• Journal of the Korean Society of Environmental Restoration Technology
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• v.3 no.3
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• pp.81-99
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• 2000

The shelterbelts are very important to conserve and protect the sandy land, vegetation coverage, farmland, livestock and human life in the desertified land. The shelterbelts are constructed by the several row-plantings of high-adaptable species in the desertified land. The shelterbelts have various kind of type, and there are shelterbelts for conservation of farmland in dry the region, the protective shelterbelts (windbreaks for blowing-sand, artificial sanddune fixation by revegetation, and construction of farmland shelterbelts to protect farmland and pasture from wind erosion, etc.) in the semi-dry steppe, shelterbelts around the villages and oasis for sanddune fixation, shelterbelts for protection of railroads, and so on. The shelterbelts consist of main she1terbelts and minor shelterbelts. The main shelterbelts were constructed by being perpendicular to main wind direction, and the minor shelterbelts were constructed by being perpendicular to the main shelterbelts. Generally, the width of shelterbelts is 8~20m, and the number of row-planting is 4~10. The grid sizes of shelterbelts networks are $400{\times}400m$, $300{\times}500m$, $100{\times}200m$, and so on, and there are ventilation type and closing type in the type of shelterbelt. The width, number of row-planting, grid size and type of shelterbelt are selected by the local characteristics. The effects of shelterbelts are mainly the climate improvement and mitigation, such as prevention of occurrence of strong wind, cold wind and blowing-sand. And, the other effects of shelterbelts are effect of reforestation, increase of agricultural productions, establishment of greenbelts and green forests, construction of landscape-eco shelterbelts, improvement of life environment of local villages, supply of fuel wood and agricultural wood, land amelioration, effect of revegetation and restoration of desertified land, and so on. The kinds of the tree species mainly used for the construction of shelterbelts have differences between regions, but main species are Populus euphratica, Populus simonii, Populus bolleana, Populus tomentosa, Salix flavida, Salix mongolica, Tamarix chinensis, Hedysarum scoparium, and so on.

• Tuberculosis and Respiratory Diseases
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• v.49 no.3
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• pp.365-371
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• 2000

Nodular pulmonary amyloidosis is one of the rare manifestation of amyloid disease. It is known to be caused by amyloid L fibrils in the majority of cases. We experienced an unusual case of a forty-one year-old woman who was presented with multiple nodular lesion on the chest X-ray. CT-guided core needle biopsy, performed on the lesion, showed apple green birefringes, when stained Congo red and examined under polarized light, Ultrastructurally, there are randomly oriented, forming densed networks, and consists of fine, 7.5 to 10nm diameter, rigid, non-branching filaments of various lengths in electron-microscopic finding. We report a case of primary diffuse nodular pulmonary amyloidosis only localized in the lung, which was confirmed by CT guided core needle biopsy.

• Journal of the Korean Regional Science Association
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• v.32 no.3
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• pp.29-43
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• 2016

The purpose of this study is to derive research subject that has been overlooked in previous studies and contribute to seek to the direction of research in rural development by analyzing the studies in the last 30 years on rural society. In this study, Social Network Analysis was used for identifying the changes in research themes and connection structure of keyword. The study shows that in the previous Roh Moo-Hyun's Administration from 1986 to 2000, the convergence of the research is not active. In terms of the connection structure of keyword, lots of keywords are connected to the 'Migration, IMF, Satisfaction, Green Tourism' but its form is not complicated. In the Roh Moo-Hyun's Administration from 2001 to 2007, the academic exchanges and convergence of keywords on rural development were promoted research. The connection structure of keyword was formed like a complex cluster associated with 'The Rural Elderly, Rural Tourism, Rural Development Policy, Urban-Rural Comparison'. Although some scholars who study 'Women's Studies, Tourism' formed the cluster, its form is still passive. Since 2008 until now, the keyword network of rural development research clustered densely and formed singly. It reveals that the convergence of research subjects has proceeded actively. And studies such as the 'Community, Participation, Social capital, Quality of life, Social networks, Alternative food movement' have begun.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.79-85
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• 2016

Recently, visible light communication(VLC) is being actively researched as green wireless communication services are drawing attention. Currently, VLC mostly uses LED for transmission and PD(Photo Diode) for receiving. However, this kind of system has limited applications. Therefore, we design and propose in this paper, a LED-to-LED two way VLC system that doesn't use PD(Photo Diode). This system has the following features and contributions. First, this system uses just LED at both transmitter and receiver with analog switch, Second, this system support both one-way communication and two way communication together. One way communication can support multi-hop communication. The performance evaluation of the proposed system is conducted at a place with standard light. We test the success or failure of one way communication by changing distance and baud rate while test the success and failure of two way communication by changing distance. We expect that the proposed LED-to-LED system in this paper can be applied for various application fields.

