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1. Poly(p-phenylene)-based membranes with cerium for chemically durable polymer electrolyte fuel cell membranes

Author

Abdul Kodir, Seunghee Woo, Sang-Hun Shin, Soonyong So, Duk Man Yu, Hyejin Lee, Dongwon Shin, Jang Yong Lee, Seok-Hee Park, and Byungchan Bae

Subjects
Hydrocarbon membrane, Durability, Fuel cells, Antioxidant, Cerium, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

A poly(p-phenylene)-based multiblock polymer is developed with an oligomeric chain extender and cerium (CE-sPP-PPES + Ce3+) to realize better performance and durability in proton exchange membrane fuel cells. The membrane performance is evaluated in single cells at 80 °C and at 100% and 50% relative humidity (RH). The accelerated stability test is conducted 90 °C and 30% RH, during which linear sweep voltammetry and hydrogen permeation detection are monitored periodically. Results demonstrate that the proton conductivity of the pristine hydrocarbon membranes is superior to that of PFSA membranes, and the hydrogen crossover is significantly lower. In addition, a composite membrane containing cerium performs similarly to a pristine membrane, particularly at low RH levels. Adding cerium to CE-sPP-PPES + Ce3+ membranes improves their chemical durability significantly, with an open circuit voltage decay rate of only 89 μV/h for 1000 h. The hydrogen crossover is maintained across accelerated stability tests, as confirmed by hydrogen detection and crossover current density. The short-circuit resistance indicates that membrane thinning is less likely to occur. Collectively, these results demonstrate that a hydrocarbon membrane with cerium is a potential alternative for fuel cell applications.

Published
2024
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3. HyperCLOVA X Technical Report

