• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.31-42
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• 2004

This study develops Accident Modification Factors (AMF) of countermeasures with Baysian method which are newly proposed for reducing Roadway-Rail grade crossing accidents. This study proposes a new "Bayesian Analytical Framework" for countermeasure assessment which combines "Subjective" Prior Information with "Logical" based Information. The newly proposed "Bayesian Analytical Framework" consists of the following three steps: The 1st step - Countermeasure Selection, Choice of Participants, Selection of Crashes; The 2nd step-Development of Crash History Manual and Countermeasure Evaluation Manual; The 3rd step-Development of AMFs through sound statistical tests. This study used the Komogorov-Smirnov(K-S) Test to determine whether two unknown distribution functions associated with the two populations are identical. The results of the study are that individual responses did not meet the K-S test of identical distributions. while individual vs. group distributions are identical. This indicates that combining the input of several people reduces the impact of individual subjectivity and assumptions and is important for developing a repeatable distribution to develop sound AMFs of countermeasures for reducing Roadway-Rail grade crossing accidents. The procedures of the AMF development conducted in this study can be used to estimate the safety effects of countermeasures for road segments and intersections, in addition to Roadway-Rail grade crossings.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.135-146
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• 2005

Up to now studies on the fusion of travel time from various detectors have been conducted based on the variance raito of the intermittent data mainly collected by GPS or probe vehicles. The fusion model based on the variance ratio of intermittent data is not suitable for the license plate recognition AVIs which can deal with vast amount of data. This study was carried out to develop the fusion model based on travel time acquired from the license plate recognition AVIs and the point detectors. In order to fuse travel time acquired from the point detectors and the license plate recognition AVIs, the optimized fusion model and the proportional fusion model were developed in this study. As a result of verification, the optimized fusion model showed the superior estimation performance. The optimized fusion model is the dynamic fusion ratio estimation model on real time base, which calculates fusion weights based on real time historic data and applies them to the current time period. The results of this study are expected to be used effectively for National Highway Traffic Management System to provide traffic information in the future. However, there should be further studies on the Proper distance for the establishment of the AVIs and the license plate matching rate according to the lanes for AVIs to be established.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.603-611
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• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.37-51
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• 2023

Spatial information is essential for interpreting urban phenomena. Methodologies for spatializing urban information, especially when it lacks location details, have been consistently developed. Typical methods include Geocoding using structured address information or place names, spatial integration with existing geospatial data, and manual tasks utilizing reference data. However, a vast number of documents produced by administrative agencies have not been deeply dealt with due to their unstructured nature, even when there's demand for spatialization. This research utilizes the natural language processing model BERT to spatialize public documents related to urban planning. It focuses on extracting sentence elements containing addresses from documents and converting them into structured data. The study used 18 years of urban planning public announcement documents as training data to train the BERT model and enhanced its performance by manually adjusting its hyperparameters. After training, the test results showed accuracy rates of 96.6% for classifying urban planning facilities, 98.5% for address recognition, and 93.1% for address cleaning. When mapping the result data on GIS, it was possible to effectively display the change history related to specific urban planning facilities. This research provides a deep understanding of the spatial context of urban planning documents, and it is hoped that through this, stakeholders can make more effective decisions.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Journal of the Korean Magnetics Society
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• v.13 no.1
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• pp.36-40
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• 2003

We have grown D $y_{x}$B $i_{3-x}$F $e_{5}$ $O_{12}$ (x = 0.5,1.0, 1.5,2.0) magnetic garnet thin films upon $Al_2$O3i and GGG substrate using Pechini process. The annealing temperature to get single phase D $y_{x}$B $i_{3-x}$F $e_{5}$ $O_{12}$ garnet is dependent on substrate, i.e. the annealing temperature for GGG substrate il 5$0^{\circ}C$ lower than that for $Al_2$ $O_3$ substrate. The grains of garnet thin film grown on GGG (111) plane align along [111] direction, and in this case the hysteresis curve does not saturate up to H : 5000 Oe. We attribute this phenomenon to rotation magnetization process. The maximum amount of Bi substitution in polycrystalline D $y_{x}$B $i_{3-x}$F $e_{5}$ $O_{12}$ thin film prepared by Pechini process is restricted to 2.0 Bi atom/unit cell, and this value is less than that in single garnet crystall grown by LPE method.own by LPE method.ethod.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.3
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• pp.1-8
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• 2002

