• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.173-180
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• 2003

This paper proposes Remote Educating Communication Tool (RECT) that allows students and teachers to communicate using Web-based Bulletin Board System. The distance teaching using DCOM (Distributed Component Object Model) voice module is used to enhance academic accomplishments for students in computer class. The DCOM voice module to be used in distance learning is designed, implemented and applied to teachers and students in the computer class in order to measure and analyze academic results. The RECT server provides Q&A sessions between students and teachers in the BBS using recording and playback functions. The client RECT includes recording and playback functions. The client module of RECT receives and uses DCOM module. When recording, the client transmits voice files with the recorded content to the server.

• Korea Information Processing Society Review
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• v.11 no.6
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• The Journal of Pediatrics of Korean Medicine
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• v.21 no.3
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• pp.85-95
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• 2007

Objectives Attention Deficit Hyperactivity Disorder(ADHD) is a type of psychiatric disorder characterized with the primary symptoms of inattention and/or impulsivity and hyperactivity. The purpose of this study is to examine ADHD children who were treated with neurofeedback therapy. Methods We analyzed clinical report of 3 ADHD children who treated with neurofeedback therapy from January 2006 to June 2006. Results 1. All 3 children were diagnosed with predominantly inattention type of ADHD. 2. After treatment, cognitive strength, response, concentration, workload, left / right brain activity score were all different from each children. 3. After treatment, left and right brain activities were balanced. 4. After treatment, learning ability level was increased. 5. After treatment, the childrenwere in a better state referred to conner's scale and H.S.Q. score. Conclusions Further studies will be needed to get more clinical cases about the benefits of neurofeedback therapy with herbal medicine and acupuncture treatment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.397-400
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• 2011

본 논문은 로봇 교육에 대한 연구의 동향 파악을 목적으로 학술연구정보서비스(RISS)를 활용하여 2000년부터 2011년까지 발간된 로봇 교육관련 국내학술지논문 119개를 분석하였다. 구체적인 조사 영역은 활용된 로봇의 종류, 연도별 논문 발행 수, 주제, 연구 대상, 적용교과, 연구방법으로 나누고 가장 많이 다루어지고 있는 연구 부분을 파악하였다. 주로 각 논문의 초록을 면밀히 분석하였으며 모호하다고 생각이 들 경우에는 논문 내용을 확인하였다. 연구 결과 로봇 교육 관련 연구는 해가 갈수록 증가하는 추세에 있으며 연구 방법으로는 양적 연구가 주를 이루지만 2007년 이후 질적 연구와 통합 연구 또한 증가하고 있었고, 로봇은 21가지 중에 주로 사용되는 것이 NXT와 피코 크리켓, iRobiQ였다. 연구 주제는 고차원적인 사고와 정서적인 측면을 측정하는 로봇 활용 교육이 다수를 차지하였고, 대상은 주로 초등학생에 집중되어 있었다. 연구에 적용된 교과를 살펴보면 주로 정보교과와 재량활동이나 방과후 활동, 통합교육 순이었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.39-39
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• 2020

Low-flow 하천에서의 최저수위를 나타내는 지표이다. 일반적으로 유황곡선의 갈수량(Q355)를 대표적으로 사용한다. Low-flow는 물 공급 관리 및 계획, 관개용수, 생태계등 다양한 분야에 영향을 미친다. 이러한 Low-flow를 산정하기 위해서는 충분한 기간의 유량자료가 필요하다. 하지만 국토의 70%가 산지지형으로 구성되어 있는 우리나라의 경우 국가하천과 1급하천을 제외한 산지유역은 수위관측소가 부재하거나 결측으로 인해 자료가 충분하지 않아 Low-flow분석에 한계가 있다. 이에 과거에는 미계측지역의 갈수량을 예측하기 위해서 다중회귀분석, ARIMA 모형 등 다양한 기법을 사용하였지만, 최근들어 머신러닝 모형의 수요가 증가하고 있다. 이에 본 연구에서는 새로운 패러다임에 맞는 머신러닝 기법인 DNN기법을 사용하고자 한다. DNN기법은 ANN기법의 단점인 학습과정에서 최적 매개변수값을 찾기 어렵고, 학습시간이 느린 단점을 보완한 방법이다. 따라서 본연구에서는 머신러닝 기법인 DNN기법을 통해 미계측지역에 적용 가능한 지역화 Low-flow indices를 산정하고자 한다. 먼저, Low-flow에 영향을 미치는 인자들을 수집하고 인자들간의 상관분석, 다중공선성 분석을 통해 통계적으로 유의한 변수를 선정하여, 머신러닝 모형에 입력자료를 구축하였다. 또한 기존의 갈수량 예측기법인 다중회귀분석 결과와 비교하여 머신러닝 기법의 효용성을 검토하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.819-822
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• 2021

AI World Cup 환경은 다수 가상 에이전트들이 팀을 이뤄서 서로 상호작용하며 대전이 가능한 가상 축구 환경이다. 본 논문에서는 AI World Cup 환경에서 멀티 에이전트기반 학습/추론 기술을 사용하여 다양한 전략과 전술을 구사하는 가상 축구 에이전트 구현과 시뮬레이션 결과를 소개한다. 먼저, 역할을 바탕으로 협동하여 상대방과 대전할 수 있는 논리 기반 추론형 멀티 에이전트 기술이 적용된 Dynamic planning 축구 에이전트 9 세트를 구현하였다. 이후, 강화학습 에이전트 기반, 단일 에이전트를 조합한 Independent Q-Learning 방식의 학습형 축구 에이전트를 구현한 후, 이를 멀티 에이전트 강화학습으로 확장하여 역할 기반 전략 학습이 가능한 가상 축구 에이전트를 구현하고 시뮬레이션 하였다. 구현된 가상 축구 에이전트들 간 대전을 통해 승률을 확인하고, 전략의 우수성을 분석하였다. 시뮬레이션 예제는 다음에서 확인할 수 있다 (https://github.com/I-hate-Soccer/Simulation).

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.62-74
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• 2023

In response to diverse external stimuli, sensory receptors generate spiking nerve signals. These generated signals are transmitted to the brain along the neural pathway to advance to the stage of recognition or perception, and then they reach the area of discrimination or judgment for remembering, assessing, and processing incoming information. We review research trends in neuromorphic sensory perception technology inspired by biological sensory perception functions. Among the various senses, we consider sensory nerve decoding technology based on sensory nerve pathways focusing on touch and smell, neuromorphic synapse elements that mimic biological neurons and synapses, and neuromorphic processors. Neuromorphic sensory devices, neuromorphic synapses, and artificial sensory memory devices that integrate storage components are being actively studied. However, various problems remain to be solved, such as learning methods to implement cognitive functions beyond simple detection. Considering applications such as virtual reality, medical welfare, neuroscience, and cranial nerve interfaces, neuromorphic sensory recognition technology is expected to be actively developed based on new technologies, including combinatorial neurocognitive cell technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.

• Journal of Distribution Research
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• v.15 no.4
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown