• English Language & Literature Teaching
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• v.15 no.4
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• pp.365-382
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• 2009

This study aims to examine the reading materials of high school English textbooks to propose the integration of the literary texts into reading materials in the classroom for development of communicative competence. Five kinds of high school English textbooks were critically examined in terms of three factors -limited text types, deficit of emotional adjectives and non-authenticity- selected by the author as characteristics of non-communicative language teaching materials. With regard to text types, more than half of the reading materials were expository and simple narratives. This imbalance of text types led materials to the deficit of emotional vocabulary. These factors seem to be closely related to the issue of authenticity of reading materials. Compared to the authentic texts, fabricated texts are likely to make reading vapid and boring task. On the basis of these results, some pedagogical suggestions are made.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.864-865
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• 2015

웹페이지와 같은 스크린 콘텐츠는 카메라로부터 획득할 수 있는 자연영상과 달리 텍스트, 로고, 아이콘 및 하위 영상과 같은 여러 가지 요소들을 포함하고 있고, 각 요소들은 서로 다른 형식의 정보를 사용자에게 전달한다. 본 논문에서는 윈도우 영상을 지역적인 특성에 따라 다수의 블록으로 분할한 후, 분할된 각 영역을 배경, 텍스트, 하위영상으로 분류하였고, 기계학습 기반의 알고리즘이 하위 영상 검출에도 좋은 접근법이 될 수 있음을 증명하기 위해 AdaBoost를 이용하였다. 실험결과로부터 93.4%의 검출률, 13%의 거짓 긍정률을 보임으로서, 제안방법이 효과적임을 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.526-527
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• 2023

Speech emotion recognition(SER) is one of the interesting topics in the machine learning field. By developing multi-modal speech emotion recognition system, we can get numerous benefits. This paper explain about fusing BERT as the text recognizer and CNN as the speech recognizer to built a multi-modal SER system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.409-410
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• 2019

본 논문에서는 국내 갑상선암의 연구 동향을 파악하기 위해 텍스트 중심의 접근법을 제안한다. 국내 갑상선암은 2000년대에 들어서며 발생이 급증하여 과잉진단의 논란을 불러일으켰으나, 다양한 분야의 자정 노력으로 수술 환자수가 크게 줄었다. 본 연구에서는 텍스트 마이닝 기술을 사용하여 디비피아에 등록되어 있는 갑상선암 관련 논문의 키워드와 초록을 수집하여 분석하였다. 1980년대는 대부분의 사례보고가 있었고 1990년대에 들어서면서 검진을 통한 조기 진단의 내용이 자주 나타났다. 2000년대에는 여러 장비들을 활용한 검사방법과 미세한 암의 발견에 대한 논의가 증가하였음을 확인 할 수 있었다. 2010년대에 들어서는 환자의 삶의 질에 대한 연구가 많이 이루어졌다. 지난 수십 년 동안 갑상선 암 연구 주제에 대해 뚜렷한 변화가 나타났으며, 향후 연구의 기초자료로 활용될 수 있으리라 기대된다.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.456-466
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• 2014

This is a study of George Lindbeck's postliberalism that views religion as a cultural-linguistic approach. Knowing that the conceptual-propositional approach of the traditional Christian theology and the experiential-expressive approach of liberalism cannot be a solution for the post-modem religious phenomenon, George Lindbeck proposes an alternative. He proposes a cultural-linguistic approach to overcome the previous approaches. The first insight of Lindbeck's postliberalism is to understand religion as culture or language, because human beings become acquainted with a religion as they learn a language. The second insight comes out of the first, to understand doctrine as grammar. If we understand religion and doctrine this way the troubles and conflicts among religions will be resolved naturally, because each religion can be interpreted in its own system just as a language cannot be said to be good or bad, right or wrong. This approach makes several contributions as follows: it promotes a dialogue among religions, it emphasizes practice; and it preserves the Bible as an authoritative theological text. However it also brings many limitations as follows: it emphasizes the church's interpretation rather than the text's own interpretation; it views the truth simply as coherence; it promotes radical relativism and elitism; and through theological eschatology he makes his theory return to a propositionalism. Accordingly, the researcher concludes that Lindbeck's cultural-linguistic theory of religion is not an alternative that overcomes the limitations of theological conservativism and liberalism.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.59-66
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• 2005

The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

• The Southeast Asian review
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• v.28 no.3
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• pp.75-110
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• 2018

This study is to figure out the Filipino cultural identity by analyzing the image of the Philippine comfort woman statue, which was created as a representation of memories of the Filipino comfort women during the World War II. As a new approach to the field of area study, this study introduced the concept of 'intertextuality', which is a method of understanding texts in the field of literature. Since the comfort woman statue represents the grieved memories of the comfort women during the international war time, the analysis of the image was focused on 'femininity' and 'nationalism'. As for comparison, the Korean comfort woman statue, the Statue of Peace, was taken into the analysis. Upon analyzing, it can be seen that Filipino perception of femininity emphasizes 'beauty' rather than 'purity' that expressed in the Statue of Peace. And the Philippine nationalism expressed through the comfort woman statue can find 'elitist and inclusive' characteristics, unlike the 'popular and resisting' characteristics of Korean.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.187-198
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• 2017

In this study, we analyzed the accessibility of open platform Android mobile banking applications, based on Korean mobile application accessibility KS standard, Section 508 technical standard of Rehabilitation Act, and European BBC guidelines. Experimental result showed that there are no mobile banking applications of 8 commercial banks in Korea that satisfy all guidelines of three standards. Typical violations included missing alternative text, keyboard focus violations, control size and spacing non-compliance, and low contrast ratio. These violations are fatal in that they make the accessibility of the blind, the disabled and the low vision and the elderly impossible. The reason that mobile banking applications do not comply with accessibility is that mobile application developers and providers have low awareness of accessibility and do not know how to implement accessibility properly. Comparing Korea mobile application accessibility guidelines with the revised standard of the Section 508 of Rehabilitation Act and the BBC standard, many guidelines are missing. Also, evaluation criteria are ambiguous and abstract, making it difficult for developers to refer specifically. Therefore, improving mobile application accessibility requires developer and government efforts and complementation of standards.

• Smart Media Journal
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• v.11 no.10
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• pp.54-64
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• 2022

A big data-driven digital transformation is defined as a process that aims to innovate companies by triggering significant changes to their capabilities and designs through the use of big data and various technologies. For a successful big data-driven digital transformation, reviewing related literature, which enhances the understanding of research statuses and the identification of key research topics and relationships among key topics, is necessary. However, understanding and describing literature is challenging, considering its volume and variety. Establishing a common ground for central concepts is essential for science. To clarify key research topics on the big data-driven digital transformation, we carry out a comprehensive literature review by performing text mining of 439 articles. Text mining is applied to learn and identify specific topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview. A total of 10 key research topics and relationships among the topics are identified. This study contributes to clarifying a systematized view of dispersed studies on big data-driven digital transformation across multiple disciplines and encourages further academic discussions and industrial transformation.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.1-12
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• 2024

In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.