• Spatial Information Research
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• v.20 no.5
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• pp.77-89
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• 2012

Walking is the most basic personal mobility and its importance and concern is ever increasing with the highlighting of a new paradigm, such as transit oriented development, sustainable development and revitalization of green transport. The existing analytical research on pedestrian network is using a pedestrian's moving distance to a destination and integration in space syntax theory as its representative accessibility factors. However, the uniplanar network moving distance fails to reflect topographic characteristics, so the moving distance could show a similar result value in case of the regions for analysis that have a similar network structure to each other. Accordingly, the aim of this study is to suggest a new analytical methodology on pedestrian network accessibility in consideration of the grade in pedestrian sections and a pedestrian's size. this study, in its analysis of a uniplanar pedestrian network moving distance, analyzed the pedestrian network moving distance in consideration of the grade in pedestrian sections, and even the pedestrian network moving distance in consideration of a pedestrian's size, and suggested the methodology on pedestrian network accessibility analysis in consideration of a more substantive pedestrian's characteristics. It is hoped that the methodology used by this study will be used as the methodology on pedestrian network analysis which can reflect topographic characteristics in the pedestrian network analysis, and take a more substantive pedestrian's movement into account.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.315-324
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• 2022

The experimental data obtained in a wave flume were analyzed using machine learning techniques to establish a model that predicts the input wave height of the wavemaker based on the waves that have experienced wave shoaling and to verify the performance of the established model. For this purpose, artificial neural network (NN), the most representative machine learning technique, and Gaussian process regression (GPR), one of the non-parametric regression analysis methods, were applied respectively. Then, the predictive performance of the two models was compared. The analysis was performed independently for the case of using all the data at once and for the case by classifying the data with a criterion related to the occurrence of wave breaking. When the data were not classified, the error between the input wave height at the wavemaker and the measured value was relatively large for both the NN and GPR models. On the other hand, if the data were divided into non-breaking and breaking conditions, the accuracy of predicting the input wave height was greatly improved. Among the two models, the overall performance of the GPR model was better than that of the NN model.

• Smart Media Journal
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• v.11 no.1
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• pp.67-80
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• 2022

Smart City Technology, which is significant in the era of the 4th industrial revolution, greatly increases the efficiency and productivity of cities nowadays. The purpose of this study is to present a strategic approach for industrial revitalization and overseas export by analyzing the current status of smart city-related companies and discovering high-priority smart city technologies. To this end, the smart city theory and ASEAN smart city were reviewed through prior research, and a survey of companies with domestic smart city technology was conducted. As a result of the survey, it is revealed that companies with smart city technology in Korea are highly willing to export to ASEAN countries. There is a strong desire to export the following technologies: construction, traffic, green·energy, etc. And there was a high willingness to export the following services: IoT, platform, AI, etc. The following solutions have been proposed as solutions to Strategic Plans to Promote the Export: 1) Deregulation and incentives, 2) Global human resource development, 3) Information provision and strengthening of local networks, 4) Financial and public relations support.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.444-444
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• 2021

하천의 오염부하량 관리 계획은 지속적인 모니터링을 통한 자료 구축과 모형을 이용한 예측결과를 기반으로 수립된다. 하천의 모니터링과 예측 분석은 많은 예산과 인력 등이 필요하나, 정부의 담당 공무원 수는 극히 부족한 상황이 일반적이다. 이에 정부는 전문가에게 관련 용역을 의뢰하지만, 한국과 같이 지형이 복잡한 지역에서의 오염부하량 배출 특성은 각각 다르게 나타나기 때문에 많은 예산 소모가 발생 된다. 이를 개선하고자, 본 연구는 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 BOD 및 총인의 부하량 예측 모형을 개발하였다. 합성곱 신경망의 입력자료는 일반적으로 RGB (red, green, bule) 사진을 이용하는데, 이를 그래도 오염부하량 예측에 활용하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이에, 본 연구에서는 오염부하량이 수문학적 조건과 토지이용 등의 변수에 의해 결정된다는 인과관계를 만족시키고자 수문학적 속성이 내재된 수문학적 이미지를 합성곱 신경망의 훈련자료로 사용하였다. 수문학적 이미지는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는데, 여기서 각 grid의 수문학적 속성은 SCS 토양보존국(soil conservation service, SCS)에서 발표한 수문학적 토양피복형수 (curve number, CN)를 이용하여 산출한다. 합성곱 신경망의 구조는 2개의 Convolution Layer와 1개의 Pulling Layer가 5회 반복하는 구조로 설정하고, 1개의 Flatten Layer, 3개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 마지막으로 1개의 Dense Layer가 연결되는 구조로 설계하였다. 이와 함께, 각 층의 활성화 함수는 정규화 선형함수 (ReLu)로, 마지막 Dense Layer의 활성화 함수는 연속변수가 도출될 수 있도록 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 연구의 대상지역은 경기도 가평군 조종천 유역으로 선정하였고, 연구기간은 2010년 1월 1일부터 2019년 12월 31일까지로, 2010년부터 2016년까지의 자료는 모형의 학습에, 2017년부터 2019년까지의 자료는 모형의 성능평가에 활용하였다. 모형의 예측 성능은 모형효율계수 (NSE), 평균제곱근오차(RMSE) 및 평균절대백분율오차(MAPE)를 이용하여 평가하였다. 그 결과, BOD 부하량에 대한 NSE는 0.9, RMSE는 1031.1 kg/day, MAPE는 11.5%로 나타났으며, 총인 부하량에 대한 NSE는 0.9, RMSE는 53.6 kg/day, MAPE는 17.9%로 나타나 본 연구의 모형은 우수(good)한 것으로 판단하였다. 이에, 본 연구의 모형은 일반 ANN 모형을 이용한 선행연구와는 달리 2차원 공간정보를 반영하여 오염부하량 모의가 가능했으며, 제한적인 입력자료를 이용하여 간편한 모델링이 가능하다는 장점을 나타냈다. 이를 통해 정부의 물관리 정책을 위한 의사결정 및 부족한 물관리 분야의 행정력에 도움이 될 것으로 생각된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.17-27
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• 2023

Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.