• International Journal of Advanced Culture Technology
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• 제6권2호
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• pp.65-71
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• 2018

In the digital era, news consumption is not confined in geological boundaries. Technological advances bring the instant dissemination of news into life and allow news audience to consume events that occur far away almost in real time. The transmission has blurred the boundary between traditional media and new media, and the one between physical and virtual world. That is, what if a journalist applies news framing to the news translation process? This paper aims to investigate the gap between the ST and the TT created when the source news texts undergo a translation process. To achieve this aim, the appraisal theory developed by White (2003) is employed to identify a difference between the ST and the TT. Furthermore, we have attempted to identify differences between soft news stories and hard news stories while the STs from both news stories are translated into the TTs. Two time-sensitive events, Hugh Grant's marriage and a U.S. and North Korea summit, were selected. The former (a soft news story) is extracted from the Telegraph and the latter (a hard news story) is from the Washington post. As a result, it was found that such strategies as attitude, engagement, and judgment were used when the source news texts from the hard news story are translated into the target news texts. Under the appraisal theory, the strategies involve evaluative language which refers to positive or negative language that judges the worth of entities. In general, it is said that a journalist frames the SS (especially from the hard news story) to convey his ideology to news consumers. Hypothetically, we assume that a similar framing process takes place in deriving the TT from the SS of the hard news story. Thus, we could conclude that the TT from the hard news story differs from the TT from the soft news story and that the difference can be explained within the framework of White's appraisal theory.

• 대한한의학회지
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• 제31권4호
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• pp.129-140
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• 2010

Objective: The aim of this study was to prove adjacent effect of Oriental Medical Therapy on aphasia after stroke. Method: We studied patients who took K-WAB (AQ; aphasia quotient) twice during their language therapy at Kyunghee University Hospital & Oriental Medicine Hospital to retrospectively investigate the effect of Oriental medical therapy on aphasia. 18 patients with post-stroke aphasia were assigned to receive one of the following adjuncts: Group A that received language therapy with Oriental medical therapy (n=12) and Group B (n=6) that received language therapy only; AQ score of Group A was compared against Group B. Result: Total AQ score and most partial scores, except 'Contents delivery', were better in Group A. 'Total AQ score', 'Fluency', and 'Auditory verbal comprehension score' presented statistical significance. Conclusion: In this study, we demonstrated the effect of Oriental medical therapy on aphasia after stroke through AQ score improvement.

• 한국언어정보학회지:언어와정보
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• 제14권2호
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• pp.71-84
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• 2010

The aim of this paper is to propose that a category P is encapsulated within a functional layer above the lexical layer, just like vP containing a lexical VP. As is well known, the category P has long been in the obscure domain of syntactic studies: Marantz (2001) and den Dikken (2003), for example, argue that P is a lexical category, but Emonds (1985), Grimshaw (1991), and Baker (2003), maintain that the category P is functional and is a closed category without its own intrinsic meaning. On the other hand, Zwart (2005) argues that it does have some meaning. Following the works of Svenonius (2003, 2006, 2007), and the spirit of Rizzi's (1997) split CP hypothesis, we elaborate and develop Svenonius' idea of split-pP analysis with detailed schematic representations of the novel examples in English, Korean, and Chinese in this paper. Unlike Svenonius, however, this paper incorporates KP into pP-Shell, which is a substantial simplification. Furthermore, Chinese Localizers that have long been considered as Postpositions are now under the category of Prepositions. This proposal renders an X-bar theoretic consistency over the categorical status of Chinese phrasal structures. In short, the present analysis accounts for inconsistency found in English complex preposition phrase (Quirk, et al, 1972, 1985), Chinese circumposition phrase (Ernst 1988, Liu, 2002) and Korean postposition phrase in a unified and consistent manner. Furthermore, by proposing a finer-grained phrasal architecture for the category P, the controversial status of the category subsides within this analysis.

