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182 results on '"Kim, Moon-Hwan"'

9. Hybrid Silhouette Extraction Method for Detecting and Tracking the Human Motion

Author

Kim, Moon Hwan, Park, Jin Bae, Ra, In Ho, Joo, Young Hoon, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Jiao, Licheng, editor, Wang, Lipo, editor, Gao, Xinbo, editor, Liu, Jing, editor, and Wu, Feng, editor

Published
2006
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11. Design of T–S Fuzzy Classifier via Linear Matrix Inequality Approach

Author

Kim, Moon Hwan, Park, Jin Bae, Joo, Young Hoon, Lee, Ho Jae, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Wang, Lipo, editor, and Jin, Yaochu, editor

Published
2005
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12. Identification of T–S Fuzzy Classifier Via Linear Matrix Inequalities

Author

Kim, Moon Hwan, Park, Jin Bae, Kim, Weon Goo, Joo, Young Hoon, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Zhang, Shichao, editor, and Jarvis, Ray, editor

Published
2005
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13. New Fuzzy Skin Model for Face Detection

Author

Kim, Moon Hwan, Park, Jin Bae, Joo, Young Hoon, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Zhang, Shichao, editor, and Jarvis, Ray, editor

Published
2005
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18. Perioperative and oncologic outcomes of minimally-invasive pancreatoduodenectomy comparing the surgical methods: Robot-assisted vs. totally laparoscopic pancreatoduodenectomy

Author

KANG, Jae Seung, primary, LEE, Jun Suh, additional, SOHN, Hee Ju, additional, LEE, Mirang, additional, HAN, Youngmin, additional, LEE, Boram, additional, KIM, Moon-Hwan, additional, KIM, Hongbeom, additional, KWON, Wooil, additional, HAN, Ho-Seong, additional, YOON, Yoo-Seok, additional, and JANG, Jin-Young, additional

Published
2022
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20. Comparison of Shoulder Protraction Strength and Electromyography Activity of Serratus Anterior and Pectoralis Major in Subjects With or Without a Winged Scapula.

Author

Kim, Jun-Seok, Kim, Moon-Hwan, Ahn, Duk-Hyun, and Oh, Jae-Seop

Subjects
*ELECTROMYOGRAPHY, *EXERCISE, *LABORATORIES, *MUSCLE contraction, *MUSCLE strength, *POSTURE, *RESEARCH funding, *SCAPULA, *SHOULDER, *T-test (Statistics), *TRAPEZIUS muscle, *STATISTICAL power analysis, *DELTOID muscles, *PECTORALIS muscle, *CROSS-sectional method, *DATA analysis software, *DESCRIPTIVE statistics, *SERRATUS anterior muscles
Abstract

Context: A winged scapula (WS) is associated with faulty posture caused by weakness of the serratus anterior (SA), which mainly acts as a scapular stabilizer muscle. It is important to accurately assess and train the SA muscle with a focus on scapula stabilizers during musculoskeletal rehabilitation of individuals with a WS. Objective: The authors examined muscle activity in the SA and pectoralis major (PM), upper trapezius (UT), and anterior deltoid (AD) as well as shoulder protraction strength during isometric shoulder protraction in individuals with and without a WS. Design: Cross-sectional study. Setting: A clinical biomechanics laboratory. Participants: In total, 27 males with no shoulder, neck, or upper-extremity pain participated. Main Outcome Measures: Isometric shoulder protraction strength was collected and surface electromyography used to measure the activity of the SA, PM, UT, and AD muscles and selective SA activity ratio to other shoulder muscles. Results: Electromyography activity of the SA muscle and shoulder protraction strength were significantly lower in individuals with a WS compared with the non-WS group (P <.05). In contrast, PM muscle activity and the PM-to-SA, UT-to-SA, and AD-to-SA ratios were significantly greater in individuals with a WS than in individuals without winging (P <.05). Conclusions: Isometric shoulder protraction for measuring SA strength in individuals with a WS should focus on isolated muscle activity of the SA, and SA strengthening exercises are important for individuals with a WS. [ABSTRACT FROM AUTHOR]

Published
2019
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32. Mine and Mine like Objects Classification Through Deep Learning Neural Network Systems

Author

Joung, Sang Ki, Song, Kwang Sub, Kim, Moon Hwan, Chu, Peter, and Naval Ocean Analysis and Prediction Lab

Abstract

CRUSER TechCon 2018 Research at NPS. Wednesday 1: Sensing Threats of sea mines are increasing due to recent technology development, such as autonomous systems and computer systems with artificial intelligent capability. There are many solutions to solve MCM problems as far as difficulties to detect identify and classification. Unmanned systems integrated with emerging technologies are the minesweepers and hunters of the future MCM operations. A focused technology effort needed to incorporate unmanned systems into the mine countermeasure ship and other related MCM fleet forces. In MCM operation, it has several due sequences; identification location, neutralization and analysis. In this study, we try to use deep learning AI technique to identify, classify, and locate mines, so that lead to programming decisions allowing mine hunting and minesweeping missions to perform without a man onboard, eliminating the risk to personnel. Most of data and information for mine detection are acquired as form of image pixel from size scan sonar or bathometry sonar. However, detection of mine from sonar image is not easy to perform because sonar image has low resolution, shadows of different shape or size and complexity of ocean environment. There are plenty of Identification and Classification Algorithms using up to date Deep Learning Method that requires huge training data and Processing Hard Ware with Graphic Processor Unit. AI system needs long training time for Neural Networks tuning, but mine and mine like object and their respective SONAR signal data are few and restrictive to access We select faster regional CNN deep learning neural network as deep learning network for mine classifications, but it needs long processing time and data for signal from minefield. Deep learning functional process are largely divided by region selection and classification sequences, and applying AI process to region selection require more time than well-defined classification process. In this works, we separate Region of Interest selection processing from whole Deep Learning Package for Mine Classification. Region of Interest are selected by combined identification process with simple model referenced CNN circuit, Tactical Mine Database, Environmental Condition probability and SONAR signal processing, which give much fast processing time. Selected regions of interest (ROI) provide through well-established Faster R-CNN Package for Classifications Efficiency test and accuracy test are to compare other deep learning classification packages and give a better accuracy and computation time. We normally check classification accuracy from trained data and non-trained (blind) data from mine warfare databases.