Author

Yoo, Kang Min, Han, Jaegeun, In, Sookyo, Jeon, Heewon, Jeong, Jisu, Kang, Jaewook, Kim, Hyunwook, Kim, Kyung-Min, Kim, Munhyong, Kim, Sungju, Kwak, Donghyun, Kwak, Hanock, Kwon, Se Jung, Lee, Bado, Lee, Dongsoo, Lee, Gichang, Lee, Jooho, Park, Baeseong, Shin, Seongjin, Yu, Joonsang, Baek, Seolki, Byeon, Sumin, Cho, Eungsup, Choe, Dooseok, Han, Jeesung, Jin, Youngkyun, Jun, Hyein, Jung, Jaeseung, Kim, Chanwoong, Kim, Jinhong, Kim, Jinuk, Lee, Dokyeong, Park, Dongwook, Sohn, Jeong Min, Han, Sujung, Heo, Jiae, Hong, Sungju, Jeon, Mina, Jung, Hyunhoon, Jung, Jungeun, Jung, Wangkyo, Kim, Chungjoon, Kim, Hyeri, Kim, Jonghyun, Kim, Min Young, Lee, Soeun, Park, Joonhee, Shin, Jieun, Yang, Sojin, Yoon, Jungsoon, Lee, Hwaran, Bae, Sanghwan, Cha, Jeehwan, Gylleus, Karl, Ham, Donghoon, Hong, Mihak, Hong, Youngki, Hong, Yunki, Jang, Dahyun, Jeon, Hyojun, Jeon, Yujin, Jeong, Yeji, Ji, Myunggeun, Jin, Yeguk, Jo, Chansong, Joo, Shinyoung, Jung, Seunghwan, Kim, Adrian Jungmyung, Kim, Byoung Hoon, Kim, Hyomin, Kim, Jungwhan, Kim, Minkyoung, Kim, Minseung, Kim, Sungdong, Kim, Yonghee, Kim, Youngjun, Kim, Youngkwan, Ko, Donghyeon, Lee, Dughyun, Lee, Ha Young, Lee, Jaehong, Lee, Jieun, Lee, Jonghyun, Lee, Jongjin, Lee, Min Young, Lee, Yehbin, Min, Taehong, Min, Yuri, Moon, Kiyoon, Oh, Hyangnam, Park, Jaesun, Park, Kyuyon, Park, Younghun, Seo, Hanbae, Seo, Seunghyun, Sim, Mihyun, Son, Gyubin, Yeo, Matt, Yeom, Kyung Hoon, Yoo, Wonjoon, You, Myungin, Ahn, Doheon, Ahn, Homin, Ahn, Joohee, Ahn, Seongmin, An, Chanwoo, An, Hyeryun, An, Junho, An, Sang-Min, Byun, Boram, Byun, Eunbin, Cha, Jongho, Chang, Minji, Chang, Seunggyu, Cho, Haesong, Cho, Youngdo, Choi, Dalnim, Choi, Daseul, Choi, Hyoseok, Choi, Minseong, Choi, Sangho, Choi, Seongjae, Choi, Wooyong, Chun, Sewhan, Go, Dong Young, Ham, Chiheon, Han, Danbi, Han, Jaemin, Hong, Moonyoung, Hong, Sung Bum, Hwang, Dong-Hyun, Hwang, Seongchan, Im, Jinbae, Jang, Hyuk Jin, Jang, Jaehyung, Jang, Jaeni, Jang, Sihyeon, Jang, Sungwon, Jeon, Joonha, Jeong, Daun, Jeong, Joonhyun, Jeong, Kyeongseok, Jeong, Mini, Jin, Sol, Jo, Hanbyeol, Jo, Hanju, Jo, Minjung, Jung, Chaeyoon, Jung, Hyungsik, Jung, Jaeuk, Jung, Ju Hwan, Jung, Kwangsun, Jung, Seungjae, Ka, Soonwon, Kang, Donghan, Kang, Soyoung, Kil, Taeho, Kim, Areum, Kim, Beomyoung, Kim, Byeongwook, Kim, Daehee, Kim, Dong-Gyun, Kim, Donggook, Kim, Donghyun, Kim, Euna, Kim, Eunchul, Kim, Geewook, Kim, Gyu Ri, Kim, Hanbyul, Kim, Heesu, Kim, Isaac, Kim, Jeonghoon, Kim, Jihye, Kim, Joonghoon, Kim, Minjae, Kim, Minsub, Kim, Pil Hwan, Kim, Sammy, Kim, Seokhun, Kim, Seonghyeon, Kim, Soojin, Kim, Soong, Kim, Soyoon, Kim, Sunyoung, Kim, Taeho, Kim, Wonho, Kim, Yoonsik, Kim, You