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수중 항법을 위한 ROS 기반 시뮬레이터를 이용한 센서 데이터 수집
김하선,김아란,강창호,김선영 제어·로봇·시스템학회 2023 제어·로봇·시스템학회 논문지 Vol.29 No.4
Simultaneous localization and mapping (SLAM) is a navigation technology used in scenarios where the surrounding environment is unknown. Although SLAM technology is highly advanced in atmospheric environments, it is not highly effective in underwater environments because of various constraints. In addition, experiments in underwater environments involve higher risks and costs compared with other environments. Therefore, in this paper, a simulator-based data collection method was proposed to reduce risks and costs for effective experimentation. By using the proposed method, sensor data can be acquired by adding and generating paths to control the movement of underwater robots depending on research purposes. In addition, collected data can be saved in various formats to facilitate data processing. Moreover, an experiment was conducted to verify that SLAM can be performed using the data collected.
표적 탐지 및 식별 성능 향상을 위한 레이더 측정치 분석
김하선,김아란,강창호,김선영 제어·로봇·시스템학회 2022 제어·로봇·시스템학회 논문지 Vol.28 No.3
Using artificial intelligence, radar measurements can improve the performance of target detection and identification methods. Testing data was generated from existing radar data, high-resolution range profile, and inverse synthetic aperture radar images. Radarcross section was chosen as the main parameter because it has been widely studied and its parameters are well known. To ensure thequality of the training dataset, we used simulation tools to determine which parameters had the greatest effect on the generated data. Missile models with different shapes were applied during simulations to confirm the possibility of detection and identification whensuitable parameters were applied. .
CARLA를 활용한 전이학습 기반 객체 검출 데이터 셋 구축에 관한 연구
김하선,라해윤,김아란,김선영 제어·로봇·시스템학회 2024 제어·로봇·시스템학회 논문지 Vol.30 No.2
The bounding box (BBox) affects the performance in object detection, but an appropriate size for the BBox has not been suggested. In addition, collecting an artificial intelligence dataset is time-consuming and affects a company’s profits. Therefore, we propose effective labeling methods and the ratio of real and synthetic datasets to improve performance. First, we checked the performance by removing BBoxes smaller than a certain percentage of the image size. Second, we searched for the appropriate BBox size by increasing the BBox edges by 0.5 pixels. Comparison of the two methods showed that the best performance was obtained by removing BBoxes smaller than 0.5% of the image size and increasing the BBox edges by 2 pixels. Finally, we evaluated the utility of a synthetic dataset and the appropriate ratio of the real and synthetic datasets. We found that combining real and synthetic datasets could be used effectively compared with using only the real dataset. Furthermore, after verifying the generalization performance, the combination of real and synthetic datasets in a ratio of 8:2 outperformed when only the real dataset was used.
토픽모델링을 활용한 상담과정에서 상담자와 내담자 간 언어변화
김하선(Ha-Seon Kim),조남옥(Nam-Ok Cho),이윤주(Yoon-Joo Lee) 학습자중심교과교육학회 2023 학습자중심교과교육연구 Vol.23 No.20
목적 본 연구의 목적은 상담과정에서 이루어진 상담자와 내담자 간의 상담 내용을 토픽모델링을 활용하여 주요 주제를 추출하며 시간의 흐름에 따른 언어변화를 탐색하는 데 있다. 방법 한 상담사가 주 1회 50분 동안 총 5회에 걸쳐 내담자 A와 내담자 B에게 개별상담을 진행한 내용과 추수상담 1회를 포함한 상담 축어록을 전사한 후, 정제과정을 거친 뒤 빈도분석과 토픽모델링을 실시하였다. 결과 빈도 분석 결과, 내담자 A의 상담에서 주요 핵심어는 ‘생각’, ‘사람’, ‘마음’ 등이 나타났으며, 내담자 B의 상담에서는 ‘엄마’, ‘아이’, ‘이야기’ 등이 주로 등장하였다. LDA토픽모델링 결과, 내담자 A의 주요 토픽은 ‘생각과 기분’, ‘자신의 생활’ 등으로, 상담자의 토픽은 ‘남편과 마음’, ‘사람의 마음’ 등 5개씩 추출되었다. 내담자 B의 주요 토픽은 ‘교수 생각’, ‘칭찬 이야기’ 등으로, 상담자의 토픽은 ‘걱정된 이야기’, ‘엄마 공부’ 등 8개씩 추출되었다. 또한, DTM토픽모델링 결과, 내담자 A와 B 모두 상담 초기와 종결 회기에서의 토픽 출현이 높았으며, 상담과정 중에는 낮았다. 반면, 상담자는 상담 초기부터 종결 회기까지 토픽의 출현이 높았으며, 추수상담에서는 내담자와 상담자 모두 토픽 출현이 낮게 나타났다. 결론 본 연구를 통해, 상담과정 중 핵심 주제어와 토픽을 추출하여 내담자의 관심사와 주제를 파악하고 토픽 변화를 분석함으로써, 상담자와 내담자 간 상호작용에서 특정 주제와 언어가 어떻게 변화되는지 탐색하는 데 도움이 되었다. 이러한 연구 결과는 상담자가 내담자의 주요 관심사에 초점을 맞춘 개인상담을 진행하고 있는지 확인하여 상담과정의 질을 개선하는 데 중요한 정보를 제공함을 시사한다. 뿐만 아니라, 개인상담의 내용을 분석하는 데 토픽모델링이라는 인공지능 분석기법을 활용하여, 상담과정에서 상담자와 내담자 간 언어변화를 제시하는 데 의의를 두고 있다. Objectives The aim of this study is to utilize counseling content between counselors and clients during the coun-seling process using topic modeling, extract key themes, and investigate language changes over time. Methods A single counselor conducted individual counseling sessions with Client A and Client B, each lasting 50 minutes, once a week for a total of 5 sessions. The transcripts of these counseling sessions, including a follow-up session, underwent refinement before undergoing frequency analysis and topic modeling. Results In the frequency analysis, key keywords in Client A's counseling sessions included ‘thoughts,’ ‘people,’ and ‘emotions,’ while in Client B's counseling sessions, ‘mother,’ ‘child,’ and ‘stories’ predominated. LDA topic modeling revealed that Client A's major topics were ‘thoughts and emotions’ and ‘personal life,’ while topics such as ‘husband and emotions’ and ‘people's emotions’ were extracted for the counselor, each occurring 5 times. For Client B, primary topics included ‘professor's thoughts’ and ‘complimentary stories,’ while for the counselor, top-ics like ‘worrisome stories’ and ‘mother's studies’ were extracted, each occurring 8 times. Additionally, DTM topic modeling results showed that both Client A and B had higher topic appearances at the beginning and end stages of counseling, with lower appearances during the counseling process. In contrast, the counselor had a high topic appearance from the beginning to the end, while in the follow-up session, both the client and the counselor showed lower topic appearances. Conclusions Through this study, extracting core keywords and topics during the counseling process allowed for the identification of client interests and themes, as well as the analysis of topic changes over time. This in-formation can assist counselors in focusing on the client's primary concerns, thus improving the quality of the counseling process. Furthermore, the use of artificial intelligence analysis techniques such as topic modeling in analyzing the content of individual counseling sessions is significant in presenting language changes between counselors and clients during the counseling process.