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Choi, Woosung,Yun, Inyeol,Jeung, Jinpyeo,Park, Yun Sung,Cho, Sunghwan,Kim, Dong Wook,Kang, In Seok,Chung, Yoonyoung,Jeong, Unyong Elsevier 2019 Nano energy Vol.56 No.-
<P><B>Abstract</B></P> <P>Human cutaneous tactile receptors are deformable, and can distinguish touch, strain, relative moving distance, and relative moving velocity. In addition, the tactile potential is self-activated when external stimulation is exerted and the potential is transmitted to the nerve system, resembling the wake-up function in electronic devices. In this study, we mimic such characteristics of the human tactile receptors. We designed a stretchable triboelectric nanogenerator (TENG) for the stimuli-responsive potential generator. The TENG device has a multilayer structure independently recognizing lateral strain by the sliding mode, touch by the contact mode, the relative moving distance, and the relative moving velocity. In addition, the device design allows simultaneous sensing of strain and touch without signal interference. The self-triggered potentials generated by various body motions such as touching, joint bending, and the combinations turn on a sleeping microcontroller unit (MCU) and are used as the distinct motion signals. This study demonstrates a wearable low-power remote tactile interface that controls the 3D movements of a mobile device (drone) by the body motions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The TENG sensor can distinguish pressure, strain, distance, velocity. </LI> <LI> The sensor can extract information from random dynamic motions. </LI> <LI> The integrated wearable haptic interface can control complex 3-D movement of a drone. </LI> <LI> The wake-up function is turned on or off by the sensor signal itself. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Multi-Functional Brain Computer Interface Using Convolutional Neural Networks
Woosung Choi,Honggi Yeom,Nakyong Ko 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Brain-computer interface (BCI) is a promising technology that controls computers or machines using brain signals. With this technology, people with various disabilities, such as neural paralysis, and spinal cord injury can control electric devices or express their intention by thinking. However, previous BCI studies have a limitation that they can predict only one type of intention. To use the BCI system in daily life, the BCI user should be able to achieve various tasks such as moving, text typing, and arm movements. In this paper, we propose a multi-functional BCI method that can predict various intentions simultaneously. To classify multiple intentions, we proposed two prediction models using Neural Networks (NN) and Convolutional Neural Networks (CNN) models. To evaluate the proposed BCI system, the classification accuracy of the model was measured and compared using steady state visually evoked potential (SSVEP), sensory motor rhythm (SMR), and both of them (Multiple Intention). The average prediction accuracies were 22.46% in NN, 55.86% in CNN. These results indicate that the proposed multi-functional BCI can predict multiple intentions. It also means that users of the proposed BCI system can control various electric devices simultaneously.
Choi, Woosung,Youn, Byeng D.,Oh, Hyunseok,Kim, Nam H. Elsevier 2019 Reliability engineering & system safety Vol.184 No.-
<P><B>Abstract</B></P> <P>Accurate prediction of the remaining useful life (RUL) of plant turbines is a major scientific challenge for effective operation and maintenance in the power plant industry. This paper proposes an RUL prediction methodology that incorporates a damage index into the damage growth model. A Bayesian inference technique is used to consider uncertainties while estimating the probability distribution of a damage index from on-site hardness measurements. A Bayesian approach is proposed for the damage growth model for use with aged steam turbines. The predictive distribution of the damage index is estimated using its mean and standard deviation. As a case study, real steam turbines from power plants are examined to demonstrate the effectiveness of the proposed Bayesian approach. The results from the proposed damage growth model can be used to predict the RULs of the steam turbines of power plants regardless of load types (peak-load or base-load) of the power plant.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A damage growth model for a steam turbine is proposed from the damage index distribution. </LI> <LI> RUL prediction methodologies incorporate the damage index into damage growth model estimation. </LI> <LI> A Bayesian inference technique is used to estimate the probability distribution of the damage index. from on-site measurements sporadically measured and heterogeneous on-site data from actual steam turbines </LI> <LI> Damage index is estimated from on-site measurements sporadically measured and heterogeneous on-site data from actual steam turbines. </LI> <LI> A damage threshold of 0.2 is determined for a reasonable damage distribution and RUL for a steam turbine. </LI> </UL> </P>
Modeling and Applications of Electrochemical Impedance Spectroscopy (EIS) for Lithium-ion Batteries
Choi, Woosung,Shin, Heon-Cheol,Kim, Ji Man,Choi, Jae-Young,Yoon, Won-Sub The Korean Electrochemical Society 2020 Journal of electrochemical science and technology Vol.11 No.1
As research on secondary batteries becomes important, interest in analytical methods to examine the condition of secondary batteries is also increasing. Among these methods, the electrochemical impedance spectroscopy (EIS) method is one of the most attractive diagnostic techniques due to its convenience, quickness, accuracy, and low cost. However, since the obtained spectra are complicated signals representing several impedance elements, it is necessary to understand the whole electrochemical environment for a meaningful analysis. Based on the understanding of the whole system, the circuit elements constituting the cell can be obtained through construction of a physically sound circuit model. Therefore, this mini-review will explain how to construct a physically sound circuit model according to the characteristics of the battery cell system and then introduce the relationship between the obtained resistances of the bulk (R<sub>b</sub>), charge transfer reaction (R<sub>ct</sub>), interface layer (R<sub>SEI</sub>), diffusion process (W) and battery characteristics, such as the state of charge (SOC), temperature, and state of health (SOH).
