• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.669-676
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• 2017

Recently, due to the importance of information security, security vulnerability analysis and various information protection technologies and security systems are being introduced as a countermeasure against cyber-attacks in new as well as existing buildings, and information security studies on high-rise buildings are also being conducted. However, security system introduction and research are generally performed from the viewpoint of general IT systems and security policies, so there is little consideration of the infrastructure of the building. In particular, the BAS or building infrastructure, is a closed system, unlike typical IT systems, but has unique structural features that accommodate open functions. Insufficient understanding of these system structures and functions when establishing a building security policy makes the information security policies for the BAS vulnerable and increases the likelihood that all of the components of the building will be exposed to malicious cyber-attacks via the BAS. In this paper, we propose an architecture reference model that integrates three different levels of BAS structure (from?) different vendors. The architectures derived from this study and the security characteristics and vulnerabilities at each level will contribute to the establishment of security policies that reflect the characteristics of the BAS and the improvement of the safety management of buildings.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.193-193
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• 2011

국제기구인 정부간 기후변화협의체(Intergovernmental Panel on Climate Change, 이하 IPCC)에서는 기후변화가 기온 상승에 따른 증발산량의 증가, 강수량 및 유출량의 시공간적 분포의 변동 등을 초래하여 수자원의 효율적 관리 및 안정적인 공급에 어려움을 증대시킬 것으로 전망하였다. 또한 IPCC 4차 보고서에 따르면 21세기말 지구의 평균기온은 현재보다 최대 $6.3^{\circ}C$정도 더 상승할 것으로 전망하였다. 전구평균기온이 $3.0^{\circ}C$ 증가할 경우 아시아에서만 연간 700만 명이상이 홍수피해 위기에 직면할 것으로 예상되고 있다. 국내의 경우 기온은 전구평균기온에 비해 2배 이상 높은 $1.5^{\circ}C$ 정도 상승하였으며, 최근 50년간의 강우일수는 감소한 반면 일강수량이 80mm 이상인 호우일수의 발생빈도는 증가되고 있다고 보고되었다. 또한 최근의 물수지 해석과 관련하여 거시적인 관점에서 기온 및 강수량 증가에 따른 물순환 과정을 모의하고, 농업용수, 댐건설, 도시화, 토지이용의 변화 등 인위적인 환경 변화 및 기후변화에 따른 유출량의 변화를 정량화하려는 연구들이 수행되고 있다(한국건설기술원, 2007). 이를 위하여 단기적이 아니라 장기적인 측면에서 유출분석을 할 필요가 있으나, 현재까지 보유하고 있는 실측 자료의 한계 및 이러한 조사를 위해 요구되는 시간 및 비용의 한계 때문에, 유출해석 모형을 주로 이용하고 있다. 본 연구에서는 장래 건설예정인 미계측 호소의 유량과 수질을 모의하기 위하여 하천, 하구, 호소 및 해역에 고루 적용할 수 있는 3차원 수리 동력학적인 모델인 EFDC 모형과 시간의 변화에 따른 수질을 모의하는데 가장 널리 이용하는 WASP 모형을 도입하였다. 향후, 내성천의 영주댐 건설과 같은 큰 변화가 발생하였을 기후 변화의 영향을 파악하기 위하여 EFDC와 WASP모형을 이용하여 대상유역에 대한 유출량과 수온의 변화를 통하여 A2, B1 기후변화 시나리오별로 2020년, 2050년, 2080년의 수질(BOD, TN, TP)변화를 분석하여 보았다. 연구의 결과는 다음과 같이 나타났다. EFDC 및 WASP 모형의 연계를 통한 기후 변화 시나리오에 따른 미래의 저수지 수질예측 모의를 수행한 결과, BOD, TN, TP 등 수질농도 변화는 2020년에서 2080년도로 갈수록 BOD, TN 다소 증가하는 경향을 나타내었고, TP농도는 감소하였다. 시나리오별 변화 특성은 TN, TP 농도는 A2 시나리오가 다소 높고, BOD 농도는 B1 시나리오가 A2보다 높은 것으로 나타났다. EFDC와 WASP을 이용하여 미계측 호소에 대한 기후변화 시나리오별로 적용하여 수질변화를 예측하여 보았는데, 향후 기후변화에 따른 기온, 유량변화와 수질 항목간의 상간관계 정립 및 수질 모의의 불확실성 등에 대한 추가 연구가 필요할 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.212-220
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• 2021