Published
2018

38. Comparison of maximal isometric forearm supination torque in two elbow positions between subjects with and without limited forearm supination range of motion.

Author

Gwak, Gyeong-Tae, Hwang, Ui-Jae, Jung, Sung-Hoon, Kim, Jun-Hee, Kim, Moon-Hwan, and Kwon, Oh-Yun

Subjects
ELBOW physiology, ANALYSIS of variance, CEREBRAL dominance, COMPARATIVE studies, CONFIDENCE intervals, FOREARM, RANGE of motion of joints, RESEARCH evaluation, SPLINTS (Surgery), T-test (Statistics), TORQUE, WEARABLE technology, SUPINATION, BODY movement, REPEATED measures design, CROSS-sectional method, CASE-control method, MOTION capture (Human mechanics), DATA analysis software, INTRACLASS correlation
Abstract

Study Design: Cross-sectional comparison. Introduction: Forearm supination range of motion is often limited by short or stiff pronators. Many studies have examined maximal isometric forearm supination torque (MIFST). However, there is little research comparing MIFST in two elbow positions between subjects with and without limited forearm supination range of motion (LSR). Purpose of the Study: The purpose of this study was to compare MIFST in two elbow positions (90º flexed elbow, extended elbow) between subjects with and without LSR. Methods: Thirteen right-handed subjects (seven men, six women) with LSR and 13 age- and gender-matched healthy controls participated in this study. The forearm supination range of motion and MIFST were measured using a Smart KEMA system. Two-way repeated-measures analysis of variance was used to compare MIFST in two elbow positions between subjects with and without LSR. Results: No significant difference between groups (p >.05) was found. However, there was an interaction effect between elbow position and group on MIFST (p <.05). Independent t-tests were used to confirm the simple effects. In the LSR group, the value of MIFST was significantly lower in the elbow-extended position than in the group without LSR (p <.05). Conclusions: These findings indicate that elbow position should be considered when assessing the strength or increasing the strength of the supinator muscle, especially in patients with LSR. [ABSTRACT FROM AUTHOR]

Published
2021
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49. Effect of applying consistent pressure to the stationary and the moving arm on measurement reliability of glenohumeral internal rotation range of motion.

Author

Hwang, Ui-jae, Kwon, Oh-yun, Jeon, In-cheol, Jung, Sung-hoon, and Kim, Moon-hwan

Subjects
ANALYSIS of variance, ARM, CONFIDENCE intervals, RANGE of motion of joints, PRESSURE, PROBABILITY theory, STATISTICS, DATA analysis, GLENOHUMERAL joint, BODY movement, ACCELEROMETRY, INTER-observer reliability, SMARTPHONES, MEASUREMENT of angles (Geometry), DATA analysis software, DESCRIPTIVE statistics, EVALUATION
Abstract

Objectives: The aim of this study was to determine the inter-rater reliability of glenohumeral internal rotation (GIR) range of motion (ROM) and pressure measurements among four measurement methods: (1) Manual stabilization of the humeral head and coracoid process (MSHC) without applying consistent pressure (ACP) to both the stationary and the moving arms (BSaMA); (2) MSHC with ACP to the moving arm; (3) MSHC with ACP to the stationary arm; and (4) MSHC with ACP to BSaMA. Design: Test-retest analyses. Participants: 39 subjects with GIR deficit. Main outcome measures: GIR ROM and pressure were measured on the stationary or moving arm by four examiners using the Clinometer application and a pressure biofeedback unit. Results: GIR ROM measurement with MSHC and ACP to the moving arm resulted in the lowest intra-class correlation coefficient (ICC = .43); the ICC for MSHC without ACP to BSaMA was.54; that for MSHC with ACP to the stationary arm was.77; and that for MSHC with ACP to BSaMA was highest, at.81. Conclusion: MSHC with ACP to both arms leads to reliable GIR ROM measurement in a clinical setting. [ABSTRACT FROM AUTHOR]

Published
2019
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50. Extraction of Human Body Using Hybrid Silhouette Extraction Method in Intelligent Robot System

Author

Kim Moon Hwan, Cho Young Jo, Park Jin Bae, Kim Hye Jin, Joo Young Hoon, and Chi Su Young

Subjects
Active contour model, Engineering, business.industry, Low resolution, Extraction (chemistry), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Silhouette, Vibration, Intelligent robots, Computer vision, Extraction methods, Artificial intelligence, business, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.

Published
2005

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