• 정보과학회 논문지
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• 제43권3호
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• pp.389-397
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• 2016

본 논문에서는 대부분 운전자들이 보유하고 있는 스마트 모바일 기기와 최소한의 중앙서버를 활용하여 구축 가능한 위치기반 고속도로 안전시스템을 제안한다. 이를 위해 중앙서버를 구축하여 GPS를 이용한 차량의 위치정보를 수집하며, 서버에서는 차량위치 업데이트 메시지 감소를 위한 위치예측 알고리즘을 수행한다. 차량에 장착된 모바일에서는 가속도 센서를 이용하여 차량의 위험 상황을 인지하여 상황을 서버에게 업데이트하고, 서버는 LTE 통신을 이용한 위치기반 유니캐스트를 통하여 주변 위험차량에게 신속하게 알려준다. 본 논문에서 제안하는 위치예측 알고리즘을 평가하기 위하여 실제 차량에 앱을 탑재한 모바일 기기를 설치하고 도심도로, 한적한 도로, 고속화도로 등 다양한 시나리오에서 실제 실험하고, 위험도 전파 등을 평가하기 위한 시뮬레이션을 수행한다. 또한 차량의 충돌상황을 감지하기 위한 충돌 모의실험을 진행하며, 모바일 기기가 거치대에서 이탈되는 등의 예외적인 상황을 처리할 수 있는 기법을 제안한다.

• Ocean and Polar Research
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• 제35권1호
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• pp.15-26
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• 2013

The toxic, Harmful Algal Blooms (HABs) caused by the Cochlodinium polykrikoides have a serious impact on the coastal waters of Korea. In this study, the acoustic detection system was developed for rapid HABs detection, based on the acoustic backscattering properties of the C. polykrikoides. The developed system was mainly composed of a pulser-receiver board, a signal processor board, a control board, a network board, a power board, ultrasonic sensors (3.5 and 5.0 MHz), an environmental sensor, GPS, and a land-based control unit. To evaluate the performance of the system, a trail was done at a laboratory, and two in situ trials were conducted: (1) when there was no red tide, and (2) when there was red tide. In the laboratory evaluation, the system performed well in accordance with the number of C. polykrikoides in the received level. Second, under the condition when there was no red tide in the field, there was a good correlation between the acoustic data and sampling data. Finally, under the condition when there was red tide in the field, the system successfully worked at various densities in accordance with the number of C. polykrikoides, and the results corresponded with the sampling data and monitoring result of NFRDI (National Fisheries Research & Development Institute). From the laboratory and field evaluations, the developed acoustic detection system for early detecting HABs has demonstrated that it could be a significant system to monitor the occurrence of HABs in coastal regions.

• Journal of Astronomy and Space Sciences
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• 제25권3호
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• pp.267-282
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• 2008

대류층의 중성 대기는 전자가파의 신호 지연을 일으키기 때문에, GNSS(Global Navigation Satel-lite System)를 이용한 정밀측위의 가장 큰 오차요인으로 작용한다. 대류층 지연오차는 대류층의 굴절률과 연관 있으며, 대류층의 굴절률은 경험적으로 압력, 온도 및 수증기 분압으로 표현된다. 따라서 GNSS 안테나 위치의 기상 정보를 알고 있다면, 대류층 지연오차는 경험적 법칙에 의해 산출될 수 있다. 이 연구에서는 임의의 장소와 시간에 대한 대류층 지연오차를 생성하기 위한 기상정보 생성에 대하여 연구하였다. 한국천문연구원이 운영하는 9개의 상시 관측소에 설치된 디지털 기상 센서의 관측값을 가지고 범용 크리깅 (Ordinary Kriging)을 적용하여 기상 정보를 생성하였고, 상시 관측소의 데이터 공백을 메우기 위해 각 상시관측소의 기상 데이터를 분석하여 수치 모델을 만들어 보완하였다.