Jin, Kim, Yuri, Kwon, Beomseok, Kwon, Ohsung, Kwon, Yoo-Hwan, Lee, Anna, Lee, Byungwook, Lee, Changho, Lee, Daun, Lee, Dongjae, Lee, Ha-Ram, Lee, Hodong, Lee, Hwiyeong, Lee, Hyunmi, Lee, Injae, Lee, Jaeung, Lee, Jeongsang, Lee, Jisoo, Lee, Jongsoo, Lee, Joongjae, Lee, Juhan, Lee, Jung Hyun, Lee, Junghoon, Lee, Junwoo, Lee, Se Yun, Lee, Sujin, Lee, Sungjae, Lee, Sungwoo, Lee, Wonjae, Lee, Zoo Hyun, Lim, Jong Kun, Lim, Kun, Lim, Taemin, Na, Nuri, Nam, Jeongyeon, Nam, Kyeong-Min, Noh, Yeonseog, Oh, Biro, Oh, Jung-Sik, Oh, Solgil, Oh, Yeontaek, Park, Boyoun, Park, Cheonbok, Park, Dongju, Park, Hyeonjin, Park, Hyun Tae, Park, Hyunjung, Park, Jihye, Park, Jooseok, Park, Junghwan, Park, Jungsoo, Park, Miru, Park, Sang Hee, Park, Seunghyun, Park, Soyoung, Park, Taerim, Park, Wonkyeong, Ryu, Hyunjoon, Ryu, Jeonghun, Ryu, Nahyeon, Seo, Soonshin, Seo, Suk Min, Shim, Yoonjeong, Shin, Kyuyong, Shin, Wonkwang, Sim, Hyun, Sim, Woongseob, Soh, Hyejin, Son, Bokyong, Son, Hyunjun, Son, Seulah, Song, Chi-Yun, Song, Chiyoung, Song, Ka Yeon, Song, Minchul, Song, Seungmin, Wang, Jisung, Yeo, Yonggoo, Yi, Myeong Yeon, Yim, Moon Bin, Yoo, Taehwan, Yoo, Youngjoon, Yoon, Sungmin, Yoon, Young Jin, Yu, Hangyeol, Yu, Ui Seon, Zuo, Xingdong, Bae, Jeongin, Bae, Joungeun, Cho, Hyunsoo, Cho, Seonghyun, Cho, Yongjin, Choi, Taekyoon, Choi, Yera, Chung, Jiwan, Han, Zhenghui, Heo, Byeongho, Hong, Euisuk, Hwang, Taebaek, Im, Seonyeol, Jegal, Sumin, Jeon, Sumin, Jeong, Yelim, Jeong, Yonghyun, Jiang, Can, Jiang, Juyong, Jin, Jiho, Jo, Ara, Jo, Younghyun, Jung, Hoyoun, Jung, Juyoung, Kang, Seunghyeong, Kim, Dae Hee, Kim, Ginam, Kim, Hangyeol, Kim, Heeseung, Kim, Hyojin, Kim, Hyojun, Kim, Hyun-Ah, Kim, Jeehye, Kim, Jin-Hwa, Kim, Jiseon, Kim, Jonghak, Kim, Jung Yoon, Kim, Rak Yeong, Kim, Seongjin, Kim, Seoyoon, Kim, Sewon, Kim, Sooyoung, Kim, Sukyoung, Kim, Taeyong, Ko, Naeun, Koo, Bonseung, Kwak, Heeyoung, Kwon, Haena, Kwon, Youngjin, Lee, Boram, Lee, Bruce W., Lee, Dagyeong, Lee, Erin, Lee, Euijin, Lee, Ha Gyeong, Lee, Hyojin, Lee, Hyunjeong, Lee, Jeeyoon, Lee, Jeonghyun, Lee, Jongheok, Lee, Joonhyung, Lee, Junhyuk, Lee, Mingu, Lee, Nayeon, Lee, Sangkyu, Lee, Se Young, Lee, Seulgi, Lee, Seung Jin, Lee, Suhyeon, Lee, Yeonjae, Lee, Yesol, Lee, Youngbeom, Lee, Yujin, Li, Shaodong, Liu, Tianyu, Moon, Seong-Eun, Moon, Taehong, Nihlenramstroem, Max-Lasse, Oh, Wonseok, Oh, Yuri, Park, Hongbeen, Park, Hyekyung, Park, Jaeho, Park, Nohil, Park, Sangjin, Ryu, Jiwon, Ryu, Miru, Ryu, Simo, Seo, Ahreum, Seo, Hee, Seo, Kangdeok, Shin, Jamin, Shin, Seungyoun, Sin, Heetae, Wang, Jiangping, Wang, Lei, Xiang, Ning, Xiao, Longxiang, Xu, Jing, Yi, Seonyeong, Yoo, Haanju, Yoo, Haneul, Yoo, Hwanhee, Yu, Liang, Yu, Youngjae, Yuan, Weijie, Zeng, Bo, Zhou, Qian, Cho, Kyunghyun, Ha, Jung-Woo, Park, Joonsuk, Hwang, Jihyun, Kwon, Hyoung Jo, Kwon, Soonyong, Lee, Jungyeon, Lee, Seungho, Lim, Seonghyeon, Noh, Hyunkyung, Choi, Seungho, Lee, Sang-Woo, Lim, Jung Hwa, and Sung, Nako

