• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.239-245
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• 2000

This study is aimed to develop the historical data management system named "ACON"(Actual COst Network system) which can be used for collecting, analysis and modification of the historical data. ACON_Local is used for collecting the historical data at each spot place. It redueces the work potential of managers, spending time and cost. ACON_Analysis is to analyze the collection , modifies the data′s error and updates the historical database. ACON_Network is developed to transfer data from ACON to Web server or opposites. The proposed model, ACON, provide the easy way for the cost estimate system, "HiCOMS" to collect, analyze and modify the historical cost evaluated data, which is used to compose the historical data base.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.468-471
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• 2001

건설공사를 수행하는데 있어 초기 프로젝트 계획에 대한 중요성이 널리 인식되어 지고 있다. 프로젝트와 관련된 방대한 양의 실적자료들이 초기 계획단계에서부터 활용될 수 있다면, 프로젝트의 전체 범위와 비용견적을 비교적 정확하게 예측할 수 있는 중요한 원천이 될 것이다. 그러나, 공사 실적자료들의 축적, 분석, 활용의 정도가 미비하여 상당한 양의 유용한 정보들이 쉽게 사장되거나 적용되지 못한 채 보유되고 있다. 이런 문제점을 개선하기 위해서는 건설사업 참여자들이 획득한 수많은 양의 실적자료들을 유용한 지식으로 획득, 저장, 공유, 활용할 수 있는 체계적, 종합적인 실적자료관리시스템을 개발하여 관리할 필요성이 있다. 본 연구에서는 이러한 기술적 흐름과 병행하여, 현재 건설공사의 실적자료들을 효과적으로 관리하여 유사프로젝트에 유용하게 이용하고자 한다

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.119-126
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• 2004

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristic. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• 산업공학
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• 제18권4호
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• pp.382-389
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• 2005

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristics. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• Asian review of World Histories
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• 제4권1호
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• pp.3-34
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• 2016

This introduction is both a statement of a research problem and an account of the first research results for its solution. As more historical databases come online and overlap in coverage, we need to discuss the two main issues that prevent 'big' results from emerging so far. Firstly, historical data are seen by computer science people as unstructured, that is, historical records cannot be easily decomposed into unambiguous fields, like in population (birth and death records) and taxation data. Secondly, machine-learning tools developed for structured data cannot be applied as they are for historical research. We propose a complex network, narrative-driven approach to mining historical databases. In such a time-integrated network obtained by overlaying records from historical databases, the nodes are actors, while thelinks are actions. In the case study that we present (the world as seen from Venice, 1205-1533), the actors are governments, while the actions are limited to war, trade, and treaty to keep the case study tractable. We then identify key periods, key events, and hence key actors, key locations through a time-resolved examination of the actions. This tool allows historians to deal with historical data issues (e.g., source provenance identification, event validation, trade-conflict-diplomacy relationships, etc.). On a higher level, this automatic extraction of key narratives from a historical database allows historians to formulate hypotheses on the courses of history, and also allow them to test these hypotheses in other actions or in additional data sets. Our vision is that this narrative-driven analysis of historical data can lead to the development of multiple scale agent-based models, which can be simulated on a computer to generate ensembles of counterfactual histories that would deepen our understanding of how our actual history developed the way it did. The generation of such narratives, automatically and in a scalable way, will revolutionize the practice of history as a discipline, because historical knowledge, that is the treasure of human experiences (i.e. the heritage of the world), will become what might be inherited by machine learning algorithms and used in smart cities to highlight and explain present ties and illustrate potential future scenarios and visionarios.

