https://scholar.dgist.ac.kr/handle/20.500.11750/10135 2026-04-08T18:02:01Z https://scholar.dgist.ac.kr/handle/20.500.11750/60180 Title: Long Short-Term Memory Network-Based H∞ Synchronization Control and Anomaly Detection for Cyber-Physical Systems Author(s): Kwon, Hyoeun; Lee, Suwoong; Kwon, Wookyong; Lim, Yongseob; Jin, Yongsik Abstract: In the synchronization of cyber-physical systems (CPSs), modeling the nonlinear dynamics of physical plants is a challenging task. To address this challenge, we propose a novel H∞ controller design method that leverages a data-driven approach to robustly synchronize CPSs and ensure their stability. In the proposed approach, the input-output relationship of the physical system is learned using long short-term memory (LSTM) networks to approximate the unknown dynamics of CPSs. Furthermore, we exploit an effective control scheme for trained LSTM networks to effectively handle the nonlinearity of activation functions. To ensure stability and performance in the convergence of synchronization error, a controller design criterion is derived for the trained LSTM network in terms of linear matrix inequalities, and the controller gain is computed using convex optimization techniques. In addition, we present an anomaly detection algorithm using the proposed method, which can synchronize CPSs and detect abnormal signals without requiring any prior physical model information. Consequently, the stability of the synchronization control system can be ensured, enabling its application to anomaly detection. Finally, the effectiveness of the proposed method is validated through an experiment on a motor control system even in abnormal operating conditions. 2025-10-06T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60146 Title: 얼굴 검출 기술을 이용한 학습 관리 방법 및 장치 Author(s): 강원석; 손창식; 진상현 Abstract: 본 개시는 얼굴 검출 기술 기반으로 학습자의 집중도를 분석하고, 집중도에 따라 맞춤형 학습 콘텐츠를 제공하는, 얼굴 검출 기술을 이용한 학습 관리 방법 및 장치에 관한 것이다. https://scholar.dgist.ac.kr/handle/20.500.11750/60137 Title: 3차원 뼈 모델을 재건하는 장치 및 방법 Author(s): 이현기; 하호건; 이종철 Abstract: 본 개시의 일 실시 예에 따른 3차원 뼈 모델 재건 방법은 각 단계의 적어도 일부가 프로세서에 의해 수행되는 단계로서, 환자의 뼈를 촬영한 적어도 한 장의 엑스레이 영상을 제공 받는 단계 및 엑스레이 영상을 딥 러닝에 기반한 학습 모델에 입력하여 뼈에 대한 SSM(Statistical Shape Model)의 파라미터를 출력하는 단계를 포함할 수 있다. https://scholar.dgist.ac.kr/handle/20.500.11750/60081 Title: 뿜칠 로봇의 강화 학습 기반 작업 초기 위치 인식 방법 Author(s): 이승열 Abstract: Recently, there has been a lot of interest concerning automation and robotics in hazardous environments including construction sites. Spray robots paint walls or ceilings on construction sites instead of workers. The main functions of the spray robot include initial spray position recognition, robot path generation, robot path following, and spray quality inspection. This paper describes a method to automatically recognize the initial spray position using AI. In particular, this paper discusses a reinforcement learning method for a spray robot to recognize the corner where the ceiling and adjacent wall meet as the initial spray position when spraying a wall. 2025-12-11T15:00:00Z