• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.63-70
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• 2008

This paper presents a method of PRI do-interleaving for LASER pulse signals. When the PRI of LASER pulse is periodically changed, the first deviation and the second deviation of TOA is used to calculate the PRI pattern of input LASER signals of receiver. If the standard deviation of the first difference of TOA is less than 5% of the average of the first difference of TOA, the PRI pattern of LASER signal is fixed or jittered type. If the standard deviation is larger than 5% of the average, those are triangular PRI patterns or sawtooth PRI patterns.

• Atmosphere
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• v.22 no.2
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.22-29
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• 2010

A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1409-1410
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• 2015

현대기술의 발달로 인해 인간의 삶 중 많은 부분을 기계가 차지하고 있다. 특히 로봇공학 분야는 위험하거나 혹은 매우 정밀함을 요하는 일, 단순반복 등 인간이 기피하거나 하기 어려운 일을 대신 해줌으로서 많은 관심을 받고 있다. 이에 우리는 우리 생활에 가장 깊숙히 들어와 있는 로봇팔분야에 대해 말하고자 한다. 현재 로봇팔은 산업용은 물론, 의료용, 재해용 등 다양한 분야에서 사용되고 있다. 하지만 매우 정밀하고 정확한 작업을 위해 만들어져 있음에도 불구하고, 약간의 충격에도 이상이 생긴다거나, 기기의 이음세 부분의 잦은 회전으로 마모가 발생하게 되고 그에 따라 미세한 오차가 발생한다. 그런 상황을 방지하고자, 우리는 PSD(Position Sensitive Detecter)센서를 이용해 실시간으로 굽힘각을 측정 및 감시하여 보다 정확한 구동을 유도하려 한다. 이는 단순한 로봇팔만이 아닌 휴머노이드나 다른 회전을 이용하는 기기라면 어디든 쉽게 적용 할 수 있을 것이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.66-73
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• 2006

Safety is the most important for all traffic management and control technology. This paper focuses on developing a flexible, reliable and real-time processing algorithm which is able to generate signal for the entering vehicle at the joining road through a camera and image processing technique. The images obtained from the camera located beside and upon the road can be used for traffic surveillance, the vehicle's travel speed measurement, predicted arriving time in joining area between main road and joining road. And the proposed algorithm displays the confluence safety signal with red, blue and yellow color sign. The three methods are used to detect the vehicle which is driving in setted detecting area. The first method is the gray scale normalized correlation algorithm, and the second is the edge magnitude ratio changing algorithm, and the third is the average intensity changing algorithm The real-time prototype confluence safety signal generation algorithm is implemented on stored digital image sequences of real traffic state and a program with good experimental results.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.67-74
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• 2010

E-learning technology which effectively supports the learning methodologies between students and professors and which provides location and time benefits to students is being researched now a days. However, E-learning classes produce bad effects comparing with offline classes in learning procedures including scholastic achievements. Bad effects of E-learning system could be proxy attendance, lack of concentration, and bad attitude of students. These environmental problems must be solved first to achieve the advantages of E-learning technology. To get rid of these problems, in this paper, we proposed a mechanism which provides effective learning progress by using face authentication method. This mechanism supervise the student by using real time face recognition which prevents proxy attendance, illegal activities, and student's absences.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.11-18
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• 2017

The Objective of this Study is to Prove the Effectiveness of a Smart Water Management(SWM) Technology. The SWM Technology can Reduce the Production Cost using Internet of Thing(IoT) Technology that Utilizes Remote Metering of Consumer's Water usage and Reduce the Leakage of Supply Facilities. The SWM Demonstration Model Installed a Remote Water Leakage Sensor, Smart Metering and Micro Multi Sensor in Water Supply Facility, and Provided Real-Time Monitoring of the Operation Status. Consumers can be Provided the usage of Tap Water and the Water Puality through a Smart Phone Application. At this Time, we Surveyed Whether Consumers save the Tap Water or Drinking Directly using the Tap Water usage Information. Also, this Study is to Verify the Degree of Improvement of Water Supply Rates and Drinking Water Rate, and to Decrease Consumer's Complaints, Operating Costs, and Water Consumption by the SWM Technology. It is also Established a SWM Model Combined with the IoT Sensor at Supply Facilities, operator monitoring system and explored recovery solution detected events. It means the upbringing of the domestic water industry by developing the related technologies and spreading the SWM to advanced levels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.146-151
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• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.39-39
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• 2021

기상재해를 극소화하기 위해서는 그 원인이 되는 기상현상의 규모와 거동을 명확히 감시하고 분석하여 신뢰성 있는 예측정보가 제공되어야 한다. 최근 위험기상 발생빈도가 증가하여 초단기 및 위험기상 예보의 정확도 향상을 위한 고품질 레이더 정보 활용 연구가 활발하게 진행되고 있다. 레이더는 전자파를 이용하여 강우의 양과 분포, 이동특성을 관측하는 장비로써 우리나라는 초단기적 위험기상 대응능력 향상을 추진하기 위한 목적으로 첨단 성능의 이중편파레이더 관측망을 구축하고 있다. 국내 기상관측용 레이더는 기상예보(기상청), 홍수예보(환경부), 군 작전 기상지원(국방부) 등으로 각 기관이 개별적으로 설치운영 하고 있다. 본 연구에서는 관계부처에서 운영하고 있는 레이더의 합성장을 이용하여 강수장의 상관성을 기반으로 이류(advection) 특성을 도출하였다. 정확도 있는 이류특성을 도출하기 위하여 시간해상도는 10분을 적용하였으며 가우시안 필터링 기법을 적용하여 강수장 상관분석을 수행하였다. 호우와 태풍을 대상으로 강수장의 이류패턴을 추출하여 강수장의 이동방향 및 속도를 고려한 강수량 예측기법의 적용성을 평가하였다. 본 연구 결과는 격자형 강수예측정보를 제공하여 AI 홍수예보 및 수치예보 모델의 초기조건 입력 등에 활용되어 기후변동성에 따른 대국민 안전 실현을 확보하는데 기후변화 대응전략의 핵심기술로 활용될 수 있을 것으로 판단된다. 덧붙어, 4차 산업혁명에 따른 수문기상 빅 데이터(big data) 통합 플랫폼을 구축하여 고해상도 홍수대응 기술 및 GIS 및 모바일 시스템을 연계한 실시간 기후재해 예·경보가 가능할 것으로 사료된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.351-353
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• 2021

In recent years, while the demand for electricity is rapidly increasing, fire accidents due to negligence in management of switchboards. In particular, switchboards for industrial and electrical resource control can cause serious problems. Thus, for the safety management of power switchboard, a secondary response is conducted to control firing when a specific condition value is satisfied, but in this case, it is highly likely that a considerable amount of time has elapsed after firing. In this paper, we propose a method to acquire big data for the development of a switchboard temperature and power control system that can actively respond to the current situation by monitoring and learning the temperature of the switchboard's busbar connection in real time. Specifically, a method for periodically acquiring and managing data such as temperature and power from various scattered sensors is proposed.