• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.337-351
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• 2018

This paper discusses 5G IOT, Augmented Reality, Cloud Computing, Big Data, Future Autonomous Driving Vehicle technology, and presents 5G utilization of Pyeongchang Winter Olympic Games and Jeju Smart City model. The reason is that 5G is the main artery of the 4th industry.5G is the fourth industrial aorta because 5G is the core infrastructure of the fourth industrial revolution. In order for the AI, autonomous vehicle, VR / AR, and Internet (IoT) era to take off, data must be transmitted several times faster and more securely than before. For example, if you send a stop signal to LTE, which is a communication technology, to a remote autonomous vehicle, it takes a hundredth of a second. It seems to be fairly fast, but if you run at 100km / h, you can not guarantee safety because the car moves 30cm until it stops. 5G is more than 20 gigabits per second (Gbps), about 40 times faster than current LTE. Theoretically, the vehicle can be set up within 1 cm. 5G not only connects 1 million Internet (IoT) devices within a radius of 1 kilometer, but also has a speed delay of less than 0.001 sec. Steve Mollenkov, chief executive officer of Qualcomm, the world's largest maker of smartphones, said, "5G is a key element and innovative technology that will connect the future." With 5G commercialization, there will be an economic effect of 12 trillion dollars in 2035 and 22 million new jobs We can expect to see the effect of creation.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.469-476
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• 2020

This study is a qualitative study to grasp the meaning of the effective role of tutors of college students experiencing problem-based learning through focus group interviews. The subjects of this study were 4th grade students in the Department of Nursing who had experienced PBL, and a total of 21 people were divided into 3 groups and interviewed. Data were analyzed in content to find meaningful topics. The results of this study were analyzed into two subjects and eight categories. Based on the research results, if we summarize the role of effective tutors recognized by students in PBL. 1) Create a permissive atmosphere so that students can express their ideas freely and interact. 2) Give praise and encouragement. 3) Encourage all learners to participate. In particular, learners with low participation should be asked questions to promote active discussion. 4) Avoid unnecessary intervention and participate in the discussion together. 5) Adjust the learning speed and manage the time well. 6) Develop a scenario that meets the goals. 7) Classes are run around questions that can promote learners' thinking. 8) It plays a role of helping to form knowledge by providing positive feedback to learners' responses.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.397-406
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• 2000

대부분의 국방정보시스템의 소프트웨어는 높은 가용성, 신뢰성, 신속성, 정확성 등을 요구하는 대규모이면서 복잡한 실시간 시스템이다. 이러한 국방정보시스템의 소프트웨어 개발사업에 있어서 저비용 고효율의 미개국방경영 건설을 위하고 강한 전투력을 육성하기 위해서는 국방정보시스템의 효율적인 소프트웨어 개발사법이 요구된다. 따라서, 국방정보시스템의 소프트웨어 사업관리자가 개발사업을 관리하고 감독하는데 있어서 개발자와 사용자간의 조정 및 통제 기능을 수행하고 해당 국방정보시스템의 특성을 파악하여 성공적인 사업수행을 할 수 있도록 기술적인 사업관리 측면에서 구체적이고 상세화된 방안/지침을 제공하기 위한 전문가시스템의 지식베이스 도메인 지식개발에 관한 연구이다. 기존의 국방정보시스템의 사업관리자가 경험을 동해 축적해 온 기술, 정책, 아이디어, 노하우 등에 대한 지식을 습득하고 사업 관련자료에서 제시한 소프트웨어 생명주기 단계별 방안이나 지침 등을 바탕으로 하여 식별된 사실이나 내용을 지식베이스로 구축하여 국방정보시스템의 사업관리자가 필요로 할 때 설명모듈을 거쳐 임무 및 세부활동사항을 게시하여 줌으로써 사업관리 경험이 부족하거나 사업관리자가 교체되었을 때 사업관리자들이 업무를 지속적으로 연계시켜 임무수행이 가능하도록 기초/기반 여건을 제공하고자 한다. 본 논문은 국방정보시스템의 소프트웨어 개발사업에서 소프트웨어 생명주기 단계별 사업관리자의 임무 및 세부활동사항 지원용 전문가시스템을 개발할 때 이용할 수 있도록 도메인 지식을 개발하는 것이며 논문의 결과를 활용시 기대되는 효과는 본문을 참고 바란다.의 장점을 취합하여 설계되었다. 본 시스템은 기존의 UN/EDIFACT표준을 사용하고 있는 EDI환경과 기존 VAN 방식의 EDI 중계 시스템과 연동되며, 향후 관세청의 XML/EDI 표준 시행을 미리 대비하는 선도연구로서 자리매김이 된다. 본 연구에서는 개발된 XML/EDI 통관시스템은 향후, 서비스의 최대 걸림돌이 되어왔던 값비싼 EDI 사용료의 부담에서 벗어날 수 있게 할 것이며, 저렴한 EDI구축/운영 비용으로 전자문서교환의 활성화와 XML이 인터넷 기반의 문서유통 표준으로 자리매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1124-1131
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• 2006

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. Moreover, MIS, PACS(Picture Archiving and Communication System), OCS, EMR are also developing. Medical Information System is evolved toward integration of medical IT and situation is changing with increasing high speed in the ICT convergence. Mobile component 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. It is the core technology to implement automatic medical processing system. This paper provides a basic review of RFID model, PACS application component services. In addition, designed and implemented database server's component program and client program of mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented mobile PACS that performed patient data based db environments, and so reduced delay time of requisition, medical treatment, lab.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.247-256
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• 2000