In order to study electric properties of (Pb$\_$0.9/La$\_$0.1/)Ti$\_$0.975/O$_3$(PLT (10)) films with varying excess lead concentration (7.5, 10, 12.5, 15 ㏖% excess lead), the PLT films were deposited by sol-gel process. DTA analyses reveal that the crystallization temperature of the precursor powers decreased with increasing amount of excess lead. XRD patterns of PLT reveal pure perovskite structure and the preferred orientation increased with increasing Pb content in the films. With increasing amount of excess P$\_$b/, the relative permittivity ($\xi$$\_$r/) increased and leakage current density at 100 ㎸/cm transformed 4.01$\times$10$\^$-5/, 2.42$\times$10$\^$-6/, 1.27$\times$10$\^$-6/, 1.56$\times$10$\^$-6/A/㎠ respectively. In the results of hysteresis loops measured at 166 kV/cm, the remanent polarization (P$\_$r/) and the coercive field (E$\_$c) are 6.36$\mu$C/cm and 58.7 ㎸/cm, respectively (at 12.5 ㏖% excess P$\_$b/) With increasing amount of excess Pb, the remanent polarization for PLT thin film degraded to about 44%, 27%, 15%, 16% of the initial value after 10$\^$9/ cycles./TEX>) With increasing amount of excess Pb, the remanent polarization for PLT thin film degraded to about 44%, 27%, 15%, 16% of the initial value after $10^{9}$ cycles.

• Journal of Welding and Joining
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• v.4 no.3
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• pp.13-25
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• 1986

