• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.375-375
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• 2011

유역에서 강우에 따라 유출이 발생하면 지표면을 따라 하천으로 유입되거나, 땅속으로 침투하여 깊은 대수층으로 유입되던지 기저유출 형태로 하천으로 유입된다. 이렇듯 하천을 구성하는 중요 두 가지 요소인 직접유출량과 기저유출량을 정확히 산정하는 것이 유역 수자원관리 및 비점오염원 관리에 매우 중요한 부분이라 할 수 있다. 그동안 하천에서 측정된 유출량에서 직접유출과 기저유출을 분리하기 위한 많은 연구가 진행되어 왔으며, 최근에는 주관적인 면을 배제하고 장기실측 유량자료를 이용하여 기저유출을 분리할 수 있는 BFlow, HYSEP, PART, RORA, RECESS, 디지털 필터링 모형 등 많은 프로그램들이 개발되어 활용되어 오고 있다. 또한 최근에는 인터넷을 통해 활용할 수 있는 Web 기반 WHAT 프로그램이 개발되어 전 세계적으로 널리 활용되고 있다. 이에 본 연구에서는 XML 프로그래밍 기법을 이용하여 WHAT 프로그램을 확장한 Expaned XML-based WHAT (EX-WHAT) 시스템 (http://www.EnvSys.co.kr/~exwhat)을 개발 하였다. 기존의 시스템에서는 USGS 일유량자료를 URL을 통해 WHAT 서버에 저장한 후 이를 가공하여 수문 분석을 수행하였으나, 이번 연구를 통해서 개발된 시스템은 XML/Parser를 이용하여 USGS 서버에 저장되어 있는 일유량자료를 바로 읽어서 수문분석을 수행할 수 있게 되었다. 이 EXWHAT 시스템에는 BFlow, HYSEP, PART, Digital Filters 와 같은 엔진이 사용되고 있다. 본 연구에서 개발된 EX-WHAT 분석결과는 XML 형식으로 제공되고 있기 때문에, 다른 Web/Desktop 기반의 관련 프로그램에서 바로 활용될 수 있을 것이라 판단된다. 특히 EX-WHAT 분석결과는 유역관리, 기저유출을 통한 비점오염원 관리 평가, 지속가능한 지하수 고나리 등 다양한 수문/비점오염 연구/실무에 활용될 수 있을 것이라 판단된다.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.527-535
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• 2021

In this study, electroconductive textiles were developed by screen-printing technology using a complex solution of PEDOT:PSS/AgNW on a polylactic acid nanofiber web. A performance evaluation was then conducted to utilize this electroconductive textile as a signal transmission line. To obtain highly conductive electroconductive textiles, this study sought to determine the optimal mixing ratio of PEDOT:PSS/AgNW. Sheet resistance was measured to evaluate the electrical properties of electroconductive textiles, Finite element-scanning electron microscopy images were then used to examine surface properties, and Fourier transform-infrared analysis was performed to evaluate chemical properties. The signal waveform characteristics of the electroconductive textile were observed using a signal generator and an oscilloscope. Radio-frequency characteristics were then evaluated to confirm frequency range, and bending tests were conducted to evaluate durability. The signal transmission lines produced in this study had a sheet resistance value of 3.30 ?/sq, and signal transmission performance was evaluated to observe that the input value of the voltage was nearly identical to the output value. In addition, S21 analysis confirmed that it was available in the frequency domain up to 35 MHz. The performances of the transmission lines were maintained after 100, 200, 500, and 1,000 repeated bending tests, and sufficient durability was confirmed.

