• 자동차안전학회지
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• 제4권1호
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• pp.5-11
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• 2012

This paper discusses the evaluation of the safety impact of the Adaptive Cruise Control (ACC) system in Korea. To evaluate the safety impact, this paper suggests an analysis method by using the test scenario and field operational test data. The test scenario is composed to represent the main component factor of the ACC system and ACC related accident situation such as rear-end collision, lane-change, and road-curvature, etc. Also, from the field operation test data, the system's potential to increase the safety can be measured ideally. Besides, field operational testdata was used to revise the expected safety impact value as Korean road conditions. By using the proposed evaluation method, enhanced safety impact of the ACC system can be estimated scientifically.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.2353-2355
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• 2010

Since the efforts in transportation for counteracting Climate Change have been enhanced, it is necessary to reduce GHG emissions from railroad construction. The aim of this study was to develop the calculation method of GHG emissions at the step of railroad construction. Main emission source was the energy consumption from the used heavy equipments. Firstly, GHG inventory including equipments list, energy consumption, and work load was established with the detailed process using standard for the unit cost of construction. Also, the energy consumption of heavy equipments during track construction at A site was collected to compare with the field data. As a result, the GHG emissions between the estimated and the field were a little different, which was caused by the inaccurate field data. Therefore, it is important to manage data efficiently for the calculation of GHG emissions in the field of railroad construction.

• 산업경영시스템학회지
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• 제25권6호
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• pp.36-41
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• 2002

We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. we show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.777-779
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• 2003

This paper describes the real-time data linkage of the field control system for distributed control in nuclear power plant environment. The most important keys of digital control system in nuclear power plant are the reliability and stability of system, and real-time control ability. This Paper brought up the hardware construction using a new method about the design of each station located upon control transmission network to improve real-time ability of field control system, and measured the station binding time between devices connected to field control module. And it was confirmed performance improvement of overall system for real-time data linkage between control devices.

• 천문학회보
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• 제44권1호
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• pp.52.2-52.2
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• 2019

Global map of solar surface magnetic field, such as the synoptic map or daily synchronic frame, does not tell us real-time information about the far side of the Sun. A deep-learning technique based on Conditional Generative Adversarial Network (cGAN) is used to generate farside magnetograms from EUVI $304{\AA}$ of STEREO spacecrafts by training SDO spacecraft's data pairs of HMI and AIA $304{\AA}$. Farside(or backside) data of daily synchronic frames are replaced by the Ai-generated magnetograms. The new type of data is used to calculate the Potential Field Source Surface (PFSS) model. We compare the results of the global field with observations as well as those of the conventional method. We will discuss advantage and disadvantage of the new method and future works.

• 한국융합학회논문지
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• 제8권11호
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• pp.103-108
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• 2017

유비쿼터스 환경에서는 다양한 센서로 부터 원거리에 데이터를 전송해야 하는 문제가 제기되어져 왔다. 특히 서로 다른 위치에서 도착한 데이터를 통합하는 과정에서 데이터의 속성 값들이 상이하거나 데이터에 일부 손실이 있는 데이터들도 처리해야 하는 어려운 문제를 가지고 있었다. 본 논문은 이와 같은 데이터들을 대상으로 집락분석 하는 방법을 제시한다. 이 방법의 핵심은 문제에 적합한 목적함수를 정의하고, 이 목적함수를 최적화 할 수 있는 알고리즘을 개발하는데 있다. 목적함수는 OCS 목적함수를 변형하여 사용한다. 이진 값을 가지는 데이터만을 처리할 수 있었던 MFA(Mean Field Annealing)을 연속 값을 가지는 분야에도 적용할 수 있도록 확장한다. 그리고 이를 CMFA이라 명하고 최적화 알고리즘으로 사용한다.

• Journal of Construction Engineering and Project Management
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• 제1권1호
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• pp.37-43
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• 2011

Labor productivity is a significant factor associated with controlling time, cost, and quality. Many researchers have developed models to define methods of measuring the relationship between productivity and various parameters such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only entails the average productivity data of the construction industry, and it is difficult to predict the time and cost spent on any particular project. As a result, errors occur in estimating duration and cost for individual activities or projects. To address these issues, this research sought to collect data, measure productivity, and develop time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites. It is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• 한국지하수토양환경학회지:지하수토양환경
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• 제28권spc호
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• pp.18-39
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• 2023

Rapid development of geophysical exploration and hydrogeologic monitoring techniques has yielded remarkable increase of datasets related to groundwater systems. Increased number of datasets contribute to understanding of general aquifer characteristics such as groundwater yield and flow, but understanding of complex heterogenous aquifers system is still a challenging task. Recently, applications of data science technique have become popular in the fields of geophysical explorations and monitoring, and such attempts are also extended in the groundwater field. This work reviewed current status and advancement in utilization of data science in groundwater field. The application of data science techniques facilitates effective and realistic analyses of aquifer system, and allows accurate prediction of aquifer system change in response to extreme climate events. Due to such benefits, data science techniques have become an effective tool to establish more sustainable groundwater management systems. It is expected that the techniques will further strengthen the theoretical framework in groundwater management to cope with upcoming challenges and limitations.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.256-261
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• 2011

Labor productivity is a significant factor related to control time, cost, and quality. Many researchers have developed models to define method of measuring the relationship between productivity and various constraints such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only contains the average productivity data of the construction industry, and it is difficult to predict the time and cost of any particular project; hence, there are some errors in estimating duration and cost for individual activity and project. To address these issues, this research collects data, measures productivity, and develops time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites and it is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• Wind and Structures
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• 제20권6호
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• pp.739-749
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• 2015

Field measurement of wind characteristics is of great significance for the wind engineering community. High-frequency anemometers such as ultrasonic anemometers are widely used to obtain the high-frequency fluctuating wind speed time history. However, conventional instrumentation systems may suffer from low efficiency, non-real time transmission and higher maintenance cost, and thus are not very appropriate in the field measurement of strong winds in remote areas such as mountain valleys. In order to improve the field measurement performance in those remote areas, a wireless high-frequency anemometer instrumentation system for field measurement has been developed. In this paper, the architecture of the proposed instrumentation system, and measured data transmission and treatment will be presented firstly. Then a comparison among existing instrumentation systems and the proposed one is made. It shows that the newly-developed system has considerable advantages. Furthermore, the application of this system to the bridge site located in the mountain valley is discussed. Finally, typical samples of measured data from this area are presented. It can be expected that the proposed system has a great application potential in the wind field measurement for remote areas such as the mountainous or island or coastal area, and hazardous structures such as ultra-voltage transmission tower, due to its real-time transmission, low cost and no manual collection of data and convenience.