철강 구조물의 용접기술에 있어 용접부의 신속성을 좌우하는 가장 중요한 요소는 용접균열에 관한 문제와 용접본드부의 취화에 관한 문제로 요약될 수 있다. 일반적으로 용접부 및 그 근방의 금속은 국부적으로 매우 높은 온도까지 급열된 후 급냉되므로, 용접부에서 각종균열의 발성 위험성이 높아지고 용접본드부를 취화하여 파양인성의 저하를 초래하게 된다. 따라서 이러한 문 제점을 극복하기 위해서는 재료의 선택이나 설계, 시공, 검사의 각 단계에서 충분한 검토가 필 요하다. 특히 최근 들어 이전보다 높은 강도의 고장력강재가 널리 사용되고 구조물의 대형화에 따라 구속조건이 증대되며 구조물의 사용 조건은 더욱 가혹 화함에 따라 상술한 문제점은 더욱 중요시되고 있다. 철강 용접부에 발생하는 균열은 용접시공시 발생되는 균열과 용접완료후 구 조물 사용중에 발생되는 균열로 대별될 수 있다. 용접시공중 발생되는 균열은 용접열싸이클로 인해 생성되는 조직, 석출물등의 치금학적 요인과 잔유응력 또는 구속응력등의 역학적 요인이 중첩됨으로서 발생된다. 또한 사용중 발생되는 균열은 상기의 두 가지 요인이외에 환경적 요인이 첨가되어 발생된다고 볼 수 있다. 이상과 같은 용접균열을 방지하기 위해서는 실 구조물 용접 조립시의 각종 조건을 재현한 시험법을 통해 용접균열 발생의 한계조건을 정량적으로 분석할 필요가 있다. 이러한 균열 시험의 결과, 적정한 용접 시공 조건이 도출될 수 있기 때문이다. 이와 같은 필요성에 의해 지금까지 다수의 용접균열 시험법에 관한 연구가 행하여져 왔고 그 중에는 각 국가의 협회나 학회의 규격으로 확립된 것도 많으며 국제규격으로 되어 있는 것도 있다. 본 고에서는 각종균열들에 대한 지금까지 밝혀진 기구들에 대해 해설하고, 그 각각에 적용되고 있는 시험법들에 대해 소개하고저 한다.C1지구의 공업.생활용수는 103units, 33units로 배분되고, 하류지구에 304units로 배분되었다. 따라서 용도별로 물배분하므로서 금호강 하루지역에 더욱 많은 물을 배분할 수 있음을 알았다.통해서 수위-유량관계(rating curve)를 규명하였다. 시험지구의 관개효율 및 용수손실 규명 등에 관한 기본자료를 수집하기 위해서는 계측시스템의 운영은 장기간으로 지속 되어야 한다며, 전기전도도와 토양수 농도, 전기전도도와 함수량의 관계를 이용한 천이상태의 오염원 농도 측정방법을 개발하였다. 특히 제안식에서는 한계함수량의 개념을 도입하여 전기전도도와 함수량관계를 추정하므로 추정식의 실험값 반영 정도를 증가시켰다. 본 연구에서 제안된 식을 이용하여 추정된 전기전도도와 함수량관계는 다른 제안식에 비하여 개선된 결과를 보여 주었고, 본 연구에서 개발한 오염원 농도 측정법을 이용하여 측정한 결과 함수량이 0.15이하에서는 측정오차가 크지만 함수량이 0.15이상일 경우 매우 좋은 결과를 보였는데 질량평형을 검토한 결과 약 5-10%의 오차율을 보였다. 따라서 본 논문에서 개발된 천이상태의 오염원 농도측정법은 용존 오염물질의 이송에 관한 정확한 실험을 제공할 것으로 판단된다.며, 수질 보전적-환경 보전 차원에서 저수관리 체계를 확고히 할 수 있는 방안을 강구하여야 할 것이다.펄스주입법에 의해 증착된 박박은 강유전성 이력을 나타내었다.지역과 비도시지역을 비교하는 조사 연구가 필요하며, 이러한 조사결과를 바탕으로 자녀의 식습관에 대한 교육을 위한 교재, 교구의 개발과 영양, 식습관 교육프로그램의 개발을 통해 가정과 학교에서 부모와 교사가 자녀의 식생활 지도 관리를 돕고 가정과 교육기관이 연계한 교육 프로그램이 활성화 될 수 있도록 지속적인 관심을 기울여 나가야 할 것이며, 이에 따른

• Tunnel and Underground Space
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• v.33 no.1
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• pp.57-69
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• 2023

In this study, we simulated induced seismicity in the Groningen natural gas reservoir using 2D hydro-mechanical coupled discrete element modelling (DEM). The code used is PFC2D (Particle Flow Code 2D), a commercial software developed by Itasca, and in order to apply to this study we further developed 1)initialization of inhomogeneous reservoir pressure distribution, 2)a non-linear pressure-time history boundary condition, 3)local stress field monitoring logic. We generated a 2D reservoir model with a size of 40 × 50 km² and a complex fault system, and simulated years of pressure depletion with a time range between 1960 and 2020. We simulated fault system failure induced by pressure depletion and reproduced the spatiotemporal distribution of induced seismicity and assessed its failure mechanism. Also, we estimated the ground subsidence distribution and confirmed its similarity to the field measurements in the Groningen region. Through this study, we confirm the feasibility of the presented 2D hydro-mechanical coupled DEM in simulating the deformation of a complex fault system by hydro-mechanical coupled processes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.33-43
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• 2005

Traffic condition monitoring system serves as the foundation for all intelligent transportation system operation. Loop detectors and Video Image Processing are the most widely common technology approach to condition monitoring in korea Highways. Lane Usage is defined as the proportion of total link volume served by each lane. In this research, the lane Usage(LU) of two lane link for one day. Interval is 56% : 44%. The LU of three lane link is 39% : 37% : 24%. The LU of four lane link is 25% : 29% : 26% : 21%. These analysis reveal that each lane distributions of link are not same. This research investigates the general concept of lane usage by using collected loop detector data and the investigated that lane distribution is different by traffic lane and lane usage is consistent by time of day.