1,722,344 research outputs found
M.I.Tomorrow--visions for East Campus
Full text linkThesis (M.S.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning and Dept. of Architecture, 1987.Bibliography: leaves [104]-[105].by Woo-Hyun Yang.M.S
Is Korea’s public funding for SMEs achieving its intended goals?
No full text노트 : This article is based on “Study on the Enhancement of the Small and Medium-sized Enterprises(SMEs) Policy in Korea (Ⅰ), (Ⅱ)” written by Chang, Woo Hyun, Yang, Yong Hyeon and Woo, Seokjin
내시경 수련을 위한 햅틱 인터페이스 하드웨어 시스템
No full text학위논문(석사) - 한국과학기술원 : 기계공학전공, 2002.2, [ viii, 61 p. ]This thesis develops a new haptic interface hardware system which is suitable for implementing the characteristics of endoscopy training. Endoscopic haptic devices with 4 DOF and 3 DOF are developed and the haptic interface system including the haptic device, the motor driver, the host computer with a control board, and Graphic User Interface (GUI) is implemented. The 3 DOF haptic device is designed with one prismatic joint and two revolute joints to provide endoscopic motions. The 4 DOF haptic device that improves defects of the 3 DOF haptic device and implements even roll motion of endoscopy is developed. Motor torques are transmitted using wire-driven mechanism which provides large torques and back drivability. Kinematics, inverse kinematics, and Jacobian matrix are derived. The central axes of each DOF are designed to intersect at one point, and this makes the equations of kinematics and inverse kinematics simple. Performance indexes such as continuous and maximum exertable force and torques, workspace, sensitivity, and inertia of each joint are measured. Frequency response tests such as bandwidth and phase are performed. Experiments to measure bandwidth of the 3 DOF PHANToM are performed to compare developed devices with commercial ones.한국과학기술원 : 기계공학전공
Time-Domain Adaptive Control Scheme for a New Passivity Condition Including the Human Arm Impedance
No full textThe new passivity condition including the human arm impedance shows that the achievable maximum stiffness at each sampling period depends on the local minimum viscosity of the human arm during the sampling period. Based on the analytical results and the characteristics of the human arm, a new control scheme is proposed to improve the performance of the haptic system, when the human arm impedance varies largely. We present a method to predict the local minimum of the human arm viscosity at every sampling period and design an adaptive virtual coupling that maximizes the performance of the system while guaranteeing the passivity of the system. The newly defined Passivity Margin Tracker (PMT) tracks how much more conservative the haptic system is than the ideal mass-spring system in the aspect of the passivity. These results are verified through experiments to affirm that the proposed method is shown to usefully improve the performance of a haptic system if the human arm viscosity is initially calibrated
The atomic and electronic properties of coordination defects in amorphous oxide semiconductors
No full textThe electronic structure of undercoordinated cation defects in amorphous oxide semiconductors
No full textElectronic structure of undercoordinated cation defects in amorphous oxide semiconductors
No full textElectronic structure of disorder-induced cation defects in amorphous oxide semiconductors
No full textStudy on Unsupervised Learning and Cyber Threat Detection in Industrial Control Systems Woo-Hyun Choi Gwangju Institute of Science and Technology
No full text산업 제어 시스템(ICS)은 제조 및 에너지와 같은 분야의 중요 인프라를 관리하는 데 필수적입니다. 이러한 시스템들의 네트워크 연결성이 증가함에 따라 사이버 보안 위험 에 대한 취약성이 높아졌습니다. 격리된 환경을 위해 설계된 ICS는 이제 중요한 위협에 노출되어 있으며, 이는 중요 인프라에 물리적 손상을 초래한 Stuxnet 공격과 같은 사례 에서확인되었습니다.전통적인 IT시스템과달리 ICS는 물리적 프로세스를 제어하므로 사이버 공격이 실제 세계에 구체적인 영향을 미칠 수 있습니다. ICS 보안의 주요 과 제는 다양한 장치와 독점 프로토콜로 구성된 이러한 시스템의 복잡성과 이질성입니다. 지속적인 운영 요구로인해 보안 업데이트 기회가 제한되어 기존 IT보안조치의 효과가 감소됩니다. 그결과, 실시간으로 알려지지 않은 위협과 이상을 탐지하기 위해 머신러닝과 비지도학습기술을 포함한 고급 접근 방식을 탐구하는 데 관심이 증가하고 있습니다. 이 논문은 두 부분으로 구성되어 있습니다. 첫 번째 부분은 비지도 기계 학습을 사용한 ICS의 이상 탐지를 검토합니다. 이 연구는 사전에 레이블이 지정된 데이터 없이 이상 행동을 식별하기 위한 복합 오토인코더 모델을 조사합니다. HIL-based Augmented ICS(HAI)의 데이터셋을 활용하여 값과 시간 모두와 관련된 이상을 탐지하는 모델의 능력을 분석합니다. 이 접근 방식은 ICS 환경 에서 시스템 신뢰성과 운영 효율성을 향상시키기 위한 지속적인 노력에 기여하는 것을 목표로 합니다. 두 번째 부분에서는 MITRE ATT&CK 프레임워크와 함께 ICS 트래픽의 이상 탐지를 위한 영과잉 포아송(ZIP) 기반 GRU 학습 모델을 탐구합니다. 모델의 성능은 ’Stuxnet’ 과 ’Industroyer’라는 두가지 주요 사이버 공격 시나리오 시뮬레이션을 통해 평가 되었습니다. 