• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.85-91
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• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1346-1357
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• 2021

The drone technology, which is receiving a lot of attention due to the 4th industrial revolution, requires an Unmanned Aerial Vehicles'(UAVs) flight path search algorithm for automatic operation and driver assistance. Various studies related to flight path prediction and recommendation algorithms are being actively conducted, and many studies using the A-Star algorithm are typically performed. In this paper, we propose an Optimal 3D Flight Path Recommendation System for unmanned aerial vehicles. The proposed system was implemented and simulated in Unity 3D, and by indicating the meaning of the route using three different colors, such as planned route, the recommended route, and the current route were compared each other. And obstacle response experiments were conducted to cope with bad weather. It is expected that the proposed system will provide an improved user experience compared to the existing system through accurate and real-time adaptive path prediction in a 3D mixed reality environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.852-853
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• 2016

In this paper, we propose a profile design of customized sports content curation system for activating daily sports. The proposed profile is a system that recommends sports convergence contents in everyday life tailored to the characteristics of profile in terms of the individual and team. Especially, the proposed profile is designed as the static profile that is changed depending on the user's feedback. The proposed design of profile design are to improve the happiness and health of individuals, it is expected to contribute the new service model development of in the field of Sport for All.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.302-304
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• 2016

In this paper, we propose the profile processing algorithm based on in-life sports contents. The proposed algorithm is required research for recommending to sport for all contents, and is preceding research to improve reliability of recommendation. So the proposed algorithm processing dynamic profile based on dynamic information for recommendation, and processing weight values that depending on dynamic recommendation classification. The proposed profile processing algorithm is expected to improve satisfaction of contents recommendation.

• Atmosphere
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• v.32 no.3
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• pp.247-261
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• 2022

The importance of ozone monitoring has been growing due to the polar ozone depletion and increasing tropospheric ozone concentration over many Asian countries, including South Korea. In-situ measurement of the vertical ozone structure has advantages for ozone research, but observations are not sufficient. In this study, ozonesonde measurements were performed from October to November in Yongin during the GMAP (The GEMS Map of Air Pollution) 2021 campaign. The procedure for ozonesonde preparation and initial analysis of the observed ozone profile are documented. The observed ozone concentrations are in good agreement with previous studies in the troposphere, and they capture the stratospheric ozone distribution as well, including stratosphere-troposphere exchange event. These balloon-borne in situ measurements can contribute to the evaluation of remote sensing measurements such as Geostationary Environment Monitoring Spectrometer (GEMS). This document focuses on providing essential information of ozonesonde preparation and measurement for domestic researchers.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.237-246
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• 2022

Among the technologies of the 4th industrial revolution, drones that have grown rapidly and are being used in various industries can be operated by the pilot directly or can be operated automatically through programming. In order to be controlled by a pilot or to operate automatically, it is essential to predict and analyze the optimal path for the drone to move without obstacles. In this paper, after securing and analyzing the pilot training dataset through the unmanned aerial vehicle piloting training platform designed through prior research, the profile of the dataset that should be preceded to search and derive the optimal route of the unmanned aerial vehicle was designed. The drone pilot training data includes the speed, movement distance, and angle of the drone, and the data set is visualized to unify the properties showing the same pattern into one and preprocess the properties showing the outliers. It is expected that the proposed big data-based profile can be used to predict and analyze the optimal movement path of an unmanned aerial vehicle.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1109-1121
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• 2022

As the demand for quality sleep increases in modern society, the importance of sleep technology has increased. Recently, development of sleep environment improvement products and research on the user's sleep improvement have been activated. Representatively, user sleep pattern analysis research is being conducted through the existing polysomnography, but it is difficult to use it in the sleep environment of daily life. Therefore, in this paper, we propose a system design that can provide a customized deep sleep service to users by detecting sleep disturbance factors in a motion bed environment. In order to improve the user's sleep satisfaction, a logistic regression-based sleep pattern analysis model is proposed and accuracy and significance are verified through experiments. And to improve user's sleep satisfaction, we propose a logistic regression-based sleep pattern analysis model and verify accuracy and significance through experiments. The proposed system is expected to improve the user's sleep quality and effectively prevent and manage sleep disorders.

