Abhisit Told Ni Thai Rath 011009

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The Thai Rath newspaper reported on October 1, 2009 that Prime Minister Abhisit was accused of copying another person's research work. Specifically, the newspaper alleged that when Abhisit was director of the National Innovation Agency (NIA), he copied significant portions of another researcher's work and published it under his own name. The newspaper article did not provide any additional details or context regarding the allegation.

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Thai Rath 01 October 2009
'ABHISIT TOLD NIA DIRECTOR COPIES OTHER PERSON'S RESEARCH'
Thai, daily, located Thailand Circulation: 1200000
Source: Own Source/Bangkok - Writer not named Page 15

Segmentation approaches, as processes that divide word into smaller parts which contain one letter at most, have important effect on cursive word recognition. While online cursive word recognition became applied technology in Latin and Chinese languages, complex structural features in Arabic-based script made it an important field of study in Persian and Arabic languages. In this paper, by introducing of Standard Persian Handwriting, we proposed a novel approach to segmentation online Persian cursive script based on width of letter's body in Persian language. Results are shown 99.86% accuracy in detection of expected segmentation points, while recognized extra points reduced 93.73% compared to our previous methods.

Risk Prediction for Production of an Enterprise

Editor IJCATR

Despite all preventive measures, there is so much possibility of risks in any project development as well as in enterprise management. There is no any standard mechanism or methodology available to assess the risks in any project or production management. Using some precautionary steps, the manager can only avoid the risks as much as he can. To address this issue, this paper presents a probabilistic risk assessment model for the production of an enterprise. For this, Multi-Entity Bayesian Network (MEBN) has been used to represent the requirements for production management as well as to assess the risks adherence in production management, where MEBN combines expressivity of first-order logic and probabilistic feature of Bayesian network. Bayesian network provides the feature to represent the probabilistic uncertainty and reasoning about probabilistic knowledge base, which is used here to represent the probable risks behind each causes of a risk. The proposed probabilistic model is discussed with the help of a case study, which is used to predict risks inherent in the production of an enterprise, which depends upon various measures like labour availability, power backup, transport availability etc.

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