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. HyperCLOVA X was trained on a balanced mix of Korean, English, and code data, followed by instruction-tuning with high-quality human-annotated datasets while abiding by strict safety guidelines reflecting our commitment to responsible AI. The model is evaluated across various benchmarks, including comprehensive reasoning, knowledge, commonsense, factuality, coding, math, chatting, instruction-following, and harmlessness, in both Korean and English. HyperCLOVA X exhibits strong reasoning capabilities in Korean backed by a deep understanding of the language and cultural nuances. Further analysis of the inherent bilingual nature and its extension to multilingualism highlights the model's cross-lingual proficiency and strong generalization ability to untargeted languages, including machine translation between several language pairs and cross-lingual inference tasks. We believe that HyperCLOVA X can provide helpful guidance for regions or countries in developing their sovereign LLMs., Comment: 44 pages; updated authors list and fixed author names

Published
2024

4. DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding

Author

Yu, Xiaoxuan, Wang, Hao, Li, Weiming, Wang, Qiang, Cho, Soonyong, and Sung, Younghun

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Point scene understanding is a challenging task to process real-world scene point cloud, which aims at segmenting each object, estimating its pose, and reconstructing its mesh simultaneously. Recent state-of-the-art method first segments each object and then processes them independently with multiple stages for the different sub-tasks. This leads to a complex pipeline to optimize and makes it hard to leverage the relationship constraints between multiple objects. In this work, we propose a novel Disentangled Object-Centric TRansformer (DOCTR) that explores object-centric representation to facilitate learning with multiple objects for the multiple sub-tasks in a unified manner. Each object is represented as a query, and a Transformer decoder is adapted to iteratively optimize all the queries involving their relationship. In particular, we introduce a semantic-geometry disentangled query (SGDQ) design that enables the query features to attend separately to semantic information and geometric information relevant to the corresponding sub-tasks. A hybrid bipartite matching module is employed to well use the supervisions from all the sub-tasks during training. Qualitative and quantitative experimental results demonstrate that our method achieves state-of-the-art performance on the challenging ScanNet dataset. Code is available at https://github.com/SAITPublic/DOCTR.

Published
2024

5. DOR3D-Net: Dense Ordinal Regression Network for 3D Hand Pose Estimation

Author

Mao, Yamin, Liu, Zhihua, Li, Weiming, Cho, SoonYong, Wang, Qiang, and Hao, Xiaoshuai

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Depth-based 3D hand pose estimation is an important but challenging research task in human-machine interaction community. Recently, dense regression methods have attracted increasing attention in 3D hand pose estimation task, which provide a low computational burden and high accuracy regression way by densely regressing hand joint offset maps. However, large-scale regression offset values are often affected by noise and outliers, leading to a significant drop in accuracy. To tackle this, we re-formulate 3D hand pose estimation as a dense ordinal regression problem and propose a novel Dense Ordinal Regression 3D Pose Network (DOR3D-Net). Specifically, we first decompose offset value regression into sub-tasks of binary classifications with ordinal constraints. Then, each binary classifier can predict the probability of a binary spatial relationship relative to joint, which is easier to train and yield much lower level of noise. The estimated hand joint positions are inferred by aggregating the ordinal regression results at local positions with a weighted sum. Furthermore, both joint regression loss and ordinal regression loss are used to train our DOR3D-Net in an end-to-end manner. Extensive experiments on public datasets (ICVL, MSRA, NYU and HANDS2017) show that our design provides significant improvements over SOTA methods.

Published
2024

7. DVI-SLAM: A Dual Visual Inertial SLAM Network

Author

Peng, Xiongfeng, Liu, Zhihua, Li, Weiming, Tan, Ping, Cho, SoonYong, and Wang, Qiang

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measurement unit (IMU) in visual SLAM has potential research value. This paper proposes a novel deep SLAM network with dual visual factors. The basic idea is to integrate both photometric factor and re-projection factor into the end-to-end differentiable structure through multi-factor data association module. We show that the proposed network dynamically learns and adjusts the confidence maps of both visual factors and it can be further extended to include the IMU factors as well. Extensive experiments validate that our proposed method significantly outperforms the state-of-the-art methods on several public datasets, including TartanAir, EuRoC and ETH3D-SLAM. Specifically, when dynamically fusing the three factors together, the absolute trajectory error for both monocular and stereo configurations on EuRoC dataset has reduced by 45.3% and 36.2% respectively., Comment: Accepted to ICRA2024

Published
2023

12. Power-Efficient Beacon Recognition Method Based on Periodic Wake-Up for Industrial Wireless Devices

Author

Soonyong Song, Donghun Lee, Ingook Jang, Jinchul Choi, and Youngsung Son

Subjects
low-power, wake-up, beacon recognition, IEEE 802.15.4, Chemical technology, TP1-1185
Abstract

Energy harvester-integrated wireless devices are attractive for generating semi-permanent power from wasted energy in industrial environments. The energy-harvesting wireless devices may have difficulty in their communication with access points due to insufficient power supply for beacon recognition during network initialization. In this manuscript, we propose a novel method of beacon recognition based on wake-up control to reduce instantaneous power consumption in the initialization procedure. The proposed method applies a moving window for the periodic wake-up of the wireless devices. For unsynchronized wireless devices, beacons are always located in the same positions within each beacon interval even though the starting offsets are unknown. Using these characteristics, the moving window checks the existence of the beacon associated withspecified resources in a beacon interval, checks again for neighboring resources at the next beacon interval, and so on. This method can reduce instantaneous power and generates a surplus of charging time. Thus, the proposed method alleviates the problems of power insufficiency in the network initialization. The feasibility of the proposed method is evaluated using computer simulations of power shortage in various energy-harvesting conditions.

