• 보건행정학회지
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• 제4권2호
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• pp.111-125
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• 1994

In developing total hospital information system, large amount of time and expense are to be spent while its results are likely to lead itself to end-users' dissatisfaction. Some of the main complaints on the part of end-users come from insufficient consideration of end-users environment as well as inappropriate representation of their requirement in the system alalysis and design. This papre addresses some advantages of Essential Logical Modeling Process for better analysis and design, explaining by example the developmental process of the Patent Management and Accounting System for a tertiary care hospital. In the case, the Essential Model, suggested by McMenamin and Palmer, proved to be an effective tool for clear separation of analysis and design phase and for better communication among system developers and with end-users. The modeling process itself contributed to better program modularity as well, shown in a Structured Chart. Difficulties in learning how to identify' essential activities' for the modeling practice were experienced in the beginnins stage, which were, however, overcome by elaborating some heuristic guideling and by rdferring to necessary tools including State Transition Diagram, Control Flow Diagram, and so many. While full evaluation of the Essential Model usag remains to wait till the completion of the case project, its strengt in making clear distinction between analysis and design phase was enough to be attractive to system analysts. The model concepts are open to many further application fields, particularly such areas as business re engineering, process remodeling, office automation, and organizational restructuring.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권4호
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• pp.149-158
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• 2023

최근 데이터 활용이 중요해짐에 따라 데이터 센터의 중요도도 함께 높아지고 있다. 하지만 데이터 센터는 막대한 전력을 소모함과 동시에 24시간 가동되는 시설이기 때문에 환경적, 경제적 측면에서 문제가 되고 있다. 최근 딥러닝 기법들을 사용하여 트래픽을 예측하거나, 데이터 센터나 서버에서 사용되는 전력을 줄이는 연구들이 다양한 관점에서 이루어지고 있다. 그러나 서버에서 처리되는 트래픽 데이터양은 변칙적이며 이는 서버를 관리하기 어렵게 만든다. 또한, 서버 상황에 따라 서버를 가변적으로 관리하는 기법에 대한 연구들이 여전히 많이 요구되고 있다. 따라서 본 논문에서는 이러한 문제점을 해결하기 위해 시계열 데이터 예측에 강세를 보이는 장단기 기억 신경망 (Long-Term Short Memory, LSTM)을 기반으로 한 가변적인 서버 관리 기법을 제안한다. 제안된 모델을 통해 서버에서 사용되는 전력을 보다 효과적으로 줄일 수 있게 되며, 현업환경에서 이전보다 안정적이고 효율적으로 서버를 관리할 수 있게 된다. 제안된 모델의 검증을 위해 위키피디아 (Wikipedia)의 데이터 센터 중 6개의 데이터 센터의 전송 및 수신 트래픽 데이터를 수집한 뒤 통계기반 분석을 통해 각 트래픽 데이터의 관계를 분석 및 실험을 수행하였다. 실험 결과 본 논문에서 제안된 모델의 유의미한 성능을 통계적으로 검증하였으며 서버 관리를 안정적이고 효율적으로 수행할 수 있음을 보여주었다.

• 한국수자원학회논문집
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• 제54권spc1호
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• pp.1183-1193
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• 2021

