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Vulnerability Analysis for Groundwater Level Management in the Midstream of the Nakdong River (낙동강 중류 지역 지하수위 관리 취약성 분석)

  • Lee, Jae-Beom;Yang, Jeong-Seok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.138-138
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    • 2017
  • 가뭄, 집중호우와 같은 자연적인 요인과 불투수면적의 증가, 각종 용수로서의 지하수 이용 증가, 지하구조물 공사 등과 같은 인위적인 요인에 의한 지하수위 하강이 이슈화 되고 있다. 지하수 위의 하강은 지하수 고갈 같은 1차적 피해뿐만 아니라 생태계 교란, 농작물 피해, 지반 침하, 싱크홀 등의 2차 피해를 야기한다. 이에 따라 지하수위 시계열 자료를 이용하여 지하수위 관리 취약성에 대한 분석을 실시하였다. 연구지역으로 낙동강 중류에 위치한 상주, 대구, 밀양 지역으로 선택하였다. 자료 수집으로 국가지하수정보센터(www.gims.go.kr)에서 제공하는 국가지하수관측망 관측정 중 자료길이가 11개년 이상인 상주, 대구, 밀양의 지하수위 관측소의 일단위 지하수위 자료와 지하수이용량 자료를 수집하였다. 관측소 인근의 하천수위 자료는 국가수자원관리종합정보시스템(www.wamis.go.kr)에서 수집하였으며, 관측소 인근의 강수자료는 기상청(www.kma.go.kr)에서 해당 지역 관측소의 일단위 강수 자료를 수집하였다. 연구지역의 지하수 함양 자료는 국가통계포털(www.kosis.kr)에서 수집하였다. 수집한 일 단위 수문 자료를 이용하여 각 관측소의 연평균, 갈수기, 풍수기에 대해서 연구지역의 지하수위 관리 취약성 분석을 실시했고, 자료 분석 시 충적층 지하수위 자료는 인근 수계에 따른 변동이 크기 때문에 암반층 지하수위 자료에 대해서 분석을 실시하였다. 분석한 결과는 표준화 과정을 거쳐 지수로 산정하였고, 산정된 지수를 통해 연구지역 내 지하수위 관리 취약성 분석을 실시하였다. 본 연구를 전국단위 국가지하수관측망으로 적용하게 되면 지하수 개발 및 관리 정책 수립에 있어 큰 도움이 될 것으로 생각된다.

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Bias & Hate Speech Detection Using Deep Learning: Multi-channel CNN Modeling with Attention (딥러닝 기술을 활용한 차별 및 혐오 표현 탐지 : 어텐션 기반 다중 채널 CNN 모델링)

  • Lee, Wonseok;Lee, Hyunsang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1595-1603
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    • 2020
  • Online defamation incidents such as Internet news comments on portal sites, SNS, and community sites are increasing in recent years. Bias and hate expressions threaten online service users in various forms, such as invasion of privacy and personal attacks, and defamation issues. In the past few years, academia and industry have been approaching in various ways to solve this problem The purpose of this study is to build a dataset and experiment with deep learning classification modeling for detecting various bias expressions as well as hate expressions. The dataset was annotated 7 labels that 10 personnel cross-checked. In this study, each of the 7 classes in a dataset of about 137,111 Korean internet news comments is binary classified and analyzed through deep learning techniques. The Proposed technique used in this study is multi-channel CNN model with attention. As a result of the experiment, the weighted average f1 score was 70.32% of performance.

The Comparison Between the Comments and the Replies on Korean President Election News: using Topic Modeling (대선 관련 인터넷 뉴스의 댓글과 대댓글 간 비교를 통해 살펴본 온라인 토론의 진행 가능성)

  • Lee, Jung
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.33-55
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    • 2022
  • This study analyzed the comments and the replies on internet news related to the presidential election in order to verify whether online discussions are properly conducted. According to Habermas' public sphere theory, discussions is an effort among participants to reach a social consensus through the deliberations that are based on open communications. We propose that if such discussions properly take place through the act of writing in the Internet space, the comments and the replies will show a certain difference in terms of the structure and the content. To validate, this study analyzed more than 40,000 comments collected from Daum News portal site in Korea. The topic of the related news was the presidential election, because it is a topic of which people are highly interested in and that comments are actively running. The result of the t-test and topic modeling result show that all the hypotheses were supported thus we conclude that online discussions properly took places. This study also showed that online comments are not chaotic remarks that relieve people's stresses, but rather an outcome of the deliberation processes moving towards a social consensus.