National R&D investment has steadily increased, reaching number 5 in the world as of 2018. However, for public technology commercialization, the level of discovery of policy models through various cooperation initiatives between government ministries is insufficient, and the performance system that can spread technology commercialization is also limited. In this respect, in order to create results in public technology commercialization, it is necessary to prepare alternatives to strengthen multi-ministerial policy cooperation and increase policy execution power. In this paper, we analyzed the current state of national R&D projects by major ministries and suggested an optimized technology commercialization plan through analysis of the structure, budget, and form of each project. In particular, an alternative in terms of policy efficiency was suggested by analyzing the problems of policy discovery that have not been studied previously. This study is of great significance in that it diagnosed problems of public technology commercialization in terms of the lack of systematic research on public technology commercialization and suggested policy advancement for the spread of technology use and the strategic direction in terms of commercialization.

• Journal of Technology Innovation
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• v.29 no.1
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• pp.1-38
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• 2021

In this paper, an exploratory analysis study was conducted on establishing a strategy to utilize living labs to enhance the innovation of the energy sector. Through the previous research literature, it was possible to confirm the concept, essential components, innovation characteristics of living labs, and types of innovation issues in the energy sector as the theoretical background. Based on this, the case studies of energy living lab (8 overseas, 1 domestic) were analyzed focusing on the possibility of utilizing living lab as an approach to innovation issues in the energy sector, establishing a customized strategy for essential components of living lab and enhancing innovation. It was confirmed that the establishment of a customized strategy for the essential components of the living lab could be a driving force in enhancing innovation, and the Living Lab is effectively used as an approach method for innovation issues(demand management, supply technology, enhance R&D acceptance and promote commercialization, technology policies) in the energy sector. As a result of the case studies, the driving force of each living lab was derived from the viewpoint of contributing to innovation, and strategies for using the living labs for each energy innovation problem were established. This study is an exploratory and descriptive analytical study of the utilization strategy and value of the living lab model as an approach to innovation issues in the energy field, which can provide a living lab strategy framework that has not been tried in the past and enables living lab activation and network formation. It can also be considered to have academic, practical, and policy implications in that it can also contribute.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.533-540
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• 2010

Dam is very important facility in water supply and flood control. Therefore study needs to analyze reservoir capacity accurately to manage Dam efficiently. This study compared time series reservoir capacity using multi-dimensional spatial information to Chungju Dam reservoir and major conclusions are as follows. First, LiDAR and multi beam echo sounder survey were carried out in land zone and water zone of Dam reservoir area. And calibration process was performed to enhance the accuracy of survey data and it could be constructed that multi dimensional spatial information which was clearly satisfied with the standard of tolerance error by validation with ground control points. Reservoir capacity by water level was calculated using triangle irregular network from detailed topographic data that was constructed by linked with airborne LiDAR and multi beam echo sounder data, and curve equation of reservoir capacity was developed through regression analysis in 2008. In the comparison of the reservoir capacity of 2008 with those of 1986 and 1996, the higher water level goes, total reservoir capacity of 2008 showed decrease because of the increase of sediment in reservoir. Also, erosion and sediment area could be analyzed through calculating the reservoir capacity by the range of water level. Especially the range of water level as 130.0~135.0 which is the upper part of average water level, showed the highest erosion characteristics during 1986~2008 and 1996~2008 and it is considered that the erosion of reservoir slant by heavy rainfall is major reason.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.870-876
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• 2005