• 한국IT서비스학회지
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• 제17권2호
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• pp.83-100
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• 2018

Demand for stone products used as building materials is increasing. The construction industry, the value of the stone industry is sufficient, but the domestic stone industry is very lag regarding IT utilization. However, the overseas stone industry produces high-quality products using IT. In this study, we want to offer an IT application technology priority fit for the stone industries. We identify the current status and production process of the stone industries, then set the priority of various IT, so that obtain competitiveness in the domestic stone industries, and minimize the gap between the overseas stone industries. Therefore, we used AHP method; stone industry production processes were selected as the Enterprise Operation Management, Quarrying, Manufacturing, Construction and Maintenance of first-tier. The second-tier ones are consisted of 30 factors out of IT elements. Focus group interviews were conducted to confirm the validity of each factor. As a result, most important factors of first-tier was selected as the order of Manufacturing, Quarrying, Enterprise Operation Management, and Construction & Maintenance. The top 5 of 30 factors in the second-tier were selected Smart Sensor, Mobile Device, Robot of manufacturing, GIS of quarrying, and SCM of enterprise operation management. And the factor that relatively less important was GPS of construction and maintenance. If properly applied an IT application technology for stone industry, we expect to provide efficient production lines and increase customer satisfaction, which will ultimately expand the promotion for the industry and thus act as positive factor in promoting the stone industry.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.344-346
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• 2004

IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.181-194
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• 2017

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.195-203
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• 2017

A 2U cube satellite called SNUGLITE has been developed by GNSS Research Laboratory in Seoul National University. Its main mission is to perform actual operation by mounting dual-frequency global positioning system (GPS) receivers. Its scientific mission aims to observe space environments and collect data. It is essential for a cube satellite to control an Earth-oriented attitude for reliable and successful data transmission and reception. To this end, an attitude estimation and control algorithm, Attitude Determination and Control System (ADCS), has been implemented in the on-board computer (OBC) processor in real time. In this paper, the Extended Kalman Filter (EKF) was employed as the attitude estimation algorithm. For the attitude control technique, the Linear Quadratic Gaussian (LQG) was utilized. The algorithm was verified through the processor in the loop simulation (PILS) procedure. To validate the ADCS algorithm in the ground, the experimental verification via a single axis Hardware-in-the-loop simulation (HILS) was used due to the simplicity and cost effectiveness, rather than using the 3-axis HILS verification (Schwartz et al. 2003) with complex air-bearing mechanism design and high cost.

• 대한토목학회논문집
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• 제33권3호
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• pp.1191-1202
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• 2013

기존의 토공 자동화 연구들은 주로 GPS와 센서의 응용, 작업환경 모델링, 장비 진로계획, 작업 정보관리, 원격조정 등과 같은 주제에 관심을 두었다. 최근에는 건설자동화 연구분야에서 $CO_2$ 감축이 주요 관심사의 하나로 대두되었다. 토공작업의 경우에는 많은 종류의 건설장비나 로봇들이 관여되므로 건설현장에서 많은 양의 $CO_2$를 배출하는 작업이 되고 있다. 효과적인 토공계획과 건설장비 운영은 생산성 및 안전성을 증가시킬 뿐만 아니라 $CO_2$ 배출량도 줄일 수 있다. 본 연구에서는 3D 토공현장 모델, 2가지 시공법에 의한 3D 토량배분 방법, 토공작업 패키지 구성방법과 같은 그린 토공을 위한 몇 가지 자동화 개념을 제시하고 있다. 엑셀로 작성된 시뮬레이터를 개발을 통하여 주어진 토공작업에 대하여 3D 토량배분 계획을 수립하였고 $CO_2$ 배출량을 추정하였다.

• Journal of Biosystems Engineering
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• 제35권2호
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• pp.77-84
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• 2010

In this study, we tried to predict tractor power output, fuel consumption rate and work performance indirectly in order to develop an eco driving system. Firstly, we developed equations which could predict tractor power output and fuel consumption rate using characteristic curves of tractor power output. Secondly, with actual engine rpm determined by initial engine rpm and work load, tractor power output and fuel consumption rate were forecasted. Thirdly, with speed signals of GPS sensor system, it was possible to foresee tractor work performance and fuel consumption rate. Lastly, precision of the eco driving system was evaluated through tractor PTO test, and effects of the eco driving system were investigated in the plowing and rotary tilling operations. Engine rpm, power output, fuel consumption rate, work performance and fuel consumption rate per plot area were displayed in the eco driving system. Predicted tractor power outputs in the full load curve were well coincided with the actual power output of prototype, but small differences, 1 to 6 ㎾, were found in the part load curve. Error of the fuel consumption rate was 0.5 L/h, 4.5%, the greatest, and 1 to 3 L/h at the part load curve. It was shown that 69% and 53% of fuel consumption rates could be reduced in plowing and rotary tilling operations, respectively, when the eco driving system was installed in tractor.