데이터 샘플링 기반 프루닝 기법을 도입한 효율적인 각도 기반 공간 분할 병렬 스카이라인 질의 처리 기법
최우성 ( Woosung Choi ),김민석 ( Minseok Kim ),( Gromyko Diana ),정재화 ( Jaehwa Chung ),정순영 ( Soonyong Jung ) 한국정보처리학회 2017 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.6 No.1
다기준 의사결정 시 활용할 수 있는 스카이라인 질의는 다수의 선택지 중에서 사용자가 `선호하지 않을 만한`(uninteresting) 선택지를 제거 함으로써 사용자가 검토해야 하는 선택지의 수를 대폭 감소시키기 때문에 대용량 데이터 분석 시 매우 유용하게 활용될 수 있다. 이러한 배경에서 대용량 데이터에 대한 스카이라인 질의를 분산ㆍ병렬 처리하는 기법이 각광을 받고 있으며, 특히 맵리듀스(MapReduce) 기반의 분산ㆍ병렬 처리 기법 연구가 활발히 진행되어 왔다. 맵리듀스 기반 알고리즘의 병렬성 제고를 위해서는 부하 불균등 문제ㆍ중복 계산 문제ㆍ과다한 네트워크 비용 발생 문제를 해소해야 한다. 본 논문에서는 부하 불균등 문제와 중복 계산 문제를 해소하면서도 데이터 샘플링 기반 프루닝을 통해 네트워크 비용 절감 시킬 수 있는 맵리듀스 기반 병렬 스카이라인 질의 처리 기법인 MR-SEAP(MapReduce sample Skyline object Equality Angular Partitioning)을 소개한다. 또한 다양한 관점에서의 실험 평가함으로써 제안 기법의 효용성을 다방면으로 검증했다. Given a multi-dimensional dataset of tuples, a skyline query returns a subset of tuples which are not `dominated` by any other tuples. Skyline query is very useful in Big data analysis since it filters out uninteresting items. Much interest was devoted to the MapReduce-based parallel processing of skyline queries in large-scale distributed environment. There are three requirements to improve parallelism in MapReduced-based algorithms: (1) workload should be well balanced (2) avoid redundant computations (3) Optimize network communication cost. In this paper, we introduce MR-SEAP (MapReduce sample Skyline object Equality Angular Partitioning), an efficient angular space partitioning based skyline query processing using sampling-based pruning, which satisfies requirements above. We conduct an extensive experiment to evaluate MR-SEAP.
호텔종사원이 지각한 상사의 감성역량이 이직의도에 미치는 영향에 있어 LMX의 조절효과
최우성 ( Woosung Choi ) 관광경영학회 2021 관광경영연구 Vol.101 No.-
This study verified the effect of the emotional competency of the bosses perceived by hotel employees on turnover intention and the moderating effect of LMX in these relationships. As a result, the following results were obtained. First, as a result of verifying the relationship between the emotional competency of the boss on turnover intention, it was found that only the attitude competency of the emotional competency of the boss had a negative effect on the turnover intention. It was found that if the boss is achievement-oriented to seek new opportunities while overcoming difficulties, it is positive in self-awareness and evaluation, and has the ability to control his impulsive emotions, the intention to turnover decreases. Second, as a result of verifying the moderating effect of LMX in the relationship between the boss's emotional competency and turnover intention, it was found that LMX showed a moderating effect in the relationship between the attitude competency and turnover intention among the emotional competency of the boss. In other words, it was found that a higher perception of the boss's attitude capability and a high perception of the LMX at the same time resulted in lower turnover intention. Therefore, it will be necessary to strengthen the attitude competency among the boss's emotional competencies, and to make the superior-subordinate relationship a friendly relationship and the support of the organization.