Low flow는 하천수의 공급관리 및 계획, 관개용수 등 다양한 분야에 영향을 미친다. 이러한 유황곡선을 산정하기 위해서는 30년 이상의 충분한 기간의 유량자료의 확보가 필수적이다. 하지만 국가하천 단위 이하의 하천의 경우 장기간의 유량자료가 없거나 중간에 일정기간 동안 결측된 관측소가 있어 하천별 유황 곡선을 산정하기에 한계가 있다. 이에 과거에는 미계측 유역의 유황을 예측하기 위해 다중회귀분석(Multiple Regression Analysis), ARIMA 모형 등 통계학적 기반의 기법들을 사용하였지만, 최근에는 머신러닝, 딥러닝 모형의 수요가 증가하고 있다. 이에 본 연구에서는 최신 패러다임에 맞는 머신러닝 기법인 DNN기법을 제시한다. DNN기법은 ANN기법의 단점인 학습과정에서 최적 매개변수 값을 찾기 어렵고, 학습시간이 느린 단점을 보완한 방법이다. 따라서 본연구에서는 DNN 모형을 이용하여 미계측 유역에 적용 가능한 유황곡선을 산정하고자 한다. 먼저, 유황곡선에 영향을 미치는 인자들을 수집하고 인자들 간의 다중공선성 분석을 통해 통계적으로 유의한 변수를 선정하여, 머신러닝 모형에 입력자료를 구축하였다. 통계적 검증을 통해 머신러닝 기법의 효용성을 검토하였다.

• 국제학술발표논문집
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• The 10th International Conference on Construction Engineering and Project Management
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• pp.1282-1282
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• 2024

Given the widespread use of intelligent surveillance cameras at construction sites, recent studies have introduced vision-based deep learning approaches. These studies have focused on enhancing the performance of vision-based excavator activity recognition to automatically monitor productivity metrics such as activity time and work cycle. However, acquiring a large amount of training data, i.e., videos captured from actual construction sites, is necessary for developing a vision-based excavator activity recognition model. Yet, complexities of dynamic working environments and security concerns at construction sites pose limitations on obtaining such videos from various surveillance camera locations. Consequently, this leads to performance degradation in excavator activity recognition models, reducing the accuracy and efficiency of heavy equipment productivity analysis. To address these limitations, this study aimed to conduct sensitivity analysis of excavator activity recognition performance based on surveillance camera location, utilizing synthetic videos generated from a game-engine-based virtual environment (Unreal Engine). Various scenarios for surveillance camera placement were devised, considering horizontal distance (20m, 30m, and 50m), vertical height (3m, 6m, and 10m), and horizontal angle (0° for front view, 90° for side view, and 180° for backside view). Performance analysis employed a 3D ResNet-18 model with transfer learning, yielding approximately 90.6% accuracy. Main findings revealed that horizontal distance significantly impacted model performance. Overall accuracy decreased with increasing distance (76.8% for 20m, 60.6% for 30m, and 35.3% for 50m). Particularly, videos with a 20m horizontal distance (close distance) exhibited accuracy above 80% in most scenarios. Moreover, accuracy trends in scenarios varied with vertical height and horizontal angle. At 0° (front view), accuracy mostly decreased with increasing height, while accuracy increased at 90° (side view) with increasing height. In addition, limited feature extraction for excavator activity recognition was found at 180° (backside view) due to occlusion of the excavator's bucket and arm. Based on these results, future studies should focus on enhancing the performance of vision-based recognition models by determining optimal surveillance camera locations at construction sites, utilizing deep learning algorithms for video super resolution, and establishing large training datasets using synthetic videos generated from game-engine-based virtual environments.

• 한국재료학회지
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• 제31권12호
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• pp.719-726
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• 2021

Through the process of chemical vapor deposition, Tungsten Hexafluoride (WF₆) is widely used by the semiconductor industry to form tungsten films. Tungsten Hexafluoride (WF₆) is produced through manufacturing processes such as pulverization, wet smelting, calcination and reduction of tungsten ores. The manufacturing process of Tungsten Hexafluoride (WF₆) is required thorough quality control to improve productivity. In this paper, a real-time detection system for oxidation defects that occur in the manufacturing process of Tungsten Hexafluoride (WF₆) is proposed. The proposed system is implemented by applying YOLOv5 based on Convolutional Neural Network (CNN); it is expected to enable more stable management than existing management, which relies on skilled workers. The implementation method of the proposed system and the results of performance comparison are presented to prove the feasibility of the method for improving the efficiency of the WF₆ manufacturing process in this paper. The proposed system applying YOLOv5s, which is the most suitable material in the actual production environment, demonstrates high accuracy (mAP@0.5 99.4 %) and real-time detection speed (FPS 46).