Published
2018
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16. MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results.

Author

Yuekun Dai, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Qingpeng Zhu, Qianhui Sun, Wenxiu Sun, Chen Change Loy, Jinwei Gu, Shuai Liu 0009, Hao Wang 0073, Chaoyu Feng, Luyang Wang, Guangqi Shao, Chenguang Zhang, Xiaotao Wang, Lei Lei, Dafeng Zhang, Xiangyu Kong, Guanqun Liu 0005, Mengmeng Bai, Jia Ouyang, Xiaobing Wang, Jiahui Yuan, Xinpeng Li, Chengzhi Jiang, Ting Jiang, Wenjie Lin, Qi Wu 0017, Mingyan Han, Jinting Luo, Lei Yu, Haoqiang Fan, Shuaicheng Liu, Bo Yan, Zhuang Li, Yadong Li, Hongbin Wang, Soonyong Song, Minghan Fu, Rayyan Azam Khan, Fang-Xiang Wu, Zhao Zhang 0001, Suiyi Zhao, Huan Zheng, Yangcheng Gao, Yanyan Wei, Jiahuan Ren, Bo Wang 0011, Yan Luo, Shuaibo Gao, Wenhui Wu, Sicong Kang, Nikhil Akalwadi, Ankit Raichur, Vinod Patil, Allabakash Ghodesawar, Swaroop Adrashyappanamath, Amogh Joshi 0001, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi, Sicheng Li, Ruoxi Zhu, Jiazheng Lian, Shusong Xu, Zihao Liu, Sabari Nathan, and Priya Kansal

Published
2023
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19. IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report

Author

She, Qi, Feng, Fan, Liu, Qi, Chan, Rosa H. M., Hao, Xinyue, Lan, Chuanlin, Yang, Qihan, Lomonaco, Vincenzo, Parisi, German I., Bae, Heechul, Brophy, Eoin, Chen, Baoquan, Graffieti, Gabriele, Goel, Vidit, Han, Hyonyoung, Kanagarajah, Sathursan, Kumar, Somesh, Lam, Siew-Kei, Lam, Tin Lun, Ma, Liang, Maltoni, Davide, Pellegrini, Lorenzo, Piyasena, Duvindu, Pu, Shiliang, Sheet, Debdoot, Song, Soonyong, Son, Youngsung, Wang, Zhengwei, Ward, Tomas E., Wu, Jianwen, Wu, Meiqing, Xie, Di, Xu, Yangsheng, Yang, Lin, Zhong, Qiaoyong, and Zhou, Liguang

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Robotics, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams). The competition dataset (L)ifel(O)ng (R)obotic V(IS)ion (OpenLORIS) - Object Recognition (OpenLORIS-object) is designed for driving lifelong/continual learning research and application in robotic vision domain, with everyday objects in home, office, campus, and mall scenarios. The dataset explicitly quantifies the variants of illumination, object occlusion, object size, camera-object distance/angles, and clutter information. Rules are designed to quantify the learning capability of the robotic vision system when faced with the objects appearing in the dynamic environments in the contest. Individual reports, dataset information, rules, and released source code can be found at the project homepage: "https://lifelong-robotic-vision.github.io/competition/"., Comment: 9 pages, 11 figures, 3 tables, accepted into IEEE Robotics and Automation Magazine. arXiv admin note: text overlap with arXiv:1911.06487

Published
2020

31. Weak trimer distortion and planar spin configuration in hexagonal Lu0.6In0.4FeO3.

Author

Cho, Kwanghee, Kamiyama, Takashi, Horibe, Yoichi, and Park, Soonyong

Subjects
MAGNETIC structure, FERROMAGNETISM, FERROELECTRICITY, FERRITES, LUTETIUM compounds
Abstract