• Journal of Industrial Convergence
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• v.20 no.7
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• pp.37-50
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• 2022

This study intends to analyze the learning effect of asynchronous online classes used in education fields around the world after the COVID-19 pandemic. To this end, we compared and analyzed the lecture evaluation and final exam questions of the HTML5 web programming course, which was conducted offline in 2019 and asynchronously online in 2020 due to COVID-19. As a result of the analysis, no significant difference was drawn between the two teaching methods in the lecture evaluation score and final exam score. However, contrary to concerns about the application of online classes to the entire curriculum, the lecture evaluation and final exam scores of the video-based online classes were high, suggesting the possibility that online classes could be more effective than offline classes if well organized and managed in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.389-396
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• 2024

Generative AI has recently been utilized across all fields, achieving expert-level advancements in deep data analysis. However, identifying regional names in scientific literature remains a challenge due to insufficient training data and limited AI application. This study developed a standardized dataset for effectively classifying regional names using address data from Korean institution-affiliated authors listed in the Web of Science. It tested and evaluated the applicability of machine learning and deep learning models in real-world problems. The BERT model showed superior performance, with a precision of 98.41%, recall of 98.2%, and F1 score of 98.31% for metropolitan areas, and a precision of 91.79%, recall of 88.32%, and F1 score of 89.54% for city classifications. These findings offer a valuable data foundation for future research on regional R&D status, researcher mobility, collaboration status, and so on.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.36-43
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• 2005

This paper suggests a method to effectively apply an application model of fuzzy-neural network to the optimal load distribution algorithm, considering the complication and non-linearity of the web server environment. We use the clustering web server in the linux system and it consists of a load balancer that distributes the network loads and some of real servers that processes the load and responses to the client. The previous works considered only with the scrappy decision information such as the connections. That is, since the distribution algorithm depends on the input of the whole network throughput, it was proved inefficient in terms of performance improvement of the web server. With the proposed algorithm, it monitors the whole states of both network input and output. Then, it infers CPU and memory states of each real server and effectively distributes the requests of the clients. In this paper, the proposed model is compared with the previous method through simulations and we analysis the results to develop the optimal and intelligent load balancing model.

• Journal of Information Processing Systems
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• v.2 no.3 s.4
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• pp.178-182
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• 2006

Children exhibit different behaviors, skills, and motivations. The main aim of this research was to investigate children's sensibility factors for icons, and to look for the best typeface for application to Web-Based Instruction (WBI) for e-Learning. Three types of icons were used to assess children's sensibilities toward metaphors: text-image, representational, and spatial mapping. Through the factor analysis, we found that children exhibited more diverse reactions to the text-image and representational types of icons than to the spatial mapping type of icons. Children commonly showedn higher sensibilities to the aesthetic-factor than to the familiarity-factor or the brevity-factor. In addition, we propose a collaborative-typeface system, which recommends the best typeface for children regarding the readability and aesthetic factor in WBI. Based on these results, we venture some suggestions on icon design and typeface selection for e-Learning.

• Journal of Engineering Education Research
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• v.15 no.5
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• pp.140-150
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• 2012

The purpose of this study was to compare and analysis researches related the promising career and job outlook and to provide the direction for job choice to engineering students. Literature review and expert council were used to achieve the objectives of study. The result of this study was analyzed that these jobs were promising, that is, environmental scientist and specialist, earth scientist and hydrologist(education and research related career), architecture and architectural engineer, civil engineer, landscape technician, land surveyor map production expert photo surveyor surveying technician(construction related career), material engineer (mechanics and material related career), mine and geology engineer(chemistry, fiber and environment related career), computer system design and analyst, system software engineer, application software engineer, web specialist, and computer support specialist (electrical and telecommunication related career) and food engineer(food related career). In addition, health silver specialist, bio biomedical engineer, renewable energy specialist etc. were promising by considering social and economic trend for demographic change like aging and green growth.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.1-6
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• 2017

This paper presents an optimized adoption of NVM for the storage system of heterogeneous applications. Our analysis shows that a bulk of I/O does not happen on a single storage partition, but it is varied significantly for different application categories. In particular, journaling I/O accounts for a dominant portion of total I/O in DB applications like OLTP, whereas swap I/O accounts for a large portion of I/O in graph visualization applications, and file I/O accounts for a large portion in web browsers and multimedia players. Based on these observations, we argue that maximizing the performance gain with NVM is not obtained by fixing it as a specific storage partition but varied widely for different applications. Specifically, for graph visualization, DB, and multimedia player applications, using NVM as a swap, a journal, and a file system partitions, respectively, performs well. Our optimized adoption of NVM improves the storage performance by 10-61%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.239-243
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• 2003

Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.