• ETRI Journal
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• 제44권2호
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• 로봇학회논문지
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• 제17권4호
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• pp.425-430
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• 2022

As robots are considered one of the mainstream digital transformations, robots with machine vision becomes a main area of study providing the ability to check what robots watch and make decisions based on it. However, it is difficult to find a small object in the image mainly due to the flaw of the most of visual recognition networks. Because visual recognition networks are mostly convolution neural network which usually consider local features. So, we make a model considering not only local feature, but also global feature. In this paper, we propose a detection method of a small marker on the object using deep learning and an algorithm that considers global features by combining Transformer's self-attention technique with a convolutional neural network. We suggest a self-attention model with new definition of Query, Key and Value for model to learn global feature and simplified equation by getting rid of position vector and classification token which cause the model to be heavy and slow. Finally, we show that our model achieves higher mAP than state of the art model YOLOr.

• Advances in nano research
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• 제15권3호
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• pp.239-251
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• 2023

In the present study, we aim to use nanotechnology sensors/actuators to capture pressure and frequency of voice singers and to send signals for improving breathing pressure. In this regard, a circular composite structure having 3 different layers are used. The core layer is nano-composite material reinforced with graphene nanoplatelets. The face sheets are piezo electric materials connected to electrical circuit capable of measuring and applying voltage to the piezoelectric layers. This sensors have extremely smaller size than conventional sensors attached to the neck of singer and, hence, minimizes the influences on the output voice of the singer. A brief theoretical framework are presented for nonlocal strain gradient theory and geometry of the sensor is described in detail. The controlling procedure along with experimental results on 20 amateur and professional singer participants are also presented. The results of the study indicate that the participants could gain benefit from the device for improving their ability in phonation and keeping their frequency at a constant level although they have difficulty in the beginning of the experiment getting used to the device.

• 웰빙융합연구
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• 제7권1호
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• pp.43-50
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• 2024

Purpose: People must express their feelings and thoughts to maintain mental health and stability. Expressing one's emotions, experiences, and thoughts in writing relieves inner feelings, promotes self-exploration, and improves individual well-being, resulting in a pleasant state on physical, mental, and social levels. This study aims to reveal the learning experiences of university students who participated in a self-expressive writing course to improve their well-being. Method: To explore the learning experiences of university students who took a self-expressive writing course, this study used qualitative research methods to analyze the students' written reflection notes. Results: Self-expressive writing was found to resolve university students' negative emotions, regulate their emotions, improve their self-reflection and self-awareness, contributing to their problem-solving skills and ability to set new goals, and strengthen their social communication. The meaning of this class experience can be summarized as healing, awareness, reflection, change, and growth. Conclusion: The results of this study provide concrete data on expressive writing classes and are valuable when designing the writing programs.

• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.182-190
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• 2024

Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

• ETRI Journal
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• 제46권1호
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• pp.11-21
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• 2024

We focus on open-domain question-answering tasks that involve a chain-of-reasoning, which are primarily implemented using large language models. With an emphasis on cost-effectiveness, we designed EffiChainQA, an architecture centered on the use of small language models. We employed a retrieval-based language model to address the limitations of large language models, such as the hallucination issue and the lack of updated knowledge. To enhance reasoning capabilities, we introduced a question decomposer that leverages a generative language model and serves as a key component in the chain-of-reasoning process. To generate training data for our question decomposer, we leveraged ChatGPT, which is known for its data augmentation ability. Comprehensive experiments were conducted using the HotpotQA dataset. Our method outperformed several established approaches, including the Chain-of-Thoughts approach, which is based on large language models. Moreover, our results are on par with those of state-of-the-art Retrieve-then-Read methods that utilize large language models.

• 한국식품조리과학회지
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• 제20권6호
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• pp.677-683
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• 2004

한국 전통 한 그릇 음식인 비빔밥에 들어가는 재료로 호박(squash), 참취(frugrantedible wild aster), 표고버섯(shiitake mushroom, Cortinellus shiitake), 고사리 (roots of ballonflowers, Platycodongroundiflourum), 도라지(fornbraber) 및 당근(carrot)을 생시료, 간단 조리 및 양념 조리 한 것의 ethanol 추출물에 대한 DPPH 수소공여능과 아질산염 소거능을 사람의 소화기관 환경과 유사한 $pH\;1.2\~3.0$(위 환경)과 pH 6.0(장 환경)에서 측정한 결과는 다음과 같다. 수소공여능은 생시료, 간단조리, 및 양념조리 모두 참취가 월등히 높았고, 그 다음이 표고버섯이었다. 전반적으로 간단조리시나 양념 조리함으로써 항산화성이 향상되었다. 비빔밥을 한 그릇 음식인 김밥 및 햄버거와 비교했을 때 비빔밥>김밥>햄버거의 순으로 비빔밥의 항산화성이 월등히 높았으며 유의적인 차이가 인정되었다(p<0.05). 아질산염 소거능을 사람의 소화기관 환경과 유사한 $pH\;1.2\~3.0$(공복 시 및 비공복시 위 환경)과 pH 6.0(장 환경)에서는 비빔밥 재료들의 생시료, 간단조리 및 양념조리 시 시료간에 유의적 차가 없었으나(p<0.05), 생시료보다 간단조리나 양념조리 경우 아질산염 소거능이 약간 향상되었으며 공복환경(pH 1.2)에서 약간 높게 나타났다. 특히, 참취의 아질산염 소거능이 우수하였다. 장 환경에서 시료간 조리방법에 따른 유의적 차이는 없었으며 위한경보다 낮게 측정되었고 비빔밥을 김밥이나 햄버거와 비교시 비빔밥의 아질산염 소거능은 위 환경에서 약간 높게 나타났다.

