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Journal Paper Accepted (Composites Part B: Engineering): Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network

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Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network  Asif Khan, Dae-Kwan Ko, Soo Chul Lim*, Heung Soo Kim* (* : corresponding author) Abstract This paper proposes a Convolutional Neural Network (CNN) based approach for the classification and prediction of various types of in-plane and through-the-thickness delamination in… 더 보기 »Journal Paper Accepted (Composites Part B: Engineering): Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network

US patent 등록 “Apparatus and method for controlling vibration transfer between vibration devices”, US10152127

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AbstractProvided is an apparatus and method for controlling a vibration transfer between vibration devices. The apparatus for controlling a vibration transfer may change vibration values of a plurality of vibration devices according to a movement of a virtual vibration body, thereby providing a user with a sense of touch of a movement of the virtual… 더 보기 »US patent 등록 “Apparatus and method for controlling vibration transfer between vibration devices”, US10152127

Journal Paper Accepted (IEEE Sensors Journal): Interaction Force Estimation using Camera and Electrical Current without Force/Torque Sensor

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Interaction Force Estimation using Camera and Electrical Current without Force/Torque Sensor Dong-Han Lee ;  Wonjun Hwang ;  Soo-Chul Lim Abstract: In this paper, we propose a method for the estimation of the interaction forces between the motorized system and object through visual and electric information. In particular, we propose a new interaction force sensing method… 더 보기 »Journal Paper Accepted (IEEE Sensors Journal): Interaction Force Estimation using Camera and Electrical Current without Force/Torque Sensor

US patent 등록 “Certification device and method using image sensor”, US10038867

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Certification device and method using image sensor Patent number: 10038867 Abstract: A mobile device method for certifying a mobile device includes: generating first fixed pattern noise (FPN) information based on column FPN of an image sensor included in the mobile device; and controlling the mobile device to perform a certification by using the first FPN information. Type: Grant… 더 보기 »US patent 등록 “Certification device and method using image sensor”, US10038867

Journal Paper 게재(Scientific Reports) : Mechanical Vibration Influences the Perception of Electrovibration

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Mechanical Vibration Influences the Perception of Electrovibration Semin Ryu, Dongbum Pyo, Soo-Chul Lim & Dong-Soo Kwon   Abstract Recently, various methods using, simultaneously, two types of tactile feedback have been proposed to emulate a real object. However, the possible masking effect when providing two types of tactile feedback has been scarcely reported. In this study,… 더 보기 »Journal Paper 게재(Scientific Reports) : Mechanical Vibration Influences the Perception of Electrovibration

Journal Paper 게재(Sensors) : Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

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Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System Hyundo Choi 1, Keehong Seo 1, Seungyong Hyung 1, Youngbo Shim 1 and Soo-Chul Lim 2,* Abstract In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered… 더 보기 »Journal Paper 게재(Sensors) : Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

Prof. Lim received Young Researcher Award from Korea Haptics community

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Prof. Lim received young researcher Award from Korea Haptics Community. 지난 11월 3일 금요일 임수철 교수가 한국 햅틱스(Haptics) 연구회의 햅틱스 워크샵에서 젊은 연구자 상(Yong Researcher Award)을 수상했다. 한국 햅틱스 연구회는 촉각 분야를 연구하는 연구자들의 한국 협회로서 햅틱스 분야에 공헌 및 발전에 기여한 학회원을 대상으로 1명을 선발해 젊은 연구자 상을 수여한다.

Journal Paper 게재(Sensors) : Inferring Interaction Force from Visual Information without Using Physical Force Sensors

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Inferring Interaction Force from Visual Information without Using Physical Force Sensors Wonjun Hwang, Soo-Chul Lim* Sensors, 17(11), 2455, 2017 Abstract: In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating… 더 보기 »Journal Paper 게재(Sensors) : Inferring Interaction Force from Visual Information without Using Physical Force Sensors