• 한국콘텐츠학회논문지
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• 제6권1호
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• pp.114-125
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• 2006

오늘날 무선 인터넷과 소형 이동 통신 기기 보급의 확산과 GPS 활용도의 급증으로 시간 변화에 따라 위치 정보가 연속적으로 변화하는 이동 객체의 연구가 활발히 이루어지고 있다. 그 중에서 차량 이동 객체에 대한 연구는 첨단 교통 정보 시스템, 차량 추적 시스템, 물류 수송 시스템에서 활용되고 있다 이들 시스템들은 차량 이동에 대한 이력 데이터를 관리함으로서 과거의 차량 위치, 미래의 차량 위치 예측, 최적 경로, 최단 경로를 탐색 할 때 유용하게 사용되고 있다. 뿐만 아니라 물류 수송 계획과 차량 배차에도 차량 이력 데이터가 활용되고 있다. 이러한 차량 이력 데이터는 일정한 시간 간격을 갖고 저장되는데, 같은 패턴이 반복되는 차량 이력 데이터를 갖는 경우도 존재한다. 예를 들어, 특정 구간을 반복적으로 운행하는 차량일 경우에는 거의 유사한 경로로 운행을 한다. 이런 반복적인 운행경로를 일정 시간 간격 마다 차량 이력 데이터로 저장하면 많은 중복 데이터가 발생함으로써 저장 공간의 낭비를 유발한다. 따라서 본 논문에서는 이런 반복적인 운행경로를 갖는 차량에 대하여 이력 데이터를 효율적으로 저장할 수 있는 유사 궤적을 이용한 차량 이력 데이터 저장 기법을 제안하고자 한다.

• 한국의류학회지
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• 제32권11호
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• pp.1680-1691
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• 2008

This study examines how the development and value of dresses shown in MBC historical dramas have changed with the overall change of the dramas. As for the research method, the second data analysis was done with literature study which was supplemented with interviews with the wardrobe team of MBC production design center. Historical dramas produced by MBC have gone through the developmental period, legitimate historical drama-oriented period, stagnant period, and historical dramas-modernized period. The value of costume in each period is as follows: Costume in the developmental period is considered only as part of drama setting. During legitimate historical drama-oriented period, it carries value as educational data and historical replica produced by historical research. Production design including costume obtains its own value in the stagnant period although the production of historical dramas decreases dramatically. And lastly, in the historical dramas-modernized period, costume starts to have commercial value as cultural contents. Historical drama costume may contain important value in terms of education and history, even though there has been controversy on TV historical dramas' role: they should focus on reproducing historical facts or they should support writers' creativity.

• 한국농공학회지
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• 제40권3호
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• pp.35-41
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• 1998

Cost estimate system Will be changed from the prime. cost calculation to the historical cost data because the present system has some problems. In this situation, each owner should prepare his own cost estimate system based on the historical cost data. In this study, the standard work items were classified and the criteria of their work amount computation were established for rural improvement projects. And also the historical cost data were collected in all range of rural improvement projects, and the database system, "HICOMS" (HIstorical COst data Management System) was built. In order to test the applicability of the HICOMS, standard work cost and contractor cost were compared. The results by HICOMS showed high significance and it was concluded that the HICOMS could be applicable for the cost estimate of the rural improvement projects. projects.

• Journal of Information Technology Applications and Management
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• 제29권5호
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• pp.27-37
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• 2022

This study intends to link agricultural machine history data with related organizations or collect them through IoT sensors, receive input from agricultural machine users and managers, and analyze them through AI algorithms. Through this, the goal is to track and manage the history data throughout all stages of production, purchase, operation, and disposal of agricultural machinery. First, LSTM (Long Short-Term Memory) is used to estimate oil consumption and recommend maintenance from historical data of agricultural machines such as tractors and combines, and C-LSTM (Convolution Long Short-Term Memory) is used to diagnose and determine failures. Memory) to build a deep learning algorithm. Second, in order to collect historical data of agricultural machinery, IoT sensors including GPS module, gyro sensor, acceleration sensor, and temperature and humidity sensor are attached to agricultural machinery to automatically collect data. Third, event-type data such as agricultural machine production, purchase, and disposal are automatically collected from related organizations to design an interface that can integrate the entire life cycle history data and collect data through this.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.13-26
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• 2008

Inference on the present data will be more reliable when the data arising from previous similar studies are available. The data arising from previous studies are referred as historical data. The power prior is defined by the likelihood function based on the historical data to the power $a_0$, where $0\;{\le}\;a_0\;{\le}\;1$. The power prior is a useful informative prior for Bayesian inference such as model selection and model comparison. We utilize the historical data to perform multiple comparison in the one-way ANOVA model. We demonstrate our results with some simulated datasets under a simple order restriction between the treatments.