• 한국ITS학회 논문지
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• 제23권4호
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• pp.110-126
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• 2024

자율주차의 요소 중 하나인 경로계획(Path-planning)을 제안한다. 실제 주차장을 참고하여 수직주차와 수평주차로 주차장의 차로 너비, 주차 공간의 너비, 길이 등 주차장 구조와 주차 환경을 다양하게 설정한다. 출발점와 도착지점 등 각도와 환경을 다양하게 설정하여 경로데이터를 수집하고 수집한 데이터를 Deep Learning model에 넣어 학습시켜 자동주차경로계획 모델을 제안한다. 분석결과, 기 알고리즘(Hybrid A-star, Reeds-Shepp Curve)과 딥러닝 모델 모두 장애물에 충돌하지 않고 비슷한 경로를 생성하지만, 거리와 소모시간이 각각 0.59%, 0.61% 감소하여 효율적인 경로가 생성되었다. 또한, Switching point도 1.3개에서 1.2개로 감소하여 직진과 후진을 최대한으로 줄여 운전자의 피로를 줄일 수 있을거라 생각된다. 마지막으로 경로생성시간은 42.76% 감소하여 효율적이고 신속한 경로생성이 가능하여 향후 자율주행 중 자율주차의 경로 계획생성에 활용될 수 있으며, 차량작도에 따라 이동하는 주차로봇의 경로생성에도 활용될 수 있을 것으로 보인다.

• 정보교육학회논문지
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• 제5권3호
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• pp.374-379
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• 2001

최근 들어 네트웍 관리 및 컴퓨터 교육의 효율을 높이기 위한 실시간 네트웍 감시 시스템에 대한 연구의 필요가 절실히 요구되고 있다. 이러한 추세에 따라 본 연구에서는 새로운 실시간 네트웍 감시 시스템을 연구 및 개발하였다. 먼저 본 시스템은 학내 망 같은 분야의 전산 수업 시 학생들의 컴퓨터를 관리, 감독할 수 있으며 학생들의 키보드나 마우스의 제어권을 획득하여 수업 시 학생들과 1 대 1 교육을 시킬 수 있다. 또한 수업 시 효율적인 전산실습 및 교육을 위해 그것의 성능을 저해하는 사용자의 유무를 체크하고 경고 메시지 및 허용되지 않은 프로그램의 실행 방지 등 사용자의 편리를 위해 제공 비치된 컴퓨터나 어떤 형태로든지 네트웍 망에 연결된 단말기의 사용범위를 실시간으로 감시, 제어 및 관리할 수 있는 기능을 제공한다. 또한 본 시스템으로 인해 네트웍 사용의 낭비를 막을 수 있고 더 나아가 컴퓨터 교육의 질을 높일 수 있으며 사용자에 더 효율적인 교육 환경을 제공할 수 있는 장점이 있다.

• 한국물환경학회지
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• 제39권1호
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• pp.46-60
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• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• 교육녹색환경연구
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• 제10권2호
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• pp.61-72
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• 2011

The purpose of this study is to carry out the research of the satisfaction level of consumers (students and teachers) and managerial characteristics for model classes of the subject classroom system and to draw the effective plan of the system. The conclusions are as follows First, the biggest advantage of the system is to fulfill the educational goal according to an individual level and ability of each student while the biggest disadvantage is the inconvenience of students to change their classrooms for each specific class. Second, it is necessary to rearrange the classrooms according to the applied subjects from the aspect of curriculum management since the time frame is not convenient for recess. English and mathematics are required preferentially as applied subjects, however Korean (as a national language) and science are needed to be taught with level-differentiated classes, too. The ideal size of classes is most likely 20-25 students according to the result of research. Lastly, the space of environment is another requirement to secure smooth flow of students' movements and extra space for technical devices used for information research. The above analysis indicates the necessity of supplementation in space planning for further implementation of subject classroom system in secondary school.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.