탐지된 이상을 MITRE ATT&CK 프레임워크에 매핑함으로써, 이 연구는 이러한 공격에 대한 정보에 입각한 대응 전략 개발에 기여하고자 합니다. 이 연구는 ICS 보안의 지속적인 과제를 다루며,진화하는 사이버위협으로부터 이러한 중요시스템을 보호하기 위한 잠재적 접근 방식을 연구합니다.|Industrial Control Systems (ICS) are essential for managing critical infrastructure in sectors such as manufacturing and energy. The increasing connectivity of these systems to networks has heightened their vulnerability to cybersecurity risks. Originally designed for isolated environments, ICS are now exposed to significant threats, as evidenced by incidents like the Stuxnet attack, which resulted in physical damage to critical infrastructure. Unlike traditional IT systems, ICS control physical processes, meaning cyberattacks can have tangible, real-world impacts. A significant challenge in ICS security is the complexity and heterogeneity of these systems, which comprise diverse devices and proprietary protocols. The requirement for continuous operation limits opportunities for security updates, reducing the effectiveness of conventional IT security measures. As a result, there is growing interest in exploring advanced approaches, including machine learning and unsupervised learning techniques, for real- time detection of unknown threats and anomalies. This dissertation examines two key topics. The first examines anomaly detection in ICS using unsupervised machine learning. The study investigates a composite autoencoder model for identifying anomalous behavior without pre-labeled data. Utilizing a dataset from HIL-based Augmented ICS (HAI), the research analyzes the model’s capacity to detect anomalies related to both value and time. This approach aims to contribute to the ongoing efforts to enhance system reliability and operational efficiency in ICS environments. The second focuses on a Zero Inflated Poisson (ZIP) based GRU Learning model for anomaly detection in ICS traffic, in conjunction with the MITRE ATT&CK framework. The model’s performance was evaluated through simulations of two major cyberattack scenarios, Stuxnet and Industroyer. By mapping detected anomalies to the MITRE ATT&CK framework, the study seeks to contribute to the development of more in- formed response strategies for such attacks. This research addresses the ongoing challenges in ICS security and studies potential approaches to enhance the protection of these critical systems against evolving cyber threats.DoctorAbstract (English) i
Abstract (Korean) iii
List of Contents v
List of Tables vii
List of Figures ix
1 Introduction 1
1.1 Research Motivation 2
1.2 Contributions 8
1.3 Organization 10
2 Related Work 12
2.1 Anomaly Detection and Identification in Complex Industrial Control
Systems 12
2.1.1 Anomaly Detection in Industrial Control Systems 13
2.1.2 Recent Approaches to the Study of Anomaly Detection in Industrial Control System 14
2.2 GRU-Poisson Model 16
2.2.1 MITRE ATT&CK Framework for ICS 16
2.2.2 ICS Security and Protection Mechanisms 19
3 Unsupervised Learning Approach for Anomaly Detection in Indus-
trial Control Systems 24
3.1 Proposed Approach 25
3.2 HAI Dataset 25
3.2.1 Data Preparation 28
3.2.2 Evaluation Metrics 36
3.3 Experiment and Evaluation 37
3.3.1 Classification and Confusion Matrix 37
3.3.2 Abnormal Behavior Detection Experiment 39
3.4 Summary 43
4 Detecting Cybersecurity Threats for Industrial Control Systems using Machine Learning 44
4.1 Motivation, Problem Description, and Key Contributions 45
4.2 System Model 45
4.2.1 Raw traffic dataset 45
4.2.2 Aligning data with MITRE ATT&CK Framework 49
4.2.3 Zero-Inflated Poisson 51
4.2.4 GRU based Detection Model 52
4.2.5 Model Performance Comparison 57
4.3 Implementation 59
4.4 Experiment and Result and Analysis 61
4.4.1 Stuxnet 63
4.4.2 Industroyer 69
4.5 Summary 76
5 Conclusion 78
References 81
A. Abbreviations 92
Acknowledgements 9
sj-docx-1-tag-10.1177_17562848241239551 – Supplemental material for Comparison of long-term outcomes of endoscopic ultrasound-guided hepaticogastrostomy and choledochoduodenostomy for distal malignant biliary obstruction: a multicenter retrospective study
No full textSupplemental material, sj-docx-1-tag-10.1177_17562848241239551 for Comparison of long-term outcomes of endoscopic ultrasound-guided hepaticogastrostomy and choledochoduodenostomy for distal malignant biliary obstruction: a multicenter retrospective study by Dongwook Oh, Sung Yong Han, Sang Hyub Lee, Seong-Hun Kim, Woo Hyun Paik, Hyung-Ku Chon, Tae Jun Song, Se Woo Park and Jae Hee Cho in Therapeutic Advances in Gastroenterology</p
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