• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.421-428
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• 2011

The communication of each others is lack between planing, design, construction and maintenance in domestic construction industry. This problem makes the omission of information and the loss of cost. So, the introduction of BIM can be the solution about that. BIM manages all information generated during all life-cycle of a structure and consequently maximizes the efficiency of utilizing information. This is done through 3D information model associated with a three-dimensional(3D) parametric CAD. This study proposes the seismic analysis process of steel box bridge for structural design of bridge construction project based on BIM. The additional process is needed for the purpose that structural data is inherent in the property information of 3D information model. This process has 3D modeling progress done by using the information decided in design phase. The design document of seismic analysis can be derived with the proposed process to steel box bridge.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.3
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• pp.91-100
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• 2017

The solution was developed for the maintenance decision support of combined cycle power plant gas turbine. The developed solution was applied to MHI501G gas turbine and is, in present, on the process of field test at GUNSAN combined cycle power plant, South Korea. The developed solution provides the calculated result of optimal overhaul maintenance period through following modules: Real Time Performance Monitoring, Model-Based Diagnostics, Performance Trend Analysis, Optimal Overhaul Maintenance Interval, Compressor Washing Period Management, and Blade Path Temperature Analysis. Model-Based Diagnostics module analyzed the differences between the data of gas turbine performance model and the online measurement. Compressor washing management module suggests the optimal point of balancing between the compressor performance and the maintenance cost.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.126-126
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• 2019

과거부터 수자원분야는 공학적인 측면을 주로 강조하였으며, 따라서 인문사회학적 요소(예, 토지이용, 인구, 생태 환경, 경제발전 등)가 종종 배제된 채 시설물 계획이 이루어졌다. 그러나, 경제가 발전하고 사회의 모습이 복잡해짐에 따라, 수자원 관련 시설물의 계획에 있어 다양한 인문사회학적 요소를 고려할 필요성이 높아지고 있다. 본 연구에서는 사회-수문 모델링 기법을 이용하여 사회-수문 상호 간 순환적 관계를 파악하고, 특히 다목적댐이 인문사회에 미치는 영향을 정략적으로 파악하고자 하였다. 우리나라는 기후변화에 의한 극한가뭄과 홍수발생 빈도가 증가하고 있다. 이에 대한 대책으로, 다목적댐을 건설하여 효율적인 수자원 관리를 하고 있다. 본 연구에서는 대상지역으로 국내 강원도의 횡성댐을 선정하였다. 횡성댐은 하류에 위치한 횡성군과 원주시에 생 공 농업용수를 공급하는 용수원의 역할과 섬강 하류지역에 발생하는 홍수를 방어하는 역할을 하고 있다. 횡성댐 유역의 사회-수문학적 관계를 이해하기 위해 인과지도를 이용한 시스템 요소간의 상호연관성을 파악하였고, 이를 바탕으로 수문학적 요소와 인문사회학적 요소 사이의 관계식을 구성하였다. 수자원 분야에 해당하는 요소로는 생 공 농업용수 이용량 및 댐 저수량과 방류량을 선정하였으며, 인문사회학적 요소는 인구, 공업지역 농경지 주거지역의 면적 및 지역 내 총생산액을 선정하였다. 이와 같은 사회-수문학 요소를 바탕으로 해당 지역의 사회-수문 전체의 동태적 변화를 이해하기 위해 시스템 동적모의(System Dynamics) 모형을 이용한 모델링을 진행하였다. 다목적댐 건설 전 후로 대상지역의 용수 이용량과 인구 및 지역 총생산액 등의 데이터를 수집하여 모델을 검증하였다. 나아가 구현한 모형을 활용하여 향후 기후변화 발생 시 다목적댐이 대상지역의 용수이용 및 인구변화, 지역경제에 미치는 영향을 정량적으로 분석하였다. 본 연구는 인문사회분야와 수자원분야 사이의 영향관계를 이해하고, 모델을 이용한 정량적인 분석을 통해 향후 수자원 시설물 계획 및 정책마련을 위한 의사결정도구로 활용될 수 있을 것으로 기대한다.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.762-769
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• 2022

Genetic testing in prenatal diagnosis is a precious tool providing valuable information in clinical management and parental decision-making. For the last year, cytogenetic testing methods, such as G-banding karyotype analysis, fluorescent in situ hybridization, chromosomal microarray, and gene panels have evolved to become part of routine laboratory testing. However, the limitations of each of these methods demonstrate the need for a revolutionary technology that can alleviate the need for multiple technologies. The recent introduction of new genomic technologies based on next-generation sequencing has changed the current practice of prenatal testing. The promise of these innovations lies in the fast and cost-effective generation of genome-scale sequence data with exquisite resolution and accuracy for prenatal diagnosis. Here, we review the current state of sequencing-based pediatric diagnostics, associated challenges, as well as future prospects.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.109-123
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• 2004

