• Industry Promotion Research
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• v.3 no.2
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• pp.63-78
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• 2018

This study used survey research method to identify factors affecting suicidal ideation in adolescents. The results of this study are as follows. First, it is necessary to narrow the psychological distance between the parents and the adolescents, to make efforts in each family to be more harmonious within the family, and to reduce consciously the physical and verbal violence which is sometimes unintentionally applied between the parents. Second, when adolescents attempt suicide, counseling agencies in schools, educational institutions, and local communities should be able to respond effectively to adolescent crisis situations, and follow-up measures such as suicide prevention education and suicide attitude education must be conducted Efforts should be made to reduce juvenile delinquent suicide and impulsive suicidal thoughts. Third, when developing adolescent suicide prevention and related programs, differentiated programs and suicide prevention education should be tried. Fourth, I think that it is necessary to prevent the suicidal thoughts of adolescents by early detection and intervention of high - depression adolescents by establishing a system that can be applied to adolescents out of school.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.39-54
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• 2018

Recently, discussions for the eradication of illegal shooting have been carried out in a socially-oriented way. The government has established comprehensive measures to eradicate cyber sexual violence crimes such as illegal shooting. Although the social interest in illegal shooting has increased, the illegal film shooting case is evolving more and more due to the development of information and communication technology. Applications that can hide confused videos are constantly circulating around the market and community sites. As a result, field investigators and professional analysts are experiencing difficulties in collecting and analyzing evidence. In this paper, we propose an evidence collection and analysis framework for illegal shooting cases in order to give practical help to illegal shooting investigation. We also proposed a system that can detect hidden applications, which is one of the main obstacles in evidence collection and analysis. We developed a detection tool to evaluate the effectiveness of the proposed system and confirmed the feasibility and scalability of the system through experiments using commercially available concealed apps.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.91-93
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• 2013

성폭력은 강간, 강제 추행, 성희롱, 도촬 등 상대방의 의사에 반하여 성적 자기 결정권을 침해하는 모든 신체적 정신적 폭력을 말한다. 남성이 가해자이고 여성이 피해자인 경우가 많은 범죄 행위 중 하나이다. 그 중에서 성폭력의 하나인 성추행은 강제추행을 뜻한다. 강제추행이 성희롱과 다른 것은 '폭행이나 협박'을 수단으로 '추행'하는 것이다. 성추행은 성욕의 자극, 흥분을 목적으로 일반인의 성적 수치, 혐오의 감정을 느끼게 하는 일체의 행위(키스를 하거나 상대의 성기를 만지는 행위 등)로, 강제추행은 이러한 추행 행위 시 폭행 또는 협박과 같은 강제력이 사용되는 경우를 말한다. 본 논문에서는 엘리베이터 내에서 이러한 여성의 성 추행 사건을 컬러 히스토그램을 통하여 추출하도록 한다.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.115-119
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• 2020

Recently, CCTV installations are rapidly increasing in the public and private sectors to prevent various crimes. In accordance with the increasing number of CCTVs, video-based abnormal behavior detection in control systems is one of the key technologies for safety. This is because it is difficult for the surveillance personnel who control multiple CCTVs to manually monitor all abnormal behaviors in the video. In order to solve this problem, research to recognize abnormal behavior using deep learning is being actively conducted. In this paper, we propose a model for detecting abnormal behavior based on the deep learning model that is currently widely used. Based on the abnormal behavior video data provided by AI Hub, we performed a comparative experiment to detect anomalous behavior through violence learning and fainting in videos using 2D CNN-LSTM, 3D CNN, and I3D models. We hope that the experimental results of this abnormal behavior learning model will be helpful in developing intelligent CCTV.

• Annual Conference of KIPS
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• 2023.05a
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• pp.570-571
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• 2023

최근 선정적이고 폭력적인 뉴스 기사 제목의 여과 없는 노출로 인하여 유해한 언어 접촉이 빈번히 이루어지고 있다. 자극적인 단어에 지속적으로 노출되는 것은 인지 능력에 부정적 영향을 주는 것으로 알려져 있다. 따라서 이를 사전에 판별하여 정보를 수용하는 것이 필요하다. 본 논문에서는 KoBERT를 기반으로 한국어 뉴스 기사 제목에서 선정성과 폭력성을 검출하고자 한다. 학습을 위한 뉴스 기사 제목들은 인터넷에서 무작위로 총 9,500개의 데이터를 크롤링 하여 수집하였고, 모델의 말단에 NLNet을 추가하여 문장 전체의 관계를 학습했다. 그 결과 선정성 및 폭력성을 약 89%의 정확도로 검출하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.703-704
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• 2023