A Study on the Characteristics and Progress of New Voice Phishing Based on Psychological Descriptions (심리적 기재를 기반으로 한 신종 보이스피싱의 특성 및 진행과정에 관한 연구)

  • SeiYouen Oh;HyeJin Song
    • Journal of the Society of Disaster Information
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    • v.19 no.3
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    • pp.510-518
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    • 2023
  • Purpose: This study compares and analyzes the characteristics and progress of existing voice phishing and new voice phishing to present a basic policy plan to prepare countermeasures against new voice phishing based on psychological descriptions. Method: The criminal progress and characteristics of the two were compared and analyzed through damage cases on various portal sites centered on voice phishing crime scenarios. Result: As a result of analyzing the progress of the third stage of new voice phishing, the scenario of new voice phishing that can deceive victims was written more carefully and the scope of the crime was expanded. In the crime execution stage, the victim was socially isolated, reducing the victim's judgment ability, making it more difficult for investigative agencies to investigate, and in the final stage, the continuity and expansion of criminal damage such as extortion of money and valuables are shown. Conclusion: There were differences in the target and scope of the crime and the method of the crime strategy between the two, and the possibility of damage is much greater, so a more efficient response strategy should be prepared.

A Study on the Perception of Artificial Intelligence Literacy and Artificial Intelligence Convergence Education Using Text Mining Analysis Techniques (텍스트 마이닝 분석기법을 활용한 인공지능 리터러시 및 인공지능 융합 교육에 관한 인식 연구)

  • Hyeok Yun;Jeongrang Kim
    • Journal of The Korean Association of Information Education
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    • v.26 no.6
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    • pp.553-566
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    • 2022
  • This study collects social data and academic research data from portal sites and RISS, and analyzes TF-IDF, N-Gram, semantic network analysis, and CONCOR analysis to analyze the social awareness and current aspects of 'AI Literacy' and 'AI Convergence Education'. Through this, we tried to understand the social awareness aspect and the current situation, and to suggest implications and directions. In the social data, the collection of 'AI Convergence Education' was more than twice that of 'AI Literacy', indicating that awareness of 'AI Literacy' was relatively low. In 'AI Literacy', the keyword 'human' in social data showed no cluster to which it belonged, indicating a lack of philosophical interest in and awareness of humanities and AI. In addition, the keyword 'Ministry of Education' showed high frequency, importance, and centrality of connection only in the social data of 'AI convergence education', confirming that 'AI convergence education' is closely related to government policy.

A Study on the Presidential Digital Archive Platform (대통령기록디지털아카이브 플랫폼 연구)

  • Kim, Seoyeon;Im, Seolhwa;Kim, Gyuseok;Song, Minji;Wi, Sooa;Yang, InHo
    • The Korean Journal of Archival Studies
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    • no.76
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    • pp.61-117
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    • 2023
  • This study raises the need to establish a 'Presidential Digital Archive Platform' that actively shares and opens related information and data by linking and integrating the presidential knowledge infrastructure. The Presidential Digital Archive Platform can promote the quality and value of presidential records as a "Governance Platform" where "Presidential Archives", "Presidential Archives-related Institutions" and "users" can interact through presidential records. And it will provide an opportunity to create a new paradigm. For this purpose, 'Presidential archives portal analysis' and 'Presidential Archives-related Institutions analysis' will be conducted to identify improvements and requirements when establishing the Presidential Digital Archive Platform. In addition to deriving implications through 'Digital Archive Platform case analysis' at home and abroad, measures to strengthen presidential archival reference services were discussed. Finally, based on the results, a step-by-step implementation strategy for platform construction was presented.

Detection of Incivility based on Attention-embedding and multi-channel CNN (어텐션임베딩과 다채널 CNN 기반 반시민성 검출 알고리즘)

  • Park, Youn-Jung;Lee, Se-Young;Keum, Hee-Jo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.12
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    • pp.1880-1889
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    • 2022
  • The online portal platform provides online news with online comments, but the anonymity of comments causes incivility, and online comments are considered social problems. While there are many foreign language-based incivility detection studies, in-depth research is not being conducted in Korea since there has not been implemented Korean language dataset which is labeled detailed criteria of incivility. In this study, the incivility notation of comments was conducted in a total of 13 items, uncivil words were summarized. Furthermore, Attention algorithm was applied to each comment and summary to extract embedding vectors. 2-d CNN followed at the end to detect incivility in given data. As a result, we showed that the proposed algorithm is useful for anti-citizen detection such as name-calling and offensive tones. This study is expected to contribute to the formation of a healthy online comment culture by detecting uncivil comments which hinder democratic discourse.

