Dong W. Kim

Prof. Dong W. Kim

Department of Digital Electronics, Inha Technical College, 100 Inha-ro, Hagik 1(il)-dong, Nam-gu, Incheon, Korea
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 August 2019 in Applied Sciences
Verified
Journal Article
Open access
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MLMinSeop Lee
MinSeop Lee
YLyunkyu lee
yunkyu lee
DPDongsung Pae
Dongsung Pae
Myo-Taeg LimMyo-Taeg Lim
Myo-Taeg Lim
Dong W. KimDong W. Kim
Dong W. Kim
TKTae-Koo Kang
Tae-Koo Kang
Physiological signals contain considerable information regarding emotions. This paper investigated the ability of photoplethysmogram (PPG) signals to recognize emotion, adopting a two-dimensional emotion model based on valence and arousal to represent human feelings. The main purpose was to recognize short term emotion using a single PPG signal pulse. We used a one-dimensional convolutional neural network (1D CNN) to extract PPG signal features to classify the valence and arousal. We split the PPG signal into a single 1.1 s pulse and normalized it for input to the neural network based on the personal maximum and minimum values. We chose the dataset for emotion analysis using physiological (DEAP) signals for the experiment and tested the 1D CNN as a binary classification (high or low valence and arousal), achieving the short-term emotion recognition of 1.1 s with 75.3% and 76.2% valence and arousal accuracies, respectively, on the DEAP data.

1 January 2016 in Computational Intelligence and Neuroscience
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Journal Article
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JPJong-Wook Park
Jong-Wook Park
HKHwan-Joo Kwak
Hwan-Joo Kwak
YKYoung-Chang Kang
Young-Chang Kang
Dong W. KimDong W. Kim
Dong W. Kim
An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller—advanced fuzzy potential field method (AFPFM)—that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

2 March 2020 in Neural Processing Letters
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Journal Article
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JCJunho Chung
Junho Chung
Dong W. KimDong W. Kim
Dong W. Kim
TKTae-Koo Kang
Tae-Koo Kang
Myo-Taeg LimMyo-Taeg Lim
Myo-Taeg Lim

7 April 2011 in Nonlinear Dynamics
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Journal Article
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Dong W. KimDong W. Kim
Dong W. Kim
NKNak-Hyun Kim
Nak-Hyun Kim
GPGwi-Tae Park
Gwi-Tae Park

15 June 2013 in International Journal of Control, Automation, and Systems
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Journal Article
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Dong W. KimDong W. Kim
Dong W. Kim
TLTy A. Lasky
Ty A. Lasky
SVSteven A. Velinsky
Steven A. Velinsky

19 January 2017 in International Journal of Control, Automation, and Systems
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Journal Article
Closed access
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BKByeongsik Ko
Byeongsik Ko
JPJong-Wook Park
Jong-Wook Park
Dong W. KimDong W. Kim
Dong W. Kim