Corporate financial distress and bankruptcy prediction is one of the major application areas of artificial neural networks (ANNs) in finance and management. ANNs have showed high prediction performance in this area, but sometimes are confronted with inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large because training the large data set needs much processing time and additional costs of collecting data. Instance selection is one of popular methods for dimensionality reduction and is directly related to data reduction. Although some researchers have addressed the need for instance selection in instance-based learning algorithms, there is little research on instance selection for ANN. This study proposes a genetic algorithm (GA) approach to instance selection in ANN for bankruptcy prediction. In this study, we use ANN supported by the GA to optimize the connection weights between layers and select relevant instances. It is expected that the globally evolved weights mitigate the well-known limitations of gradient descent algorithm of backpropagation algorithm. In addition, genetically selected instances will shorten the learning time and enhance prediction performance. This study will compare the proposed model with other major data mining techniques. Experimental results show that the GA approach is a promising method for instance selection in ANN.

• Journal of Service Research and Studies
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• v.3 no.2
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• pp.53-60
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• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• Journal of radiological science and technology
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• v.28 no.4
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• pp.317-325
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• 2005

The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. That is, with the new guidelines and technology, hospital business escapes simple fee calculation and insurance claim center. Moreover, MIS(Medical Information System), PACS(Picture Archiving and Communications System), OCS(Order Communicating System), EMR(Electronic Medical Record), DSS(Decision Support System) are also developing. Medical Information System is evolved toward integration of medical IT and situation si changing with increasing high speed in the ICT convergence. These changes and development of ubiquitous environment require fundamental change of medical information system. Mobile medical information system refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to Internet whenever and wherever. RFID is one of the technologies for Automatic Identification and Data Capture(AIDC). It is the core technology to implement Automatic processing system. This paper provides a comprehensive basic review of RFID model in Korea and suggests the evolution direction for further advanced RFID application services. In addition, designed and implemented DB server's agent program and Client program of Mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented medical information system that performed patient data based EMR, HIS, PACS DB environments, and so reduced delay time of requisition, medical treatment, lab.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.39-50
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• 2022

Based on the signaling theory, this study examined whether startups are more likely to attract venture investment when receiving government R&D subsidies. First, we reviewed previous studies of the investment decision-making process of venture capitalists and understood the conditions that influence investment decisions. Based on previous studies on the signal effect of government subsidies, particularly government R&D grants, on inducing private fund investment, this study revealed a mechanism to induce venture investment by startups. In addition, in order to verify whether government R&D subsidies have the effect of inducing venture investment, an empirical analysis was conducted based on data from startups under seven years and certified as a venture companies in 2021. This paper used PSM(Propensity Score Matching) method and DID(Difference In Difference) analysis for an empirical study to analyze the average treatment effect on the treated group(beneficiary startups of government R&D grants). As a result of empirical analysis, companies that receive more government R&D subsidies after starting a business are more likely to attract venture investment. From two to three years after conducting the first government R&D project, startups that received government R&D grants attracted more venture investment than those that did not. The results of this paper demonstrate that government R&D projects can also affect the venture investment ecosystem, giving policy implications to government R&D projects targeting startups. It is also expected to suggest strategic implications to startups that need new funding.

• Journal of Korean Library and Information Science Society
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• v.54 no.2
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• pp.23-42
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• 2023

The library tour program is a new type of cultural program that was first introduced and operated by J City, and library tourists travel to specialized libraries in the city according to a set course and experience various experiences. This study aims to build a customized course recommendation model that considers the characteristics of individual participants in addition to the existing fixed group travel format so that more users can enjoy the opportunity to participate in library tours. To this end, the characteristics of library travelers were categorized to establish traveler personas, and library evaluation items and evaluation criteria were established accordingly. We selected 22 libraries targeted by the library travel program and measured library data through actual visits. Based on the collected data, we derived the characteristics of suitable libraries and developed a persona-based library tour course recommendation model using a decision tree algorithm. To demonstrate the feasibility of the proposed recommendation model, we build a mobile application mockup, and conducted user evaluations with actual library users to identify satisfaction and improvements to the developed model.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.891-899
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• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.