Estimation of Occurrence Probability of Socioeconomic Damage Caused by Meteorological Drought Using Categorical Data Analysis (범주형 자료 분석을 활용한 사회경제적 가뭄 피해 발생확률 산정 : 충청북도의 적용사례를 중심으로)

  • Yu, Ji Soo;Yoo, Jiyoung;Kim, Min-ji;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.348-348
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    • 2021
  • 가뭄 연구의 궁극적 목표는 가뭄 발생의 메커니즘에 대한 이해를 높이고, 예측기술을 향상시켜 선제적 대응이 가능하도록 하는 것이다. 일반적으로 가뭄분석에 활용되는 가뭄지표는 연속형 변수로 간주하여 확률모형을 구축하지만, 가뭄상태와 가뭄피해 자료는 순서형 및 이산형 변수이므로 범주형 자료 분석 기법을 적용하는 것이 더 적절하다. 따라서 본 연구에서는 기상학적 가뭄과 피해발생 사이의 관계를 규명하기 위해 범주형 자료 분석 방법 중 로그선형(log-linear) 모형과 로지스틱(logistic) 회귀모형을 활용하였다. 가뭄피해 예측을 위한 가뭄 피해 정보를 수집하는 것은 매우 어려운 일이다. 가뭄의 영향으로 인해 발생할 수 있는 피해의 종류가 다양하며, 여러 분야의 이해관계자가 받아들이는 가뭄의 피해 양상이 다르기 때문이다. 본 연구에서는 국가가뭄정보포털(drought.go.kr)에서 충청북도의 가뭄피해현황 자료를 수집하였다. 30년(1991~2020년)동안 238개 읍면동 중 34개 행정구역에서 총 272건의 가뭄피해가 발생한 것으로 확인되었다. 표준강수지수(SPI)를 이용하여 분석된 지역별 연평균 가뭄발생횟수는 약 8.44회이며, 가뭄이 가장 많이 발생한 해는 2001년(평균 가뭄발생 18.7회)이었다. 강수의 부족으로 인해 발생하는 기상학적 가뭄이 사회경제적 피해를 야기하는 수문학적 가뭄으로 전이되기까지 몇 주에서 몇 달까지 시간이 소요된다. 이러한 관계를 파악하기 위해 가뭄피해 발생 여부를 예측변수, 가뭄피해 발생 이전의 가뭄상태를 설명변수로 설정하여 기상학적 가뭄 발생에 따른 가뭄피해 발생 확률을 산정하였다. 그 결과 가뭄피해 발생 당시의 가뭄상태보다 그 이전에 연속된 가뭄상태가 있을 경우 가뭄피해 발생 확률이 약 2.5배 상승하는 것으로 나타났다.

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Social Perception of Disaster Safety Education for Migrant Youth based on Big Data (빅데이터를 통해 바라본 이주배경청소년 재난안전교육에 대한 사회적 인식)

  • Ying Jin;Sang Jeong
    • Journal of the Society of Disaster Information
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    • v.20 no.2
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    • pp.462-469
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    • 2024
  • Purpose: This study aims to analyze data on disaster safety education for migrant youth and to examine the corresponding social perceptions. Method: Data on disaster safety education for migrant youth were collected and analyzed using Textom and Ucinet. The data used in the study were searched on portal websites from 2016 to 2023 using the keywords 'migrant youth+ disaster + safety education'. Result: The analysis results showed that 'education (306)' had the highest frequency, followed by 'safety (287)', 'school (97)', 'society (85)', and 'support (77)'. The keyword with the high degree of centrality, closeness centrality, and betweenness centrality were 'education', 'safety' and 'society'. 'Family' ranked higher in betweenness centrality than the rankings of frequency analysis, degree centrality and closeness centrality, indicating that 'family' plays a significant role as a mediator in the network of disaster safety education for migrant youth. Conclusion: By examining social awareness about disaster safety education for migrant youth, the findings will be used to develop policies and strategies for disaster safety education that consider the unique vulnerabilities of migrant youth in disaster situations.

Improving Government Website Chatbot UX Based on User Journey Map: A Focus on NTIS Chatbot ND (사용자 여정 지도를 기준으로 정부 웹사이트 챗봇 UX 개선: NTIS의 챗봇 ND 를 중심으로)

  • Haeyoon Lee;Inyoung Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.4
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    • pp.601-606
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    • 2024
  • Today, governments are evolving into digital governments that actively leverage digital technologies to promote national development. Government websites play a crucial role as key elements in reshaping the interaction between individuals and the government. Within this context, government website chatbots play an important role in facilitating citizens' easy access to information. However, the chatbot ND on the National R&D Knowledge Information Portal (NTIS) exhibits low usage rates. This study proposes a framework based on user journey mapping to address the usability issues of chatbot ND. By delineating the user journey into pre-usage, in-usage, and post-usage stages, the study aims to identify points of inconvenience experienced by users at each stage and provide enhanced user experiences.