• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.713-718
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• 1994

Voronoi diagrams for closed shapes have many practical applications, ranging from numerical control machining to mesh generation. Shape offset based on Voronoi diagram avoids the topological problems encountered in traditional offsetting algorithms. In this paper, we propose a procedure for generating a Voronoi diagram and an exact offset for planar curve. A planer curve can be defined by free-form curve segements. The procedure consists of three steps : 1) segmentation by minimum curvature, 2) construction of Voronoi diagram, and 2) generation of the exact offset.

• Journal of Advanced Marine Engineering and Technology
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• 제39권2호
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• Nuclear Engineering and Technology
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• 제52권7호
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• Journal of Advanced Marine Engineering and Technology
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• 제38권5호
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• pp.566-572
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• 2014

Recently, indoor navigation has been applied in large convention centers by using wireless sensor networks (WSNs), which provide not only a user's path to be traveled but also orientation and shopping information to increase user's convenience. This paper presents the localization system for estimating relative coordinates without pre-deployment of the reference node based on ultra wide band (UWB) ranging system, which is relatively suitable for indoor localization compared to other wireless communications, and azimuth sensor. The proposed localization system which consists of an azimuth sensor and a mobile node composed of three nodes estimates relative coordinates of the reference node without applying any recursive and time consumption algorithms. Also, in the process of estimating relative coordinates of the reference node, ranging errors are minimized through the proposed technique and the number of nodes can be reduced. Experimental results show the feasibility and validity of the proposed system.

• 인터넷정보학회논문지
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• 제11권2호
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• pp.61-72
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• 2010

본 논문에서는 Ultra-Wide-Band(UWB) 영역 측정을 활용한 이동객체 위치추정과 이동객체 위치정확도를 개선하기 위한 방법을 논한다. 실외환경과는 달리 실내에서는 여러 가지 노이즈로 인해 이동객체의 위치추적이 어렵다. UWB는 최근 위치추적 응용에서 주목을 받고 있는 라디오 기술이다. UWB의 영역측정 기술은 cm 수준의 정확도를 제공한다. UWB의 데이터 전송과 정밀한 영역측정, 물질관통의 특성은 실내위치추적 응용에 적합하다. 본 논문은 UWB 영역 기술과 파티클 필터를 이용한 이동객체의 위치추정 알고리즘을 제안한다. 기존 위치추정 알고리즘들은 이동객체의 위치추정을 한 후에 예상되는 오차와 bias 값을 제거하였다. 그러나 이 논문에서 제안한 알고리즘은 먼저 예상되는 UWB 영역 거리 오차를 제거하고 난 후에 이동객체의 위치를 추정한다. 본 논문에서는 제안 알고리즘이 기존 이동객체의 위치 추정 후 오차를 제거하는 방식보다 위치정밀도가 좋아졌음을 실험을 통하여 보였다. 본 연구에서는 UWB를 이용하여 고정되어 있고 위치를 알고 있는 세 앵커들과 이동객체 간의 추정 거리로부터 bias값과 반복 영역 오차 값을 제거한 후 삼각측량을 하여 이동객체의 위치를 추정하였다. 마지막으로 파티클 필터를 사용하여 이동객체의 위치 정밀도 개선을 한다. 실험 결과는 제안 위치추정 방식이 실내 환경에서 더 정밀함을 보인다.

• 한국정보통신학회논문지
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• 제16권8호
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• pp.1789-1798
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• 2012

IEEE 802.15.4a 표준은 정확한 위치추정 서비스를 지원하기 위하여 time-of-arrival (TOA) 기반의 거리측정 기술을 제공한다. 특히, non-line-of-sight (NLOS) 상황은 TOA 기반의 위치인식에서 중요한 문제이고, IEEE 802.15.4a 네트워크의 성능에 심각한 영향을 끼칠 수 있다. 본 논문에서는 에너지 효율적인 낮은 복잡도의 위치추정 알고리즘을 제안한다. 제안한 알고리즘은 TOA 거리측정을 위해 순차적인 acknowledgment (ACK) 패킷을 이용하고 위치추정지역을 제한 할 수 있는 작은 사각 영역을 설정함으로써 위치를 추정한다. 패킷 교환으로 인한 메시지 오버헤드는 순차적 ACK 패킷을 이용하여 감소될 수 있다. 사각 영역 설정을 통하여 NLOS 환경에 있는 거리측정 값을 제거하고, 위치 추정의 영역을 제한함으로써 추정하는 연산 시간과 에너지를 줄일 수 있다. 시뮬레이션을 통해 에너지 소모와 추정 위치의 정확도 측면에서 제안한 알고리즘이 기존의 알고리즘 보다 좋은 성능을 보이는 것을 확인 하였다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.153-156
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• 2007

There have been many studies on extracting building boundaries from LiDAR(Light Detection And Ranging) data. In such studies, points are first segmented, then are further processed to get straight boundary lines that better approximate the real boundaries. In most research in this area, processes like generalization or regularization assume that buildings have only right angles, i.e. all the line segments of the building boundaries are either parallel or perpendicular. However, this assumption is not valid for many buildings. We present a new approach consisting of three steps that is applicable to more complex building boundaries. The three steps consist of boundary tracing, generalization, and regularization. Each step contains algorithms that range from slight modifications of conventional algorithms to entirely new concepts. Four typical building shapes were selected to test the performance of out new approach and the results were compared with digital maps. The results show that the proposed approach has good potential for extracting building boundaries of various shapes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권2호
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• pp.253-270
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• 2013

To achieve accurate localization information, complex algorithms that have high computational complexity are usually implemented. In addition, many of these algorithms have been developed to overcome several limitations, e.g., obstruction interference in multi-path and non-line-of-sight (NLOS) environments. However, localization systems those have complex design experience latency when operating multiple mobile nodes occupying various channels and try to compensate for inaccurate distance values. To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-$O(n^2)$ of only a few data points and an algorithm with a self-calibration feature. The performance of the proposed localization system is verified by means of actual experiments. The results show a mean error of about 1 m and multiple mobile node operation in a $100{\times}35m^2$ environment under NLOS condition.

• ETRI Journal
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• 제29권4호
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• pp.411-420
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• 2007

The steady evolution of mapping technology is leading to an increasing availability of multi-sensory geo-spatial datasets, such as data acquired by single-head frame cameras, multi-head frame cameras, line cameras, and light detection and ranging systems, at a reasonable cost. The complementary nature of the data collected by these systems makes their integration to obtain a complete description of the object space. However, such integration is only possible after accurate co-registration of the collected data to a common reference frame. The registration can be carried out reliably through a triangulation procedure which considers the characteristics of the involved data. This paper introduces algorithms for a multi-primitive and multi-sensory triangulation environment, which is geared towards taking advantage of the complementary characteristics of spatial data available from the above mentioned sensors. The triangulation procedure ensures the alignment of involved data to a common reference frame. The devised methodologies are tested and proven efficient through experiments using real multi-sensory data.

• Smart Structures and Systems
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• 제15권3호
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.