• The Journal of Korean Philosophical History
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• no.29
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• pp.255-280
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• 2010

Zhang Bo-duan compiled about internal alchemy in Taoism. Although he lived in the mundane world, he wished to seek theory on neidan of Taoism(internal alchemy). After finding enlightenment, he elucidated that the enlightenment was a state of rising above world not needed to leave the world. After ages, he was admired as the founder of Taoism in Southern school and his Oh Jin Peon which contents internal alchemy was considered seriously to have more than 30 people who annotated with it until Ch'ing Empire. At his age of 80, he met the real person who gave him theory on neidan of Taoism(internal alchemy), its preface tells that he organized its main point, and then wrote Oh Jin Peon with it in 1075. Generally Zhang Bo-duan was known to leave three books as Oh Jin Peon, Guem Dan Sa Baek Ja, and Cheung Hwa Bi Mun, most of critics have been studying on the basis of them. However, it is not correct whether all of them is his writings and there is not exact analysis but simple belief about it. I think accuracy and details are indispensible in philosophical approach. The study not having verification about primary data is no more than a visionary projet which soon collapses. So the purpose of this study is adding the detail analysis on it and making its exact basis of philosophical approach. Zhang Bo-duan over his age of 80, became enlightened, in his old age handed down his student the secret as a record and theory on neidan of Taoism(internal alchemy). And not in his living but after his dying his status was soared. Because of his high status in internal alchemy Taoism, it seems that there are more interest in it and some published books which just leave his name. In this study, I accept Oh Jin Peon as a his real writing among unsure his writings and criticize systematically and classify its characteristics. And I demonstrate that Guem Dan Sa Baek Ja, Cheung Hwa Bi Mun couldn't be his real writings, these could be forgeries by posterity, with proposing some basis of the argument.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.