• 한국응급구조학회지
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• 제13권3호
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• pp.29-40
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• 2009

Objective : This study is an experimental study which is designed to examine the differences between knowledge and self-confidence before and after theory education(CPR PPT material) based on guidelines of CPR and emergency cardiac treatment of American Heart Association(AHA, 2005) and video self-instruction program for the general public by Korean Association of Cardiopulmonary Resuscitation(KACPR), trace CPR performance ability after CPR and AED education and investigate the accuracy of artificial respiration and chest compression, and know the difference in CPR performance abilities including AED. Methods : Subjects of this study include ground crews and staffs at M airport in G province equipped with emergency equipments for CPR according to Art. 47, Sec. 2 of Emergency Medical Law, airport police, rent-a-cops, security guard, quarantine officer, custom officer, and communication, electricity, civil engineering, facility management staff, airport fire fighting staff, air mechanic, traffic controller, and airport management team among airport facility management staffs. They were given explanation of necessity of research and 147 of 220 subjects who gave consent to this research but 73 who were absent from survey were excluded were used as subjects of this study. of 147 subjects, there were 102 men and 45 women. Results : 1) Knowledge score of CPR was $6.18{\pm}0.87$ before instruction and it was increased to $15.12{\pm}1.78$ after instruction, and there was statistically significant difference. 2) Self-confidence score in CPR was $3.16{\pm}0.96$ before instruction and it was increased to $7.05{\pm}0.75$ after instruction, and there was statistically significant difference. 3) Total average score in CPR performance ability after instruction was 7.46 out of 9, performance ability was highest in confirmation of response as 144(97.95%), follwed by request of help as 140(95.25%) and confirmation of respiration as 135(91.83%), and lowest in performing artificial respiration twice(gross elevation of chest) as 97(65.98%). Accuracy of artificial respiration(%) was $28.60{\pm}16.88$ and that of chest compression(%) was $73.10{\pm}22.16$. 4) Performance ability of AED after instruction showed proper performance in power on by 141(95.91%) and attaching pad by 135(91.83%), hand-off for analyzing rhythm showed 'accuracy' in 115(78.23%) and 'non-performance' in 32(21.77%), delivery of shock and hand-off confirmation showed 'accuracy' in 109(74.14%) and 'inaccuracy' in 38(25.86%), and beginning chest compression immediately after AED was done by 105(71.42%).

• 예술인문사회 융합 멀티미디어 논문지
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• 제6권11호
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• pp.81-90
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• 2016

본 연구는 베를린 국립유럽학교(SESB)의 교육과정을 분석하여, 독일의 이주민 사회통합 정책에 따른 상호문화교육에 대하여 이중언어교육을 중심으로 알아보았다. 이를 위하여 베를린 국립유럽학교 중에서 Joan-Miró 초등학교와 Finow 초등학교을 사례로 교육과정을 분석하였다. 독일에서는 이주가정의 학생이 자신이 속한 문화적 공동체의 언어 및 정체성을 유지하면서 동시에 독일사회에 통합할 수 있는 다문화교육 정책을 유지하고 있다. 따라서 이주자들의 모국어 사용능력 유지와 이주학생들의 독일어습득이 독일의 사회통합 정책의 중심에 있다고 할 수 있다. 베를린 국립유럽학교는 학생들의 언어능력뿐만 아니라, 다양한 문화적 배경의 학생들을 위한 상호문화교육 환경 조성을 위하여 설립된 일반 공립학교이다. 베를린의 국립유럽학교는 이주가정 출신의 학생들이 그들의 언어와 문화정체성을 유지하는 것과 동시에 독일사회에 통합할 수 있도록 하는 상호문화교육을 교육목표로 하고 있다. Joan-Miró 초등학교에서는 학생들의 미래 지식사회를 위한 준비와 함께 상호문화 능력 및 이중언어 능력을 장려하고, 학생들로 하여금 독립적 생활과 자기주도적 학습을 할 수 있도록 하고 있다. Finow 초등학교에서는 학생들에게 미래 유럽의 지식사회에서 요구하는 시민으로서의 역량을 강화시킬 수 있는 기본능력 이외에 상호문화적 역량 및 언어적 역량, 그리고 지향성 역량을 장려하고 있다. 한국 학교의 외국어교육에서도 독일의 국립 유럽학교와 같이 실용적으로 다변화할 필요가 있다. 이와 함께 학생들의 이중언어능력의 개선, 학생 각각의 개인별 특성에 맞는 능력개발, 그리고 상호문화이해역량을 증진할 수 있도록 교육환경의 개선이 필요하다.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.921-929
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• 2011

정보화시대에 대학에서의 교양 컴퓨터교육과정은 컴퓨터에 대한 소양을 쌓고 정보화 사회에 능동적으로 대처할 수 있는 능력을 배양하여 생산성 향상은 물론 국가 간의 경쟁력에서 뒤지지 않게 하는데 목표를 두고 있다. 본 논문에서는 대학생을 대상으로 컴퓨터교육 만족도에 영향을 미치는 결정적인 변인의 발견 및 만족도를 분석한다. 전처리과정으로 자바 기반의 학습 도구인 속성 부분집합의 선택기반을 사용하여 최적의 변인을 선택한 후 통계적 학습이론에 기반을 둔 다중 최소제곱 서포트벡터 기계를 사용하고자 한다. 대학의 교양 컴퓨터교육 만족도 분석을 위하여 새로운 알고리즘을 제시하기 보다는 기존의 다중 서포트벡터기계와 다중 최소제곱 서포트벡터기계를 비교 분석한다. 본 논문의 연구결과는 컴퓨터교육 만족도 자료의 분석에서 다중 최소제곱 서포트벡터기계가 다중 서포트벡터기계와 같이 우수한 성과를 나타내는 것을 확인하였다.