This paper describes the creation process and statistics of Punjabi English (PunEng) parallel corpus. Parallel corpus is the main requirement to develop statistical machine translation as well as neural machine translation. Until now, we do not have any availability of PunEng parallel corpus. In this paper, we have shown difficulties and intensive labor to develop parallel corpus. Methods used for collecting data and the results are discussed, errors during the process of collecting data and how to handle these errors will be described.

OBJECTIVE:The study aimed at evaluating the impact of 24 hours of sleep deprivation on temporal processing and frequency resolution in normal individuals with no history of neurological and psychological deficits. MATERIALS and METHODS:Sixteen individuals with normal hearing were included in the study. Temporal modulated transfer function, gap detection test, duration discrimination test, and pitch discrimination test were carried out in all of the individuals with a baseline evaluation, followed by an intra-test evaluation after 24 hours of sleep deprivation. RESULTS:The mean gap detection test values were elevated in sleep deprivation conditions as compared to the baseline condition. The temporal modulation transfer function scores were also increased in the sleep deprivation condition when compared to the baseline condition. Individuals performed poorly for the duration discrimination test and pitch discrimination test in the sleep-deprived condition. All tests showed statistical significance between the two conditions, with p<0.005. DISCUSSION:The reduced scores may be due to the effects of sleep deprivation on working memory, arousal, attention, concentration, and also reduced metabolism in the frontal lobe. CONCLUSION:This could indicate that sleep deprivation also affects central auditory processing, since temporal processing and frequency resolution form the neurobiological basis of central auditory processing. Hence, it can be put forth that an acute period of 24 hours of sleep deprivation was sufficient to significantly worsen temporal processing and frequency resolution abilities.

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Fault tree analysis is a widely accepted technique to assess the probability and frequency of system failure in many industries.Traditionally statistical methods and boolean reductions is employed to analyze the fault tree. Even though the fault tree approach is commonly used for system reliability analysis, there are inherent limitations in terms of accuracy and computational efficiency. For the evaluation of minimal cut-set using fault tree method, it is required to solve large number of boolean expressions which increases number of computations. At the same time these computations are based on approximations which affect the accuracy of the results. The Binary Decision Diagram (BDD) is relatively new approach employed for fault tree analysis which has better computational efficiency. But the limitations of BDD lies in the optimal ordering of basic events, because such an ordering determines the final size of BDD which in turns determines the overall efficiency of this method. Hence the choice of heuristic is very crucial to get the maximum benefit from this method. Fordetermining the optimal ordering many heuristic has been developed, but not a single heuristic is able to give minimal BDD.Hence for the determining the optimal ordering a latest approach based on "Genetic algorithm (GA)" is presented in our project. In our project we have discussed the current heuristic approaches being used for BDD size optimization and highlighted its limitations. Then we have proposed a generalized method for the selection of optimal ordering of basic events using GA, which is not based on any heuristic previously given. Main key idea in the application of GA in BDD size optimization is to define population size and representation of ordered set of variable as chromosome. I. I NTRODUCTIONFault tree analysis is a widely accepted technique to assess the probability and frequency of system failure in many industries. Limitations of fault tree method for calculating minimal cut-sets can be overcome by Binary decision diagram method. The Binary decision diagram (BDD) is relatively new approach which is based on binary logic where there is no need to solve such boolean expressions for finding minimal cut-sets. The BDD method does not analyse the fault tree directly, but converts978-1-4244-8343-3/10/$26.00 ©2010 IEEE 168 the tree to a BDD, which represents the Boolean equation for the top event and hence has better computational efficiency. To overcome these problems various techniques have been employed to reduce the number of comparisons [1]. Some methods only produce the most important minimal cut sets. One of these techniques is referred to as culling, which means that cut sets of a certain order, say 4 and above, are ignored or deleted from the expression, Rasmuson and Marshall [2] employ this technique in their paper. The justification for doing this is that cutsets of a high order tend to have low probability of occurrence and therefore do not make a significant contribution to the top event probability. However the disadvant...

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