• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.784-785
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• 2024

형량 예측 연구는 법률 인공지능에서 가장 활발히 연구되고 있는 분야 중 하나이며, 비법률전문가의 사법 신뢰도 상승과 법률전문가의 업무 부담 완화에 긍정적 영향을 줄 수 있다. 본 연구는 형사 사건의 양형 예측에 ChatGPT 를 접목하여 입력된 사실관계와 유사한 선행 판례를 검색함으로써 형량 예측에 필요한 모델의 훈련 시간과 비용을 절감하는 접근법을 제안한다. 본 모델의 weighted F1-score 는 0.53 으로, 미세조정된 BERT 모델과 유사한 성능을 기록하였다.

• Tunnel and Underground Space
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• v.14 no.6 s.53
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• pp.399-410
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• 2004

The utilization of AS(Artificial Intelligence) and Database could be considered as an useful access for the application of underground information from the point of a geotechnical methodology. Its detailed usage has been recently studied in many fields of geo-sciences. In this paper, the target of usage is on controlling the injection of grout which more scientific access is needed in the grouting that has been used a major method in many engineering application. As the proposals for this problem it is suggested the methodology consisting of a fuzzy-neural hybrid system and a database. The database was firstly constructed for parameters dynamically varied according to the conditions of rock mass during the injection of grout. And then the conceptional model for the fuzzy-neural hybrid system was investigated fer optimally finding the controlling range of the grout valve. The investigated model applied to four cases, and it is found that the controlling range of the grout valve was reasonably deduced corresponding to the mechanical phenomena occurred by the injection of grout. Consequently, the algorithm organizing the fuzzy-neural hybrid system and the database as a system can be considered as a tool for controlling the injection condition of grout.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.480-484
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• 2008

셀렝게(Selenga)강은 몽골에서 발원하여 세계최대의 담수호로 알려진 러시아 바이칼호로 유입되는 국제하천으로서 소비에트 연방해체 이후 계획경제가 무너지면서 다양한 물환경문제에 노출되어 있다. 몽골의 경우 도시개발이 급격히 진행되고 있으나 처리시설의 미비로 인한 오폐수 배출 및 무분별한 광산개발에 따른 수질오염문제가 현안이 되고 있으며, 러시아(브리아트공화국)는 계획경제의 붕괴에 따른 산업구조의 변화, 처리시설의 부족 및 운영의 비효율성, 산림자원의 개발에 따른 비점오염부하의 증가 등의 수질문제 해결이 요구된다. 몽골은 자연적인 특성상 광물질을 많이 포함하는 지표수 성상 및 매우 적은 강우량으로 인한 수자원의 부족, 지역별로 극심한 물공급량의 불균형, 산업개발에 따른 지하수 오염 등의 문제를 포함한 수자원 부족이 해결해야할 현안과제이고, 러시아는 수자원은 매우 풍부하나 공급시설의 낙후 및 비효율적인 운영으로 인한 물 공급 시스템의 개선이 절실히 요구되는 상황이다. 물 환경관리 체계를 보면 양국 공히 대내적으로는 이용 및 공급 주체별로 분화된 물 관리체제로 인해 부문간 통합성이 결여되어 있으며, 대외적으로는 셀렝게강 상 하류 물이용 개발, 수질보전 및 수생태계보호와 연관된 문제해결을 위한 몽골과 러시아간의 국제적인 협력시스템이 없는 실정이다. 경제개발에 따라 최근 수질오염 및 물이용 개발과 관련된 이해당사자 간의 갈등이 심화되고 있어 이를 지역, 국가, 국제적인 차원에서 조정할 수 있는 통합관리시스템의 구축과 이해당사자의 인식제고 및 자체적인 관리능력 배양을 위한 역량강화프로그램의 개발 운영이 요구되고 있다. 따라서 본 연구에서는 동지역에서 기초현황조사, 물 환경현안 파악, 물 관리정책 및 체계와 문제점을 파악하고 향후 DPISR(Drivers-Pressures-Impact-State- Response) 분석이 가능하도록 물환경관리와 연관된 물환경상태, 현안, 원인, 영향 및 대책을 종합적인 관점에서 분석하며, 해외의 주요 국제하천의 물 환경관리모델에 대한 사례분석 및 비교연구를 통해 물이용 및 개발과 관련된 이해상충 조정체계를 개발하고자 하였다.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.6
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• pp.794-801
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• 2012

Finite Element Method is a strong tool to analyse static and dynamic problem of a structure. FEM is a good method for static problem, but for dynamic problem there are some differences between real phenomena and analyzed phenomena. Therefore some modifications are needed to identify two results. In this paper authors propose a genetic algorithm method 1) to adjust dimensions of plate for identifying natural frequencies, 2) to fit amplitude of FEM Frequency Response Function(FRF) onto it of real FRF. Analysis by raw FEM data gave questions if the results were for the same object. By only adjusting Young's modulus much better accordances were obtained, but limitation existed still. Very good agreements were achieved by shape modification and damping coefficient identification.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.336-343
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• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.200-209
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• 2019

