• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.7-13
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• 2019

This study aims to develop a FE Model to simulate dissimilar friction stir welding and to address its potential for fundamental analysis and practical applications. The FE model is based on Coupled Eulerian-Lagrangian approach. Multiphysics systems are calculated using explicit time integration algorithm, and heat generations by friction and inelastic heat conversion as well as heat transfer through the bottom surface are included. Using the developed model, friction stir welding between an Al6061T6 plate and an AZ61 plate were simulated. Three simulations are carried out varying the welding parameters. The model is capable of predicting the temperature and plastic strain fields and the distribution of void. The simulation results showed that temperature was generally greater in Mg plates and that, as a rotation speed increase, not the maximum temperature of Mg plate increased, but did the temperature of Al plate. In addition, the model could predict flash defects, however, the prediction of void near the welding tool was not satisfactory. Since the model includes the complex physics closely occurring during FSW, the model possibly analyze a lot of phenomena hard to discovered by experiments. However, practical applications may be limited due to huge simulation time.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.404-404
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• 2011

최근 기상변동성 증가와 극치수문사상의 발생빈도 증가로 인한 기상재해가 빈번하게 일어나고 있다. 이러한 기상현상으로 인한 재해의 예방을 위해서 사전에 위험을 인지하고 그 규모를 예측할 수 있는 여러 기법들이 기상레이더 또는 수치예보자료 등을 이용하여 개발 및 적용되고 있다. 이 과정에서 해결해야 할 여러 문제점들이 있는데, 우선 수치예보자료 또는 기상레이더자료를 종관기상관측소 및 자동기상관측지점의 지상관측 강수량과 연계하여 평가하는 과정이 필요하고, 현재시점에 형성되어 있는 강우장의 공간 이동 예측 기법이 확보되어야 할 것이다. 전북지역은 게릴라성 집중호우가 빈번한 산악형 강수와 산지유역의 급한 하천경사가 맞물려 인명 및 재산피해가 매년 발생하고 있으며, 과거 돌발홍수가 발생한 사례가 있어 이상기후 및 기후변화로 인한 홍수 위험도가 커질 것으로 전망되고 있다. 본 연구는 전라북도의 기상재해 예측모형 개발을 위한 사전 분석과정으로 전라북도지역에서 관측된 기존의 대규모 강수사상을 이용한 강수사상의 특성 분류 및 관측소간 공간상관성을 분석하는데 목적을 두고 있다. 강수사상의 특성분류를 통해 강수 발생형태에 따른 기상학적 영향인자, 강수의 발생량 및 이동특성 예측의 정도를 향상시킬 수 있으며, 분류 기법으로 SVM(support vector machine)을 이용한 자동분류를 적용한다. 또한 관측소간 공간상관성 분석을 위하여 각 관측소 강수량간의 조건부 확률을 이용한다. 예로써 부안관측소에 강수가 발 생했을 때, 부안관측소의 강수량 조건에 의한 전주관측소 강수량 확률을 다음과 같이 구성할 수 있다. �揚滑斂�수량�咀刮활�수량��. 공간상관성 분석과정에서 관측소간 강수 이동시간에 따른 강수 발생 시간의 차이 또한 고려하며, 과거 기상관측 자료의 분석을 통해 전라북도지역의 관측소간 강수발생의 공간적 상관성을 규명하고, 단기예측 모델 개발을 위한 기초자료로 활용할 수 있을 것이다. 또한, 기후변화시나리오에 의한 미래 강수량의 지역적 상세화 과정에도 본 연구를 통한 결과를 이용할 수 있을 것이라 판단된다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.29-32
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• 2011

센서 네트워크는 원격지의 상태를 실시간으로 파악하기 위하여 각종 모니터링 시스템에서 활발히 활용된다. 시스템은 원격지에 일어난 사건을 인식하고 사용자에게 유용한 정보를 제공하기 위하여 각종 시뮬레이션 모델 및 분석 기법과 함께 수집된 센서 데이터를 분석한다. 이 논문에서는 모니터링 시스템에서 원격지의 사건을 인식하기 위하여 사건을 등록하고 처리하는 과정을 설계하였다. 이 과정에는 사건 정보 등록, 센서 데이터로부터 사건 정보 추출, 데이터 종류 별 테마(theme) 생성, 연산자를 통한 테마 결합, 시뮬레이션 모델을 활용한 사건 진행 예측, 영향 분석이 포함된다. 그리고, 실제 센서 네트워크를 활용하여 등록된 사건이 처리됨을 보인다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.3
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• pp.10-17
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• 2016

This paper presents a laboratory validation of a new approach for Finite Element Model Updating(FEMU) on short-span bridges by combining ambient vibration measurements with static load input-deflection output measurements. The conventional FEMU approach based on modal parameters requires the assumption on the system mass matrix for the eigen-value analysis. The proposed approach doesn't require the assumption and even provides a way to update the mass matrix. The proposed approach consists of two steps: 1) updating the stiffness matrix using the static input-deflection output measurements, and 2) updating the mass matrix using a few lower natural frequencies. For a validation of the proposed approach, Young's modulus of the laboratory model was updated by the proposed approach and compared with the value obtained from strain-stress tests in a Universal Testing Machine. Result of the conventional FEMU was also compared with the result of the proposed approach. It was found that proposed approach successfully estimated the Young's modulus and the mass density reasonably while the conventional FEMU showed a large error when used with higher-modes. In addition, the FE modeling error was discussed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.102-110
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• 2023