학교폭력은 교육 환경에서 심각한 문제이다. 피해자에게 심리적 고통과 육체적 상해를 입히고 학교 내 안전과 안정성을 위협한다. 이에 많은 교육기관과 정부 기관이 학교폭력 예방과 대처를 위한 다양한 방안을 제시하고 있지만, 여전히 어려운 문제이다. 최근에는 인공지능 기술을 활용하여 학교폭력 방지와 대처에 관한 연구가 이루어지고 있다. 본 연구에서는 YOLOv5(You Only Look Once version 5) 딥러닝 알고리즘을 활용하여 학교 내부에서 발생하는 폭력 행위를 실시간으로 탐지하는 모델을 제안한다. 이 모델은 CCTV와 같은 영상 데이터를 입력으로 받아들여 학교 내부에서 발생하는 폭력 행위를 실시간으로 식별하는 것을 목표로 한다.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.1
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• pp.31-60
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• 2023

Purpose: This study explored the influencing factors on suicide-related behaviors (ideation, plans, and attempts) focusing on mental health problems (anxiety, depression, and loneliness) among Korean adolescents. Methods: A secondary analysis was conducted with data from the 16th Korean Youth Health Behavior Survey collected from in 2020 by the Korea Centers for Disease Control and Prevention. Chi-square tests and multivariate logistic regression analyses were performed. Results: After the adjustment of demographic characteristics and health risk behaviors, the influences of mental health problems on suicidal ideation, plans, and attempts showed the anxiety odds ratio (OR) for severe anxiety vs. minimal (OR 4.65, 4.67, and 3.75), depression (OR 4.27, 3.69, and 4.49), loneliness (OR 2.18, 1.96, and 1.96). Health risk behaviors (violence experience, drug use, stress, smoking, and drinking alcohol) and demographic variables (gender, school record, and socioeconomic status) were also significantly associated with suicide-related behaviors. Conclusion: Anxiety, depression, and loneliness were strong predictors of suicide-related behaviors. Early detection of suicide risks through screening for comprehensive mental health problems was recommended. Suicide prevention that considers the risk factors, including mental health problems and other risk factors, needs to be developed and implemented to reduce suicide risks among adolescents.

• Annual Conference of KIPS
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• 2020.05a
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• pp.442-445
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• 2020

인터넷 및 IT 기술의 발전과 더불어 미디어산업에도 큰 변화가 일어나고 있다. TV 를 대신하여 스트리밍 서비스를 이용하는 사람들이 늘고 있으며 SNS 를 활용하여 서로의 경험을 간접적으로 공유하는 형태의 새로운 문화 컨텐츠가 자리잡아가고 있다. 하지만 이러한 컨텐츠를 소비하는 주요 계층 중에는 초중고 학생들도 포함되어 있다. 인터넷 혹은 SNS 에서 소비되는 컨텐츠들을 관리 감독하는 컨트롤 타워가 부족하거나 전무하기 때문에 폭력, 음주, 흡연 등 사회적으로 악영향을 줄 수 있는 영상 또는 사진이 무분별하게 생산되어 청소년들에 의해 소비되고 있으며 더 나아가 이것이 사회적 문제로까지 대두되고 있다. 이러한 문제를 해결하기 위해 인공지능 기술을 활용한 여러 다양한 감시 시스템 개발을 위한 연구가 한창이다. 본 연구에서는 SNS 및 스트리밍 서비스에서 제공되는 영상 및 사진을 Pose Estimation 및 표정 인식 기술을 활용하여 폭력을 자동적으로 감지할 수 있는 폭력 감지 시스템을 개발하는데 그 목적이 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2427-2432
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• 2014

Color-$X^2$ is used as a method for scene change detection. It extracts a violent scene in an elevator and then could be used for real-time surveillance of criminal acts. The scene could be also used to secure after-discovered evidences and to prove analysis processes. Video Forensic is defined as a research on various methods to efficiently analyze evidences upon crime-related visual images in the field of digital forensic. The method to use differences of color-histogram detects the difference values of histogram for RGB color from two frames respectively. Our paper uses Color-$X^2$ histogram that is composed of merits of color histogram and ones of $X^2$ histogram, in order to efficiently extract violent scenes in elevator. Also, we use a threshold so as to find out key frame, by use of existing Color-$X^2$ histogram. To increase the probability that discerns whether a real violent scene or not, we take advantage of statistical judgments with 20 sample visual images.