• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.307-308
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• 2019

본 논문은 기존에 시장에 출시된 선풍기에 아두이노(Arduino)를 기반으로 특수기능을 추가하여 스마트 선풍기를 설계하고 시제품을 제작하였다. 제안된 스마트 선풍기의 주요 기술적 기능은 온.습도 센서(temperature-humidity sensor)를 사용하여 온도와 습도를 측정하여 간접적인 불쾌지수를 계산하고, 불쾌감의 정도가 낮아질 때 까지 자동으로 전원을 제어하도록 하였다. 또한 수면의 질 향상을 위해 원하는 작동 시간 설정이 가능하도록 전원제어, 회전, 타이머 기능을 가지도록 하였다. 이러한 기능들을 블루투스(Bluetooth)를 통해 스마트 기기로 선풍기의 조작을 가능하게 하여 편의성을 높였다. 제작된 스마트 선풍기 시제품을 스마트폰 어플로 동작을 성공적으로 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.279-280
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• 2009

스마트 의류는 일상생활에 필요한 IT기술을 이용한 디지털 장치와 섬유 패션기술을 융합시킨 차세대 하이테크 기능성 의류이다. 이는 소비자의 라이프스타일의 변화와 인간 중심의 감성을 중시한 디자인의 요구에 따라 여러 분야에서 다양하게 연구 개발되고 있다. 본 논문에서는 실시간 기상지수 제공을 위한 웨어러블 기반의 스마트 의류를 개발하고자 하였다. 착용자가 평소 자주 쓰는 의류를 응용하여 답답해하거나 불편하지 않게 스포츠 의류의 형태에 따라 제작하였다. 온도, 조도, 습도, 자외선을 감지하여 분석한 후 기상청에서 제공하는 생활기상지수를 응용하여 자외선지수, 체감온도지수, 불쾌지수, 열지수의 기상지수를 서비스한다. 개발된 웨어러블 기반의 스마트 의류는 외관 형태는 그대로 유지하고 착용성을 높였다. 기상지수는 실시간으로 무선 전송되어 이를 모니터링하게 된다. 제안된 방법에 대해서 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다.

• Journal of IKEEE
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• v.26 no.1
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• pp.56-61
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• 2022

Various efforts have been made worldwide to respond to environmental problems such as climate change. Research on artificial intelligence (AI)-based energy management has been widely conducted as the most effective way to alleviate the climate change problem. In particular, buildings that account for more than 20% of the total energy delivered worldwide have been focused as a target for energy management using the building energy management system (BEMS). In this paper, we propose a multi-armed bandit (MAB)-based energy management algorithm that can efficiently decide the energy consumption level of the lighting system in each room of the building, while minimizing the discomfort levels of occupants of each room.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.143-148
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• 2024

Traffic congestion has caused issues in various forms such as the environment and economy. Recently, an intelligent transport system (ITS) using artificial intelligence (AI) has been focused so as to alleviate the traffic congestion problem. In this paper, we propose a reinforcement learning-based traffic signal control algorithm that can smooth the flow of traffic while reducing discomfort levels of drivers and pedestrians. By applying the proposed algorithm, it was confirmed that the discomfort levels of drivers and pedestrians can be significantly reduced compared to the existing fixed signal control system, and that the performance gap increases as the number of roads at the intersection increases.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.73-78
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• 2001

BP neural network model and multiple-regression model were composed for forecasting the special-days load. Special-days load was forecasted using that neural network model made use of pattern conversion ratio and multiple-regression made use of weekday-change ratio. This methods identified the suitable as that special-days load of short and long term was forecasted with the weekly average percentage error of 1∼2[%] in the weekly peak load forecasting model using pattern conversion ratio. But this methods were hard with special-days load forecasting of summertime. therefore it was forecasted with the multiple-regression models. This models were used to the weekday-change ratio, and the temperature-humidity and discomfort-index as explanatory variable. This methods identified the suitable as that compared forecasting result of weekday load with forecasting result of special-days load because months average percentage error was alike. And, the fit of the presented forecast models using statistical tests had been proved. Big difficult problem of peak load forecasting had been solved that because identified the fit of the methods of special-days load forecasting in the paper presented.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.5
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• pp.29-43
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• 2020

