• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.400-404
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• 2008

라이다는 데이터 획득의 신속성과 처리의 자동화라는 장점을 가지고 있어서 도시 모델의 생성, 변화탐지(Change Detection), 삼림지역의 DTM(Digital Terrain Model)의 생성, 등고선 추출, 나무의 높이 결정을 통한 산림관리, 해안 지형의 관리 등 다양한 분야에서 활용이 되고 있다. 이와 같이 라이다데이터 활용에 대한 많은 연구가 이루어지면서 다양한 처리 알고리즘이 개발되고 있다. 알고리즘을 개발하고 그 성능을 정확하게 평가를 위해서는 알고리즘을 다양한 형태의 시험데이터에 적용해 보아야 하지만, 성능평가를 위해 다양한 실측 데이터를 획득하기는 어려운 실정이다. 본 연구에서는 개발된 알고리즘의 성능평가를 위한 다양한 모의데이터를 실제 DEM으로부터 시뮬레이션을 통해 생성하는 방법을 제안한다 라이다 시스템에 대한 기하학적 모델링하여 센서방정식을 유도하고, 이를 기반으로 DEM상에서 플랫폼의 이동경로에 따라 취득되는 모의 라이다데이터를 생성한다. 본 연구에서 제안하는 시뮬레이션을 이용하면 라이터데이터를 이용하는 다양한 활용 알고리즘 개발과 경제적이고 정확한 성능평가에 도움이 될 것이다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.394-396
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• 2007

본 논문은 레이더를 통해 입력받은 데이터를 분석하여 같은 물체에 관한 데이터를 구분하는 방법을 제시한다. 큰 영역을 감시하는 레이더에 비해 영역이 좁을 때 레이더는 한 물체에 대해서 물체 형태에 따라 데이터가 들어오게 된다. 이 데이터들은 같은 물체인지 아닌지 구분이 없어서 응용된 알고리즘을 적용하기 힘들다. 따라서 응용된 알고리즘을 적용하기 전 하나의 물체에 대한 데이터의 그룹핑 작업이 필요하다. 본 논문에서 그룹핑 방법을 제시하며 실제 도로에서 취득한 데이터를 가지고 시뮬레이션을 하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5518-5524
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• 2012

The world today, has come to an age of diverse paradigms and technologies being developed, and technology of a new field is realized by merging technologies of different fields.One of such, u-Health system refers to a system which can monitor its users, regardless of time and place, using many body sensor datas based on USN (Ubiquitous Sensor Network). In the past, this kind of u-Health system was able to collect sensor datas through wires and could be monitored only by using PC (Personal Computer), but with development in technology, the system is now becoming possible to collect sensor datas wireless and monitor unhindered by time and place. This research aims to collect sensor datas of the user, and through Jena inference network, provide web service and smartphone application which enables checking of user's body datas in times of emergency, whenever, wherever.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.221-230
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• 2016

As structures' long term performances and users' safety have been highlighted, a new maintenance technique using IT has drawn attention around the globe. Therefore, throughout the paper, by analyzing bridge's static and dynamic data using wireless measuring sensor, a "real time smart bridge monitoring system" has developed. Smart bridge monitoring system is consists of three main parts a sensor that can measure major members' movement, a wireless system that informs the data from the sensor, and the database system that analysis the data. In order to test the performance of the system, five different were placed on the Olympic Bridge, Seoul. The power system of the sensors was replaced by self-sustain solar energy system. In order to validate data from the real time smart bridge monitoring system, the data was collected for a week from both wireless system and the wired system and the two data were compared to see the relevance.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.506-511
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• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2736-2744
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• 2013

