• Title/Summary/Keyword: 대형 언어 모델

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An Improved SysML-Based Failure Model for Safety Verification By Simulation (시뮬레이션을 통해 안전성 검증을 위한 개선된 SysML 기반 고장 모델)

  • Kim, Chang-Won;Lee, Jae-Chon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.10
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    • pp.410-417
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    • 2018
  • System design errors are more likely to occur in modern systems because of their steadily increasing size and complexity. Failures due to system design errors can cause safety-related accidents in the system, resulting in extensive damage to people and property. Therefore, international standards organizations, such as the U.S. Department of Defense and the International Electrotechnical Commission, have established international safety standards to ensure system safety, and recommend that system design and safety activities should be integrated. Recently, the safety of a system has been verified by modeling through a model-based system design. On the other hand, system design and safety activities have not been integrated because the model for system design and the failure model for safety analysis and verification were developed using different modeling language platforms. Furthermore, studies using UML or SysML-based failure models for deriving safety requirements have shown that these models have limited applicability to safety analysis and verification. To solve this problem, it is essential to extend the existing methods for failure model implementation. First, an improved SysML-based failure model capable of integrating system design and safety verification activities should be produced. Next, this model should help verify whether the safety requirements derived via the failure model are reflected properly in the system design. Therefore, this paper presents the concept and method of developing a SysML-based failure model for an automotive system. In addition, the failure model was simulated to verify the safety of the automotive system. The results show that the improved SysML-based failure model can support the integration of system design and safety verification activities.

Semantic Network Analysis of 2019 Gangwon-do Wild Fire News Reporting: Focusing on Media Agenda Analysis (2019년 강원도 화재 보도에 대한 언어망 분석: 미디어의제 분석을 중심으로)

  • Lee, Jeng Hoon
    • The Journal of the Korea Contents Association
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    • v.19 no.11
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    • pp.153-167
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    • 2019
  • This study aims to identify the media agenda and to compare each media agenda by media and by time period, analyzing the news about 2019 Gangwon-do's wild fire reported by 37 Korean news media. Using the topic modeling algorithm and semantic network analysis, this study inspected the configuration of the network media agenda and examined the intermedia agenda setting effect by using QAP correlation analysis. Results showed that the sensational media agenda with the attributes such as victim aid and political conflict and the similarity of each media agenda for this disaster reporting.

Deep learning-based Multilingual Sentimental Analysis using English Review Data (영어 리뷰데이터를 이용한 딥러닝 기반 다국어 감성분석)

  • Sung, Jae-Kyung;Kim, Yung Bok;Kim, Yong-Guk
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.3
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    • pp.9-15
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    • 2019
  • Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

Contrastive Information Processing in Discourse Comprehension

  • Lee Jung-Mo;Lee Jae-Ho
    • Korean Journal of Cognitive Science
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    • v.16 no.2
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    • pp.69-92
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    • 2005
  • A brief survey of linguistic studies on the nature of contrastive information in discourse was Presented first, and an attempt was also made to incorporate the Linguistic theories and concepts about contrast in discourse into a psychological framework. A tentative model of processing of contrastive information in discourse was Proposed, and eight experimental studies on the effects of contrastive information on comprehension and memory of short and ions discourses were reviewed. Experimental results showed that contrastive sentences took more time to process at encoding, and yet were recognized faster and cued-recalled in greater amount than noncontrastive sentences. It was also found that levels of contrast in the discourse structure have some effects on encoding time. It was further found that the sentence immediately following the contrastive sentence was processed slowly regardless of whether it does or does not resolve the contrast. The implications of the results of empirical studies were discussed in relation to developing a research framework that integrate coherence studies and contrast studies urns the two disciplines of linguistics and cognitive psychology.

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