Improper ferroelectricity and canted ferromagnetism in antiferromagnetically ordered hexagonal ferrites with A2-type spin configuration have been intensely studied due to their potential for room-temperature multiferroicity with strong magnetoelectric couplings. However, the subtle interplay between the magnetic structure and trimer structural distortion, which is a critical ingredient for ferroelectricity, has not been clearly verified in experiments due to the lack of control over trimer distortion. In this study, we report on Lu0.6In0.4FeO3, which exhibits weaker trimer distortion primarily related to the smaller tilting of the FeO5 bipyramids. The reduced vertical displacement of the equatorial oxygen of FeO5 located at the center of the trimer lowers the magnitude of the in-plane Dzyaloshinskii–Moriya vector component, resulting in the absence of canted ferromagnetism with the planar A1-type spin configuration, rather than the canted A2-type observed in other hexagonal ferrites. Our findings demonstrate that the degree of trimer distortion plays an important role in determining the spin configuration in related hexagonal systems. [ABSTRACT FROM AUTHOR]

Published
2023
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36. IROS 2019 Lifelong Robotic Vision: Object Recognition Challenge [Competitions].

Author

Heechul Bae, Eoin Brophy, Rosa H. M. Chan, Baoquan Chen, Fan Feng, Gabriele Graffieti, Vidit Goel, Xinyue Hao, Hyonyoung Han, Sathursan Kanagarajah, Somesh Kumar, Siew-Kei Lam, Tin Lun Lam, Chuanlin Lan, Qi Liu 0042, Vincenzo Lomonaco, Liang Ma, Davide Maltoni, German Ignacio Parisi, Lorenzo Pellegrini, Duvindu Piyasena, Shiliang Pu, Qi She, Debdoot Sheet, Soonyong Song, Youngsung Son, Zhengwei Wang, Tomas E. Ward, Jianwen Wu, Meiqing Wu, Di Xie, Yangsheng Xu, Lin Yang, Qihan Yang, Qiaoyong Zhong, and Liguang Zhou

Published
2020
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43. SBraille: A New Braille Input Method for Mobile Devices

Author

Lee, Soonyong, Park, Ji Su, Shon, Jin Gon, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Park, James J., editor, Loia, Vincenzo, editor, Yi, Gangman, editor, and Sung, Yunsick, editor

Published
2018
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49. 韓国における児童虐待事犯教育プログラムの効果に関する統合的アプローチ

Author

Soonyong, Park and Minho, Kang

Subjects
効果, 児童虐待事犯, South Korea, 統合的アプローチ, Education program, 369.4, Effectiveness, 韓国, Child abuse offender, Integrated approach, 教育プログラム
Abstract

本研究の目的は，韓国の児童虐待履修命令者を対象に実施した教育プログラムの効果分析を通じ，その活用可能性および持続可能性に対する手がかりを得ることである。児童虐待事犯10人を対象とし，20セッション50時間で構成される心理療法プログラムを実施し，包含モデルを基にした統合的アプローチにて分析を行った。具体的には，自尊感情尺度と育児自己効力感尺度を採用し，対応のあるt-検定にて教育プログラム前後の変化を分析したところ，p＜.05 レベルで統計的に有意であった。同時に，グループワークでの発言に対する内容分析においても教育が進むにつれ，参加者の自己省察が深化され，教育に対する認識が前向きに変化することが示された。考察では，本教育プログラムが「児童虐待事犯による虐待行為の再発」を防ぐなどの肯定的な機能を有する可能性について述べた。, This study analyzes the effectiveness of an educational program targeting child abuse offenders in South Korea, thereby gaining insight into its potential use and sustainability. A psychotherapy program for ten child abuse offenders was conducted, consisting of 20 sessions over 50 hours. Subsequently, analysis was conducted using an integrated approach based on the embedded model. Specifically, the self-esteem and parenting self-efficacy scales were employed with the changes before and after the educational program analyzed via a paired t-test. These changes were statistically significant at the p＜.05 level. Simultaneously, a content analysis of the participants' comments during the group work showed that as time went on, their selfreflection deepened and there were positive changes in their perception of the program. In the discussion section, we reflect on the potential positive functions of this educational program, such as preventing the recurrence of abusive behavior by child abuse offenders., 論文(Article)

Published
2023

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