• Journal of Environmental Health Sciences
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• v.49 no.1
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• pp.1-10
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• 2023

Low-dose radiation exposure has received considerable attention because it reflects the general public's type and level of exposure. Still, controversy remains due to the relatively unclear results and uncertainty in risk estimation compared to high-dose radiation. However, recent epidemiological studies report direct evidence of health effects for various types of low-dose radiation exposure. In particular, international nuclear workers' studies, CT exposure studies, and children's cancer studies on natural radiation showed significantly increased cancer risk among the study populations despite their low-dose radiation exposure. These studies showed similar results even when the cumulative radiation dose was limited to an exposure group of less than 100 mGy, demonstrating that the observed excess risk was not affected by high exposure. A linear dose-response relationship between radiation exposure and cancer incidence has been observed, even at the low-dose interval. These recent epidemiological studies include relatively large populations, and findings are broadly consistent with previous studies on Japanese atomic bomb survivors. However, the health effects of low-dose radiation are assumed to be small compared to the risks that may arise from other lifestyle factors; therefore, the benefits of radiation use should be considered at the individual level through a balanced interpretation. Further low-dose radiation studies are essential to accurately determining the benefits and risks of radiation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.186-186
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• 2022

강수 및 침투 등으로 발생하는 지하수위의 변동을 예측하는 것은 지하수 자원의 활용 및 관리에 필수적이다. 지하수위의 변동은 지하수 자원의 활용 및 관리뿐만이 아닌 홍수 발생과 지반의 응력상태 등에 직접적인 영향을 미치기 때문에 정확한 예측이 필요하다. 본 연구는 인공신경망 중 다층퍼셉트론(Multi Layer Perceptron, MLP)을 이용한 지하수위 예측성능 향상을 위해 MLP의 구조 중 Optimizer를 개량하였다. MLP는 입력자료와 출력자료간 최적의 상관관계(가중치 및 편향)를 찾는 Optimizer와 출력되는 값을 결정하는 활성화 함수의 연산을 반복하여 학습한다. 특히 Optimizer는 신경망의 출력값과 관측값의 오차가 최소가 되는 상관관계를 찾는 연산자로써 MLP의 학습 및 예측성능에 직접적인 영향을 미친다. 기존의 Optimizer는 경사하강법(Gradient Descent, GD)을 기반으로 하는 Optimizer를 사용했다. 하지만 기존의 Optimizer는 미분을 이용하여 상관관계를 찾기 때문에 지역탐색 위주로 진행되며 기존에 생성된 상관관계를 저장하는 구조가 없어 지역 최적해로 수렴할 가능성이 있다는 단점이 있다. 본 연구에서는 기존 Optimizer의 단점을 개선하기 위해 지역탐색과 전역탐색을 동시에 고려할 수 있으며 기존의 해를 저장하는 구조가 있는 메타휴리스틱 최적화 알고리즘을 이용하였다. 메타휴리스틱 최적화 알고리즘 중 구조가 간단한 화음탐색법(Harmony Search, HS)과 GD의 결합모형(HS-GD)을 MLP의 Optimizer로 사용하여 기존 Optimizer의 단점을 개선하였다. HS-GD를 이용한 MLP의 성능검토를 위해 이천시 지하수위 예측을 실시하였으며 예측 결과를 기존의 Optimizer를 이용한 MLP 및 HS를 이용한 MLP의 예측결과와 비교하였다.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.2
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• pp.1-9
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• 2012

Applicability of regenerative cooling in 2,500 N-class bipropellant thruster using hydrogen peroxide and kerosene was considered for improvement of performance and application in various missions. Calculation was performed by one dimensional approach using hydrogen peroxide as a coolant. The heat flux of thruster at nozzle throat was estimated at 18 - 20 MW/$m^2$. Designed cooling channel width and height were 2.5 mm and 0.5 mm, respectively. Based on designed cooling channel configuration, flat plate model was manufactured and tested for estimation of pressure drop in cooling channel, and CFD analysis was compared with the test result. The maximum error between CFD analysis and experimental result was approximately 13% and average error was approximately 5%.