• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.322-327
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• 2006

Banwol bridge with steel plate girder and Pyongtaek bridge with PSC bos girder have been operated maintenance measuring system by the Seoul-Chonan of Kyongbu express railway. By analyzing the theoretical and experimental values of design load for these two bridge, the establishment of reference maintenance for measuring items was deduced from research. Two materials, steel and concrete plates, were considered as the upper structure. Actual measurement data for the behavior under speed, structural analysis results, and the presented references were analyzed and used to set up the reference establishment. The measuring items are stress(strain), displacement, dynamic acceleration, expansion movement, and dynamic frequency. The maintenance reference was established by comparing analytical and measuring values of the five items with respect to structural state class.

• 조명전기설비학회논문지
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• 제28권7호
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• pp.26-33
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• 2014

The purpose of this study is to evaluate the accuracy of luminance maps generated from five types of HDRI builder(High Dynamic Ranging Image builder) which include Photosphere, Bracket, Picturenaut, Luminance HDR and Photoshop. To accomplish this goal a set of experiments was conducted. In order to assess the luminance values of the HDR image from HDR image builder, the values had to be compared to the ones obtained from imaging photometer. After comparing measured luminance data using imaging photometer with those retrieved from the HDR images, Photosphere error rate estimated at 3% below.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.1952-1954
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• 2001

In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through comparing with ANFIS.

• 응용통계연구
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• 제26권2호
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• pp.361-373
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• 2013

군집분석을 위한 알고리즘은 매우 많다. 이러한 군집분석 방법들이 개체들을 어떻게 여러 개의 군집으로 나누는 지를 서로 비교하기 위해서는 나누어지는 군집들이 얼마나 동일한가를 알 수 있는 동의 측도가 필요하다. 우리가 고려하여야 할 군집분석 방법들이 많아질수록 덩달아 동의 측도들 값도 많아지게 된다. 그래서 복수 개의 군집분석 방법들과 대응되는 동의 측도값들을 한 눈에 확인할 수 있는 도구가 필요하다. 본 논문을 통하여 군집분석 방법들과 대응되는 동의 측도값들을 한 눈에 확인할 수 있는 그래픽도구들을 제안하고자 한다.

• Nuclear Engineering and Technology
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• 제38권7호
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• pp.665-674
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• 2006

Three-dimensional neutron flux and fluence of Kori Unit 3 were evaluated using the synthesis technique described in Regulatory Guide 1.190 for all reactor geometry. For this purpose DORT neutron transport calculations from Cycle 1 to Cycle 15 were performed using BUGLE-96 cross-section library. The calculated flux and fluence were validated by comparing the calculated reaction rates to the measurement data from the dosimetry sensor set of the $5^{th}$ surveillance capsule withdrawn at the end of cycle 15 of Kori Unit 3. And then the best estimation of the neutron exposures for the reactor vessel beltline region was performed using the least square evaluation. These results can be used in the assessment of the state of embrittlement of Kori Unit 3 pressure vessel.

• 대한원격탐사학회지
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• 제24권5호
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• pp.473-481
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• 2008

This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.344-346
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• 2019

본 논문에서는 Ultra-Wideband(UWB) 시스템에서 합성곱 신경망을 이용한 거리 추정 기법을 제안한다. 합성곱 신경망을 이용한 딥러닝 모델을 학습하는데 사용하는 학습 데이터는 MATLAB 프로그램을 통해 생성하였으며, IEEE 802.15.4a 표준을 활용한다. 기존 거리 추정에 사용하는 문턱값 기반의 거리추정 기법과 성능 비교를 통해 제안하는 거리 추정 기법의 성능을 검증한다.

• 융합보안논문지
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• 제23권5호
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• pp.101-106
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• 2023

최근 사이버 공격은 지능적이고 지속적인 피싱사이트와 악성코드를 활용한 해킹 기법을 활용하는 사회공학적 공격이 증가하고 있다. 개인 보안이 중요해지는 만큼 웹 어플리케이션을 이용해 악성 URL 여부를 판별하는 방법과 솔루션이 요구되고 있다. 본 논문은 악성 URL를 탐지하는 정확도가 높은 기법들을 비교하여 각각의 특징과 한계를 알아가고자 한다. 웹 평판 DB 등 기반 URL 탐지 사이트와 특징을 활용한 분류알고리즘 모델과 비교하여 효율적인 URL 이상탐지 기법을 제안하고자 한다.

• Nuclear Engineering and Technology
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• 제56권7호
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• pp.2704-2710
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• 2024

Nuclear archaeology research provides scientific methods to reconstruct the operating histories of fissile material production facilities to account for past fissile material production. While it has typically focused on analyzing material in permanent reactor structures, spent fuel or high-level waste also hold information about the reactor operation. In this computational study, we explore a Bayesian inference framework for reconstructing the operational history from measurements of isotope ratios from a sample of nuclear waste. We investigate two different inference models. The first model discriminates between three potential reactors of origin (Magnox, PWR, and PHWR) while simultaneously reconstructing the fuel burnup, time since irradiation, initial enrichment, and average power density. The second model reconstructs the fuel burnup and time since irradiation of two batches of waste in a mixed sample. Each of the models is applied to a set of simulated test data, and the performance is evaluated by comparing the highest posterior density regions to the corresponding parameter values of the test dataset. Both models perform well on the simulated test cases, which highlights the potential of the Bayesian inference framework and opens up avenues for further investigation.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.