오늘날의 기업은 상품을 판매하는 것 뿐만 아니라 기업의 신용과 이미지를 위해 그 상품에 대한 사후처리(After Service) 업무에 많은 투자를 하고 있다. 이러한 양질의 사후서비스를 고객에게 공급하기 위해서는 많은 인력을 합리적으로 관리해야 하고 요청되는 고장수리 서비스 업무를 빠르게 해결하기 위해서는 업무를 인력들에게 합리적으로 배정을 하고 회사의 비용을 최소화하면서 정해진 시간에 요청된 작업을 처리하기 위해서는 인력들에게 작업을 배정하고 스케줄링하는 문제가 발생된다. 본 논문에서는 이러한 문제를 해결하기 위해 화학계기의 A/S 작업을 인력에게 합리적으로 배정하는 스케줄링 시스템에 관한 연구이다. 먼저 스케줄링 모델을 HP 사의 화학분석 및 시스템을 판매, 유지보수 해 주는 "영진과학(주)"회사의 작업 스케줄을 분석하여 필요한 도메인과 고객서비스전략과 인력관리전략에서 제약조건을 추출하였고 여기에 스케줄링 문제를 해결하기 위한 방법으로 제약만족문제(CSP) 해결기법인 도메인 여과기법을 적용하였다. 도메인 여과기법은 제약조건에 의해 변수가 갖는 도메인의 불필요한 부분을 여과하는 것으로 제약조건과 관련되어 있는 변수의 도메인이 축소되는 것이다. 또한, 스케줄링을 하는데에 있어서 비용적인 측면에서의 스케줄링방법과 고객 만족도에서의 스케줄링 방법을 비교하여 가장 이상적인 해를 찾는데 트래이드오프(Trade-off)를 이용하여 최적의 해를 구했으며 실험을 통해 인력에게 더욱 효율적으로 작업들을 배정 할 수 있었고 또한, 정해진 시간에 많은 작업을 처리 할 수 있었으며 작업을 처리하는데 있어 소요되는 비용을 감소하는 결과를 얻을 수 있었다. 검증하였다.를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity

• Journal of Korean Society of Steel Construction
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• v.23 no.2
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• pp.199-210
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• 2011

The cables in cable-stayed bridges are under high stress and are very sensitive to vibration due to their small section areas compared with other members. Therefore, it is reasonable to evaluate the cable impact factor by taking into account the dynamic effect due to moving-vehicle motion. In this study, the cable impact factors were evaluated via moving-vehicle-load analysis, considering the design parameters, i.e., vehicle weight, cable model, road surface roughness, vehicle speed, longitudinal distance between vehicles. For this purpose, two steel composite cable-stayed bridges with 230- and 540-m main spans were selected. The results of the analysis were then compared with those of the influence line method that is currently being used in design practice. The road surface roughness was randomly generated based on ISO 8608, and the convergence of impact factors according to the number of generated road surfaces was evaluated to improve the reliability of the results. A9-d.o.f. tractor-trailer vehicle was used, and the vehicle motion was derived from Lagrange's equation. 3D finite element models for the selected cable-stayed bridges were constructed with truss elements having equivalent moduli for the cables, and with beam elements for the girders and the pylons. The direct integration method was used for the analysis of the bridge-vehicle interaction, and the analysis was conducted iteratively until the displacement error rate of the bridge was within the specified tolerance. It was acknowledged that the influence line method, which cannot consider the dynamic effect due to moving-vehicle motion, could underestimate the impact factors of the end-cables at the side spans, unlike moving-vehicle-load analysis.

• Applied Chemistry for Engineering
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• v.27 no.2
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• pp.221-226
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• 2016

Production of eco-friendly and biologically harmless materials is strongly required in all industries. In particular, reducing volatile organic compounds in coating processes is extremely important to secure worker's safety. During recent two decades, extensive research works on water-borne polyurethane dispersion (PUD) have been continuously developed as an alternative to solvent-borne polyurethane. However, PUD was shown inferior mechanical properties to the organic solvent-borne polyurethane due to a limit to the molecular weight increase, which resulted in the limit of applications. To overcome this drawback, several approaches have been examined such as polymer blends and thermal/radiation induced crosslinking. Among these methods, the radiation curing system was suitable for industrialization because of the high crosslinking density and fast curing speed. In this study, we overcame the drawback for PUD via introducing benzophenone radiation curable units to PUD. We synthesized PUD films which possessed good dispersion in water for 30 days, increased Tg and Td more than $5^{\circ}C$ after UV curing film as well as improved young's modulus more than double.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.373-379
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• 2019

Polymethyl methacrylate (PMMA), a self-polymerizing resin for removable orthodontic devices, has been used as a dental orthodontic device for many years because of its advantages such as color stability, volume stability, and tissue compatibility. However, such a removable orthodontic device has a disadvantage that the longer the use in the oral cavity due to the low strength of the PMMA fracture of the orthodontic device resin in use. In this study, zinc nanoparticles (ZNP) were mixed with orthodontic PMMA to introduce strength effect. Rectangular samples ($1.4{\times}3.0{\times}19.0mm$) of orthodontic PMMA (0, 0.5, 1.0, 2.0 and 4.0%) containing ZNP were prepared. The finished specimen was tested for three-point bending strength at a speed of 1 mm / min, and the Vickers hardness was measured three times using a hardness tester. The surface roughness was measured with a surface roughness. As a result, the 3-point bending strength did not change significantly (p>0.05). Surface energy increased significantly. As a result, we successfully synthesized ZNP in this study and prepared the dispersed resin specimen for calibration. It will be possible to develop high-density dental orthodontic resins.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1217-1227
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• 2018

This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.