Thermal environment of city is getting worse due to severe urban heat island caused by climate change and urbanization. The cooling effect of street tree is regarded as a effective way to ameliorate the urban heat environment. The effect is largely made up of shadow formation and transpiration. This study aims to identify how the transpiration affects the discomfort index by analyzing comprehensive impact of the transpiration on the air temperature and relative humidity. The changes in the amount of transpiration, air temperature, and relative humidity were estimated for Seogyo-dong area which has a lot of floating population in Seoul, at 2 p.m. in dry day in July and August. On average, the transpiration of the street tree decreased the temperature 0.3℃ and increased the relative humidity 2.6% in an hour. As a result of these changes in temperature and humidity, the discomfort index rose mostly(0.036 on average). It was always get rise especially on the day when the discomfort index was above 80(0.05 on average). However, compared with the significant change in temperature and humidity, the variation of the discomfort index itself was very slight(up to 0.107). Therefore, the effect of transpiration by the street trees might not be effective in the planning to improve the thermal environment(especially on the day when the discomfort index is high). It is necessary to select the species of trees and planting location considering the cooling effect of shade formation synthetically.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.7-15
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• 2008

The paper proposes information system for providing proper well known delicious restaurants as interactions with users. The system calls 'Moloke', which is an agent for recommending sensitive information on mobile environment The proposing agent differs from existing ones that guide the telephone number and the name of the restaurant. The differences are as following goals. First, the agent gets existing from users as interactive communications on mobile devices through the proper requests on each time zone such as morning, afternoon, and evening. Second, the agent also can recommend a specific restaurant for current personal states such as parties, special community meetings, bio-rhythms and so on. Among them, specially the bio-rhythm is used for recommending proper restaurants to each user. In addition to through proposal suitable design for the mobile agent design more effectively. The research used mobile environment for recommendation service and web environment for data management. Server environment for service used Apache, PHP4, Mysql and mobile page was implemented m-html for approach. Mobile Service was optimized Mozilla-1.22, KUN-1.2.3 Browser

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1785-1790
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• 2016

There is exhibit a degree of pain in the occurrence and course of treatment levels or oral, pain rating scale actions, such as illness, for example, the discomfort scale because of the pain "annoying", "unpleasant" "annoyed am", "painful" represents a pain scale of the order of "painful", "hard to bear", "very difficult to bear". Depression is recognized based on the premise of the situation, because it is difficult to recognize themselves. In this paper we define the components of the depression can be seen lifestyle which can lead to depression or through a biological signal. The depression index was derived from the ontology modeling to understand the state of depression. Depression ontology components and depression index will be aware of the situation based information services for depression. Combined with the situational awareness based devices and can be synchronized to verify the results of the depression index. It will be applied to improve lifestyle factors that of depression.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.477-484
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• 2009

It is important for the strategy of service to provide the weather information in the environment that the smart clothing has been changed focusing on the consumer center. Recently, the various applications of smart clothing concept have been presented by researchers and developers. Among them, the smart clothing based on the sensors is most likely to gain the highest demand rate in the market. In this paper, we proposed the life weather index monitoring system using the wearable based smart cap. By wearing the proposed smart cap, the weather status is gathered and its signals are transmitted to the connected UMPC. It can be easily monitored in real time. To provide the life weather index according to the sensors, the weather index was analyzed in terms of 6 factors, such as, the heat index, the food poisoning index, the discomfort index, the ultraviolet index, the water pipe freeze possibility index, and the windchill temperature index. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the life weather index monitoring system. Accordingly, the satisfaction and the quality of services will be improved the smart clothing.

• Journal of the Korean Chemical Society
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• v.44 no.4
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• pp.343-349
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• 2000

Volatile Organic Compounds(VOCs) emitted form electronicSince toluene, xylene, cyclohexanone, and benzofuran will bring on the deleterious smell and the health risk, eventhough very small amount of these areexposed to human body, quantitative analysis was achieved by GC-MS system. As a result of these analyses, except PCB(CEM-1) of which is one of the electronic parts, the left of electronic parts represented, imme-diately form 30 minutes to 1 hour after heating, the trends that toluene, xylene, cyclohexanone and phenol were consecuticely emitted very high. and toluene, xylene, phenol, cyclohexanone, and benzofuran from most of the electronic parts were emitted very frequently within the measuring period. Finally, Trans of electronic parts showed the highest concentration of emission, and xylene(550~2482 ${\mu}g/m^2$) was the most noticeably emitting compound of VOCs.