explaining any phenomenon, has been applied. In order to depict the changes on each and every action, and to do the experiments, particular algorithms have being designing and these algorithms are to be integrated to the Kernel of the operating system. After doing these implementations, new processing model can be compared with the existing model by executing the same program for multiple times in the operating system with and without the new model and recording the time take in each round. Then the dependent two sample t-test which is more powerful and descriptive, can be applied on the results. Further, to check the quality of the new model a parametric test can be applied on the results of a survey conducted on a single group of users who has worked on the operating system with and without the new processing model.
A Plug-in to Boost the Behaviour of a Rule-Based Expert System More Like a Human
(Faculty of Graduate Studies, University of Kelaniya, 2015) Weerakoon, W.A.C.; Karunananda, A.S.; Dias, N.G.J.
Artificial Intelligence (AI) is one major aspect of Computer Science. Among the applications of AI, expert systems are predominant. There are expert systems built for variety of subject domains such as education, medicine, and engineering, and were built by imitating the human experts with the ability to make accurate decisions by resolving the proper set of rules and facts stored in a knowledgebase to solve more complex problems. When it comes to systems, it is expected to be more accurate, reliable, efficient and complete. The current expert systems consists of many facilities such as user interfaces, reasoning of the system, knowledgebase, working memory, making inferences, prioritizing and an automatic way for the user to enter knowledge, with compared to the human experts. Even though, the expert systems are still behind and much specific in some aspect such as the abilities in generalizing concepts, drawing associations among knowledge entities depending on the causal relationships, adding new knowledge, removing irrelevant knowledge, prioritizing knowledge entities for the execution as per the input to gain improvements over generations of execution as human experts do. Among the technical categories of the expert systems such as rulebased, frame-based and induction-based, our concern is to improve the rule-based expert systems by solving the said problem by constructing a processing model which consists of the processing states such as Origin, Classified, Pre-State, Resolve and Terminate with newly introduced multiple sub-processes such as Input/Identify knowledge entities, Classify facts/rules depending on the causal relationships crafting the generalizing facility and Termination. When the system executes over generations, it produces outputs and gains improvements using the above mentioned processing model as per the input/queries. For this processing model, newly introduced sub-processes will be implemented using C programming language and will integrate to the current expert systems written in ‗C Language Integrated Production System‘ as a plug-in. The system will be able to evaluate by comparing its states With-Plug-In and Without-Plug-In for the quality using a non-parametric test such as Mann-Whitney-U-test and for the time using a paired-t-test. As a result we are capable of providing an expert system which is more like a human expert.

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