The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.127-135
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• 2012

This paper introduced the flow forecast modeling system that a water management agency in west central Florida, Tampa Bay Water has been operated to forecast monthly rainfall and streamflow in the Tampa Bay region, Florida. We evaluated current 1-year monthly rainfall forecasts and flow forecasts and actual observations to investigate the benefits of incorporating rainfall forecasts into monthly flow forecast. Results for rainfall forecasts showed that the observed annual cycle of monthly rainfall was accurately reproduced by the $50^{th}$ percentile of forecasts. While observed monthly rainfall was within the $25^{th}$ and $75^{th}$ percentile of forecasts for most months, several outliers were found during the dry months especially in the dry year of 2007. The flow forecast results for the three streamflow stations (HRD, MB, and BS) indicated that while the 90 % confidence interval mostly covers the observed monthly streamflow, the $50^{th}$ percentile forecast generally overestimated observed streamflow. Especially for HRD station, observed streamflow was reproduced within $5^{th}$ and $25^{th}$ percentile of forecasts while monthly rainfall observations closely followed the $50^{th}$ percentile of rainfall forecasts. This was due to the historical variability at the station was significantly high and it resulted in a wide range of forecasts. Additionally, it was found that the forecasts for each station tend to converge after several months as the influence of the initial condition diminished. The forecast period to converge to simulation bounds was estimated by comparing the forecast results for 2006 and 2007. We found that initial conditions have influence on forecasts during the first 4-6 months, indicating that FMS forecasts should be updated at least every 4-6 months. That is, knowledge of initial condition (i.e., monthly flow observation in the last-recent month) provided no foreknowledge of the flows after 4-6 months of simulation. Based on the experimental flow forecasts using the observed rainfall data, we found that the 90 % confidence interval band for flow predictions was significantly reduced for all stations. This result evidently shows that accurate short-term rainfall forecasts could reduce the range of streamflow forecasts and improve forecast skill compared to employing the stochastic rainfall forecasts. We expect that the framework employed in this study using available observations could be used to investigate the applicability of existing hydrological and water management modeling system for use of stateof-the-art climate forecasts.

• Korean Journal of Environment and Ecology
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• v.36 no.1
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• pp.102-111
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• 2022

Among protected areas, National Parks are rich in biodiversity, and the benefits of ecosystem services provided to human are higher than the others. Ecosystem service evaluation is being used to manage the value of national parks based on objective and scientific data. Ecosystem services are classified into four services: supporting, provisioning, regulating and cultural. The purpose of this study is to evaluate habitat quality among supporting services. Habitat Quality Model of InVEST was used to analyze. The coefficients of sensitivity and habitat initial value were reset by reflecting prior studies and the actual conditions of protected areas. Habitat quality of 21 national parks except Hallasan National Park was analyzed and mapped. The value of habitat quality was evaluated to be between 0 and 1, and the closer it is to 1, the more natural it is. As a result of habitat quality analysis, Seoraksan and Taebaeksan National Parks (0.90), Jirisan and Odaesan National Parks (0.89), and Sobaeksan National Park (0.88) were found to be the highest in the order. As a result of comparing the area and habitat quality of 18 national parks except for coastal-marine national parks, the larger the area, the higher the overall habitat quality. Comparing the value of habitat quality of each zone, the value of habitat quality was high in the order of the park nature preservation zone, the park nature environmental zone, the park cultural heritage zone, and the park village zone. Considering both the analysis of habitat quality and the legal regulations for each zone of use, it is judged that the more artificial acts are restricted, the higher the habitat quality. This study is meaningful in analyzing habitat quality of 21 National Parks by readjusting the parameters according to the situation of protected areas in Korea. It is expected to be easy to intuitively understand through accurate data and mapping, and will be useful in making policy decisions regarding the development and preservation of protected areas in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.