• Acta Via Serica
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• 제3권2호
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• pp.151-160
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• 2018

There is a variety of opinions about the first translation activities within the Turkic Empire. It is widely believed that some Buddhist sutras were translated into the Turkic language in the period of Taspar Qagan (572-581). This theory is based on certain arguments: Some Turks practiced Buddhism, Buddhist monks translated sutras in the center of the Turkic Empire, Taspar brought sutras from China and had them translated, and the monarch of Northern Qi had a sutra translated and sent to Taspar. However, in my opinion, these arguments lack credibility. This article, which is based on primary Chinese sources, will question the likelihood of such translation activities having occurred. Some Chinese records for these claims exist: Da Tang Nei Dian Lu (大唐內典錄) and Xu Gao Seng Chuan (續高僧傳) by the Buddhist monk Jinagupta and the records of Hui Lin in Sui Shu (隋書) and Wen Xian Tong Kao (文獻通考). These are known as "primary sources." Secondary sources, namely contemporary history and language studies, such as those in books and articles, must be based on primary sources. It can be seen that claims relating to the first Turkic translation activities at the time of Taspar are mainly derived from secondary sources, and that the arguments in these secondary sources vary. Sometimes researchers make suppositions on the existence of information that is not referred to in primary sources. However, this is not normal practice. If a researcher relies on unknowns for the evidence of information existing, it can cause false information, ideas and anachronisms to be created. It is important that primary sources, such as the Chinese sources mentioned above, be translated correctly in language and history studies. If only a word is mistranslated, very different results may occur. Mistranslating or misinterpreting a primary source allows conclusions to be reached that are not supported by dissemination of information from primary sources. This can mislead experts and result in information that is not correct being considered as being true. As well as helping to prevent such misinterpretations occurring, another aim of this paper is to question the interpretations of the first Turkic translations in contemporary studies on history and language. The origin of such assessments will be explored and the validity of that information will be examined.

• 융합정보논문지
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• 제12권4호
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• pp.143-157
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• 2022

이 연구의 목적은 마인크래프트의 몰입형 게임 환경인 스퍼드빌을 디자인하여 학습자가 영어를 습득할 수 있도록 효과적으로 돕는 것이다. 마인크래프트를 사용하여 성공적인 학습 경험을 만들기 위해, 본 연구에서는 애자일 모델과 디자인 사고 접근법을 채택했다. 우선 학습자들의 요구를 분석하기 위해 광범위한 문헌 검토를 수행하였으며 이후의 분석 단계에서 수집된 자료를 바탕으로 마인크래프트 월드를 설계하고 개발하였다. 연구자들은 인지주의 학습 모델을 스퍼드빌에 적용하면 학습자가 정보를 처리하는 방법에 대한 더 많은 통찰력을 제공할 수 있고 한편으로 구성주의 및 행동주의 접근 방식을 구현하는 것이 또한 이점이 있다는 것을 알게 되었다. 마인크래프트 게임을 통하여 영어학습의 효과를 향상시킬 수 있으며 게임기반학습이 언어학습에 도움이 될 수 있는 잠재력을 확인할 수 있었다.

• Journal of Audiology & Otology
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• 제23권3호
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• pp.121-128
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• 2019

Background and Objectives: There is a scant evidence on the use of simulations in audiology (especially in Malaysia) for case-history taking, although this technique is widely used for training medical and nursing students. Feedback is one of the important components in simulations training; however, it is unknown if feedback by instructors could influence the simulated patient (SP) training outcome for case-history taking among audiology students. Aim of the present study is to determine whether the SP training with feedback in addition to the standard role-play and seminar training is an effective learning tool for audiology case-history taking. Subjects and Methods: Twenty-six second-year undergraduate audiology students participated. A cross-over study design was used. All students initially attended two hours of seminar and role-play sessions. They were then divided into three types of training, 1) SP training (Group A), 2) SP with feedback (Group B), and 3) a non-additional training group (Group C). After two training sessions, the students changed their types of training to, 1) Group A and C: SP training with feedback, and 2) Group B: non-additional training. All the groups were assessed at three points: 1) pre-test, 2) intermediate, and 3) post-test. The normalized median score differences between and within the respective groups were analysed using non-parametric tests at 95% confidence intervals. Results: Groups with additional SP trainings (with and without feedback) showed a significantly higher normalized gain score than no training group (p<0.05). Conclusions: The SP training (with/without feedback) is a beneficial learning tool for history taking to students in audiology major.