In this paper, we present a Smart Water Treatment Plant using Zigbee USN devices and a real-time monitoring system in K-water Flow Meter Calibration Center Building. For verification, the data of vertical type WTP such as flow rate, pressure, water level and water temperature are obtained by the Zigbee USN devices, operating in 2.45 GHz band, and be wirelessly surveilled by the real-time monitoring system. The received data from the sensor is transmitted to the data processing device, and then the processed data can be monitored on a smart phone. Consequently, the pilot plant based on the low-cost and high-efficiency USN has been developed with the performance analysis for the communication network and remote monitoring system on mobile devices.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5695-5706
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• 2015

Recently adoption of BIM technology for building renovation and remodeling has been increased in construction industry. However most buildings have trouble in 2D drawing-based BIM modeling, because 2D drawings have not been updated real situations continually. Applying reverse engineering, this study analysed the point cloud data structure and the process for guideline of reverse engineering of architectural MEP, and deducted the relating considerations. To active usage of 3D scanning technique in domestic, the objective of this study is to analyze the point cloud data processing from real site with terrestrial LiDAR and the process from data gathering to data acquisition.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.29-38
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• 2023

Although the biosignal is the best way to represent the human condition, it is difficult to acquire the biosignal of a driver driving for detecting driver's condition. As one of the methods to overcome this limitation, this paper proposes a driving stress monitoring system based on information provided by OBD-II(on-board diagnostics version II). The driving information and EDA(Electrodermal activity) data are obtained through the OBD-II scanner and E4 wristband, respectively. EDA data is used as ground truth to distinguish whether driver is stressed or not. MLP(multi-layer perceptron) neural network is used as a model to detect driving stress and is trained using driving data for about a month. To evaluate the proposed system, we used about 1 hour of driving data and the accuracy is 92%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.104-104
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• 2022

임진강 수계는 북측 지역이 다수를 차지하는 유역 특성으로 예고 없는 상류 급방류, 강우 등으로 인해 댐 운영에 근본적 어려움이 있으며, 이에 따라 홍수조절지 및 댐 하류 계측 가능 지역의 취득 자료를 고려한 하천 수위 변화에 대한 사전 예측을 필요로 하고 있다. 홍수기 하천 도달시간 및 수위예측 기법으로는 물리 기반 및 데이터 기반 모델들이 다양하게 연구되어 왔으며, 일부 연구성과들은 현업에 활용하고 있다. 물리기반 모델은 하천 지형 변화에 대한 자료 취득 및 분석에 많은 시간을 요하는 단점은 있으나, 설명 가능한 모델을 구현할 수 있을 것으로 사료 된다. 반면, 데이터 기반 인공지능 모델은 짧은 시간 및 비용으로 모델을 개발할 수 있으나, 복잡한 알고리즘구현 시 설명이 불가하여 일관성을 의심 받을 수 있다. 본 논문에서는 홍수 도달시간과 하류 수위 상승에 대하여 설명 가능한 인공지능 알고리즘 및 시뮬레이션 프로그램을 개발하고자 하였다. 홍수 도달시간 예측은 기존 조견표 방식에서 고려하지 않았던 홍수파의 영향을 추가 변수화 하고, 데이터의 전후처리를 통하여 도달시간을 예측하였다. 실시간 하류 수위 예측은 댐 방류량, 주변 강우, 조위 등을 고려하여 도달시간 후 수위를 예측할 수 있도록 구현하였으며, 자료 동화 기술을 일부 적용하였다. 미래 방류조건에 대한 시뮬레이션을 위해서는 미래 방류량, 예상 강우 입력 시 하천 지점별 수위 상승을 예측할 수 있도록 알고리즘 및 프로그램을 개발하였다. 이를 구현하기 위하여 다양한 인공지능 알고리즘을 이용한 학습, 유전자 알고리즘을 이용한 가중치 학습 제한 조건내 최적화, 수위파와 조위파의 중첩의 정리 등을 이용하여 예측 정확도 및 신뢰성을 제고 하였다. 인공지능 분석결과의 현업활용성 제고를 위하여 시뮬레이터 프로그램을 개발하여 현업에 적용하였다.