PSC-I girder bridges constitute the largest proportion among highway bridges in Korea. According to the precision safety diagnosis data for the past 10 years, approximately 41.3% of the PSC-I bridges have been graded as C. Furthermore, with the increase in the aging of bridges, preemptive management is becoming more important. Damage and deterioration to the deck and girder with a long replacement cylce can have considerable impacts on the service and deterioration of a bridge. In addition, the high rate of device damages, including expansion joints and bearings, necessitates an investigation into the influence of the device damage in the structural members of the bridge. Therefore, this study defined representative PSC-I girder bridges with single and multiple spans to evaluate heterogeneous damages that incorporate the damage of the bridge member and device with the deterioration of the deck. The heterogeneous damages increased a crack area ratio compared to the individual single damage. For the single-span bridge, the occurrence of bearing damage leads to the spread of crack distribution in the girder, and in the case of multi-span bridges, expansion joint damage leads to the spread of crack distribution in the deck. The research underscores that bridge devices, when damaged, can cause subsequent secondary damage due to improper repair and replacement, which emphasizes the need for continuous observation and responsive action to the damages of the main devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.189-192
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• 2021

This study applies a deep learning-based long short-term memory(LSTM) model to track tracking technology. In the case of existing track tracking technology, the weight of constant velocity, constant acceleration, stiff turn, and circular(3D) flight is automatically changed when tracking track in real time using LMIPDA based on Kalman filter according to flight characteristics of an aircraft such as constant velocity, constant acceleration, stiff turn, and circular(3D) flight. In this process, it is necessary to improve performance of changing flight characteristic weight, because changing flight characteristics such as stiff turn flight during constant velocity flight could incur the loss of track and decreasing of the tracking performance. This study is for improving track tracking performance by predicting the change of flight characteristics in advance and changing flight characteristic weigh rapidly. To get this result, this study makes deep learning-based Long Short-Term Memory(LSTM) model study the plot and target of simulator applied with radar error model, and compares the flight tracking results of using Kalman filter with those of deep learning-based Long Short-Term memory(LSTM) model.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.349-356
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• 2005

Artificial Organism-used application areas are expanding at a break-neck speed with a view to getting things done in a dynamic and Informal environment. A use of general programming or traditional hi methods as the representation of Artificial Organism behavior knowledge in these areas can cause problems related to frequent modifications and bad response in an unpredictable situation. Strategies aimed at solving these problems in a machine-learning fashion includes Genetic Programming and Evolving Neural Networks. But the learning method of Artificial-Organism is not good yet, and can't represent life in the environment. With this in mind, this research is designed to come up with a new behavior evolution model. The model represents behavior knowledge with Classification Rules and Enhanced Backpropation Neural Networks and discriminate the denomination. To evaluate the model, the researcher applied it to problems with the competition of Artificial-Organism in the Simulator and compared with other system. The survey shows that the model prevails in terms of the speed and Qualify of learning. The model is characterized by the simultaneous learning of classification rules and neural networks represented on chromosomes with the help of Genetic Algorithm and the consolidation of learning ability caused by the hybrid processing of the classification rules and Enhanced Backpropagation Neural Network.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.137-140
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• 2004

최근 모바일 기기의 보급이 증가되고, 고급 어플리케이션의 동작이 가능해지는 등 모바일 장비의 사용 편이성이 급속도로 증가되고 있다. 또한 GPS 기술의 발전으로 인해 위치 기반 서비스가 여러 분야에서 널리 사용되고 있다. 본 논문에서는 고정된 노선을 이동하는 버스를 대상으로 목적지까지의 최단 시간 경로를 제공하는 교통 정보 시스템을 제안한다. 이를 위해 우선, 이동 객체인 버스와 관련된 정보를 효율적으로 저장, 관리, 검색할 수 있는 스키마와 질의 모델을 제안한다. 또한, 제안된 시스템에서는 최단 시간 경로를 위해 버스의 노선 정보 및 위치 정보, 정류장간 소요 시간 정보, 사용자의 근접 정류장까지의 이동 시간, 사용자의 도보 이동 시간 등의 정보를 활용한다. 대부분의 위치기반 서비스를 위한 시공간데이터베이스 기술에서는 이동 객체가 시간의 흐름에 따라 속도와 방향의 변화로 인한 임의의 동선으로 움직인다고 가정하고 있으며, 버스와 같이 고정된 노선을 이동하는 이동 객체의 관리 기법은 다루어지지 않고 있다. 따라서 본 논문의 연구 결과는 고정된 노선을 이동하는 이동 객체의 저장 및 이동 객체의 미래 위치 예측 기법에 활용될 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.355-364
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• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.393-401
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• 2017

Assuming that Smart Work will have a positive effect on job satisfaction, and which, in turn, will improve productivity, domestic and international organizations have adopted and implemented Smart Work. However, leading companies have recently reduced or shut down operations of Smart Work. If Smart Work had really brought about the improvement of productivity, there would be no reason for organizations to take such action. Therefore, this paper reviews the relationship among Smart Work, job satisfaction and productivity. Based on the National Digital Science Library (NDSL) database, we select eight references related to Smart Work, and analyze them systematically. The previous empirical studies show that Smart Work produces a positive outcome for job satisfaction, which, in turn, improves productivity. However, we find that the previous research has a problem demonstrating the relationship between job satisfaction and productivity, because they has unclearly measured the concept of job satisfaction. This research deeply discuss this issue, and provides future research direction.