• 대한청각학회지
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• 제23권3호
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• pp.121-128
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• 2019

Background and Objectives: There is a scant evidence on the use of simulations in audiology (especially in Malaysia) for case-history taking, although this technique is widely used for training medical and nursing students. Feedback is one of the important components in simulations training; however, it is unknown if feedback by instructors could influence the simulated patient (SP) training outcome for case-history taking among audiology students. Aim of the present study is to determine whether the SP training with feedback in addition to the standard role-play and seminar training is an effective learning tool for audiology case-history taking. Subjects and Methods: Twenty-six second-year undergraduate audiology students participated. A cross-over study design was used. All students initially attended two hours of seminar and role-play sessions. They were then divided into three types of training, 1) SP training (Group A), 2) SP with feedback (Group B), and 3) a non-additional training group (Group C). After two training sessions, the students changed their types of training to, 1) Group A and C: SP training with feedback, and 2) Group B: non-additional training. All the groups were assessed at three points: 1) pre-test, 2) intermediate, and 3) post-test. The normalized median score differences between and within the respective groups were analysed using non-parametric tests at 95% confidence intervals. Results: Groups with additional SP trainings (with and without feedback) showed a significantly higher normalized gain score than no training group (p<0.05). Conclusions: The SP training (with/without feedback) is a beneficial learning tool for history taking to students in audiology major.

• 정보보호학회논문지
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• 제34권3호
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• pp.451-461
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• 2024

최근 거대 언어 모델을 기반으로 한 다양한 인공지능 챗봇이 출시되고 있다. 챗봇은 대화형 프롬프트를 통해 사용자에게 빠르고 간편하게 정보를 제공할 수 있다는 이점을 가지고 있어서 질의응답, 글쓰기, 프로그래밍 등 다양한 분야에서 활용되고 있다. 그러나 최근에는 챗봇의 취약점을 악용하는 '프롬프트 주입 공격'이 제안되었는데, 이는 챗봇이 기입력된 지시사항을 위반하도록 하는 공격이다. 이와 같은 공격은 거대 언어 모델 내부의 기밀 정보를 유출하거나 또 다른 악성 행위를 유발할 수 있어서 치명적이다. 반면 이들에 대한 취약점 여부가 한국어 프롬프트를 대상으로는 충분히 검증되지 않았다. 따라서 본 논문에서는 널리 사용되는 챗봇인 ChatGPT를 대상으로 악성 한국어 프롬프트를 생성하여 공격을 수행해보고, 이들에 대한 실행 가능성을 분석하고자 한다. 이를 위해 기존에 제안된 프롬프트 주입 공격 기법을 분석하여 악의적인 한국어 프롬프트를 자동으로 생성하는 시스템을 제안하고자 한다. 특히 유해 표현을 유도하는 악성 프롬프트를 중점적으로 생성하였고 이들이 실제 유효함을 보이도록 한다.

• 해양환경안전학회지
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• 제30권1호
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• pp.82-88
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• 2024

현대 해양 산업은 기술적 발전을 통해 신속한 발전을 이루고 있다. 이러한 발전을 주도하는 주요 기술 중 하나는 데이터 처리 기술이며, 이 중 자연어 처리 기법은 사람의 언어를 기계가 이해하고 처리할 수 있도록 하는 기술이다. 본 연구는 자연어 처리 기법을 통해 해양안전심판원의 재결서를 분석하여 이미 재결이 이루어진 선박 충돌사고의 원인 제공 비율을 학습한 후, 새로운 재결서를 입력하면 원인 제공 비율을 예측하는 모델을 개발하고자 하였다. 이 모델은 사고 당시 적용되는 항법과 원인 제공 비율에 영향을 주는 핵심 키워드의 가중치를 이용하여 사고의 원인 제공 비율을 계산하는 방식으로 구성하였다. 이 연구는 이러한 방식을 통해 제작한 모델의 정확도를 분석하고, 모델의 실무 적용 가능성을 검토함과 동시에 충돌사고 재발 방지 및 해양사고 당사자들의 분쟁 해결에 기여할 것으로 기대한다.

• Journal of Multimedia Information System
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• 제5권3호
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.