When forecasting future values, a model estimated after minimizing training errors can yield test errors higher than the training errors. This result is the over-fitting problem caused by an increase in model complexity when the model is focused only on a given dataset. Some regularization and resampling methods have been introduced to reduce test errors by alleviating this problem but have been designed for use with only a given dataset. In this paper, we propose a new optimization approach to reduce test errors by transforming a test error minimization problem into a training error minimization problem. To carry out this transformation, we needed additional data for the given dataset, termed pseudo data. To make proper use of pseudo data, we used three types of missing data imputation techniques. As an optimization tool, we chose the least squares method and combined it with an extra pseudo data instance. Furthermore, we present the numerical results supporting our proposed approach, which resulted in less test errors than the ordinary least squares method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.9
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• pp.916-922
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• 2009

Because thermal design of satellite carrying out mission in space is performed by thermal analysis result using thermal mathematical model, accuracy of thermal mathematical model is important and it can be improved by model correlation. Correlation steps of satellite thermal math model are composed of modeling of satellite configuration placed in thermal vacuum chamber, verification of correspondence between thermal math model and real satellite configuration, and adjustment of modeling parameters from major part to minor part etc. In this study, correlation success criteria was established and correlation for satellite thermal math model was performed using result of thermal vacuum test of satellite structure-thermal model to meet the success criteria. The overall results satisfied the criteria and this correlated thermal model was applied for detailed thermal design of satellite.

• Korean Journal of Construction Engineering and Management
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• v.5 no.4 s.20
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• pp.107-114
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• 2004

This paper represents the application of the 3D CAD Model data for 4D simulation and quantity estimation. These support the effective and practical use of 4D CAD model. By using and manipulating the 3D CAD model information, scheduling and quantity estimation could be developed more quickly and effectively. So the 3D CAD model information is made use of not only drawing a blueprint but also playing an important part of data integration platform. The scheduling module sets up the schedule generation logic that consists of period, priority of element arrangement, and time lag of floor placement. It sorts the working items as a priority of working process. And the quantity estimation module queries the material quantity of the structural elements according to the scheduling conditions. These two modules are developed using the 3D CAD model information and assist the function of 4D CAD model.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.757-764
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• 2013

The estimation of maintenance cost of information system so far has been conducted centered on the ordering body, so the problem of provider's having to cover the cost due to small cost compared to the amount of work is not solved. This study is a base study for estimating the maintenance cost of information system centered on provider, and it deduces cost items of maintenance and suggests adjustment factors for adjusting the gap between the ordering body and provider regarding the maintenance cost. In order to deduce the cost items of maintenance, this study adds the activities of the provider for maintenance to the base study of cost factors regarding the existing maintenance activity, divides, and classifies them into the fixed cost and variable cost. In order to adjust the gap between the ordering body and provider regarding the maintenance cost, this study found the adjustment factors such as the code, utility, and components created by the automatic tool that was not included when estimating the maintenance cost centered on the ordering body. After examining and analyzing K Company's data of maintenance performance for three years, it confirmed that the gap regarding the adjustment factors was about 13% in case of K Company.

• Journal of Advanced Navigation Technology
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• v.2 no.1
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• pp.61-67
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• 1998

In this paper, we have described the Ramp Activity Coordination Expert System (RACES) which can solve aircraft parking problems. RACES includes a knowledge-based scheduling problem which assigns every daily arriving and departing flight to the gates and remote spots with the domain specific knowledge and heuristics acquired from human experts. RACES processes complex scheduling problem such as dynamic inter-relations among the characteristics of remote spots/gates and aircraft with various other constraints, for example, custome and ground handling factors at an airport. By user-driven modeling for end users and knowledge-driven near optimal scheduling acquired from human experts, RACES can produce parking schedules of aircraft in about 20 seconds for about 400 daily flights, whereas it normally takes about 4 to 5 hours by human experts. Scheduling results in the form of Gantt charts produced by the RACES are also accepted by the domain experts. RACES is also designed to deal with the partial adjustment of the schedule when unexpected events occur. After daily scheduling is completed, the messages for aircraft changes and delay messages are reflected and updated into the schedule according to the knowledge of the domain experts. By analyzing the knowledge model of the domain expert, the reactive scheduling steps are effectively represented as rules and the scenarios of the Graphic User Interfaces (GUI) are designed. Since the modification of the aircraft dispositions such as aircraft changes and cancellations of flights are reflected to the current schedule, the modification should be notified to RACES from the mainframe for the reactive scheduling. The adjustments of the schedule are made semi-automatically by RACES since there are many irregularities in dealing with the partial rescheduling.