• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.120-130
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• 2023

This study aims to develop a Park Performance Assessment Tool (PPAT) to qualitatively evaluate the level of urban neighborhood park services. The Park Performance Assessment Tool (PPAT) development process is as follows. First, a pool of evaluation items was formed by analyzing domestic and foreign cases related to the Park Performance Evaluation Tool (PPAT). Second, evaluation items were refined considering domestic park conditions through expert advisory meetings and pilot evaluations. Third, the reliability of the Park Performance Evaluation Tool (PPAT) was verified through pilot evaluations. Fourth, weights for each evaluation item were derived through an expert survey and AHP analysis. Fifth, a Park Performance Evaluation Tool (PPAT) evaluation table and evaluation guidelines were prepared. The developed Park Performance Assessment Tool (PPAT) was applied to 22 neighborhood parks in Bupyeong-gu, Incheon to evaluate the quality of the physical environment. As a result of the evaluation, several urban neighborhood parks that need improved park services were identified. The Park Performance Evaluation Tool (PPAT) is expected to be used to establish a basic plan for parks and green spaces, select priority and project promotion methods for park maintenance projects, and certify excellent parks

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• 월간 기계설비
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• s.298
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• pp.56-65
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• 2015

1970년대 고급 아파트촌의 대명사로 불리웠던 동부이촌동이 강북지역 한강변 초고층 주거시설의 랜드마크로 또한번 새롭게 변신한다. 지상 56층, 42층, 36층 총 3개동으로 구성된 초고층 주거시설이 오는 8월 1일부터 입주할 예정이기 때문이다. 이 아파트는 당분간 건립되기 힘든, 강북에서 가장 높은 초고층 주거시설로 지난 2013년 4월 서울시가 한강변 건축물 높이를 35층으로 제한하기 전인 2009년 사업시행 인가를 받았다. 한강이 내려다 보이고 인근에 국립중앙박물관, 용산가족공원, 한강공원 등 대형 공원이 있는데다 강남권, 강북권, 강서권으로의 접근성이 뛰어나 한강변의 새로운 랜드마크로 주목받고 있는 만큼 특화된 커뮤니티 시설과 함께 친환경 건축물 최우수 등급, 에너지효율 1등급, 초고속 정보통신 특등급 인증 획득을 목표로 최고의 주거성능등급 아파트 시공에 만전을 기하고 있다. 본지는 준공준비에 여념이 없는 이촌동 렉스아파트 재건축 현장에서 삼성물산 권진학 현장소장과 (주)우진아이엔에스(대표 홍평우 손광근) 김동원 현장소장을 만났다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.711-715
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• 2005

본 논문에서는 유비쿼터스 센서 네트워크의 핵심인 RFID에 대한 응용기술을 개발하기 위하여 대상을 놀이공원으로 잡고, 공원에 출입하는 입장객들이 각 놀이 기구에 입장한 시간과 나가는 시간을 자동으로 입력받아서 데이터베이스에 저장한 후에 전체적인 놀이공원 인원 배치에 관한 합리적인 지시, 명령을 도출하도록 하는 프로그램을 개발하는 시스템을 개발하였다. 이를 위하여 본 논문에서는 13.25Mhz 대의 RFID 센서와 마이크로소프트사의 MSSQL 데이터베이스와 IIS 웹서버를 기반으로 하는 시스템 구축을 수행하였다. 이를 위하여 SkyeTek사의 RFID 리더를 기반으로 시스템을 구축하여 호스트 PC와 연동 프로그램을 C++ 언어를 이용하여 개발하였고, ASP.NET과 C#을 이용한 웹사이트 구축하였으며, RFID 리더의 태그 인식 범위를 확장하기위한 외장형 안테나 제작한 결과 30${\sim}$40 cm 수준의 인식 거리를 보장하는 동판형 안테나를 개발하였으며, 시스템에 적용한 결과 성능의 우수함을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.871-876
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• 2005

Theme park automation system is developed by using the RFID sensor reader, IIS web server, ASP.NET and MSSQL database in this paper. Its operation is that park entrance people checked automatically when he who possessed the ta8 passed the reader acquisition bound and its tag information is sent to the host computer through the RS-232 data acquisition system. Tag information and time data will be stored in the RFID database tables and reused to extract and distribute the entrance people for the purpose of each arrangement of each entertainment devices. First of all, we developed interface program between host and reader and then, programmed the related web site and database connection function using ASP.NET with $C\#$ and MSSQ. We also design and make an production of external Ant. to extend the acquisition range up to $30\~40$ cm using copper PCB plate. We confirmed the performance through the RFID test bed site.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.129-132
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• 2002

대체 에너지(태양광, 풍력등)의 전력저장 시스템으로 널리 사용되는 겔형(Gel Type) 밀폐형 연(鉛)축전지의 노화 특성 평가 및 충전회로에 관하여 연구하였다. 납 합금을 이용한 기판 주조 기술과 전해액(Gel) 배합기술이 축전기 성능과 수명을 좌우하며 또한 배터리 충전 시스템에 따른 온도 상승이 치명적인 영향을 미치게 된다. 따라서 본 연구에서는 적외선 열화상 장치를 이용한 내부 열원 추적에 의해 노화정도를 측정하며 축전지 수명시험을 통해 입수한 데이터와 비교 평가하고자 한다. 현재 실험실 충방전 수명시험을 마치고 (주)코윈텍이 부안 해창 공원에 설치한 30kW급 풍력발전 시스템에 적용하여 Field Test를 시험중이다.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.1-12
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• 2012

There are many trees in a roadside, parks or facilities for landscape. Although we are easily seeing a tree in around, it would be difficult to classify it and to get some information about it, such as its name, species and surroundings of the tree. To find them, you have to find the illustrated books for plants or search for them on internet. The important components of a tree are leaf, flower, bark, and so on. Generally we can classify the tree by its leaves. A leaf has the inherited features of the shape, vein, and so on. The shape is important role to decide what the tree is. And texture included in vein is also efficient feature to classify them. This paper evaluates the performance of a leaf classification system using both shape and texture features. We use Fourier descriptors for shape features, and both gray-level co-occurrence matrices and wavelets for texture features, and used combinations of such features for evaluation of images from the Flavia dataset. We compared the recognition rates and the precision-recall performances of these features. Various experiments showed that a combination of shape and texture gave better results for performance. The best came from the case of a combination of features of shape and texture with a flipped contour for a Fourier descriptor.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.55-61
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• 2011

The small-sized wind turbine generating system with the output power less than 10kW, which can be installed in some areas of hills, parks, and cities due to its flexibility, is one of the progressive research and development fields in renewable energy. It is important for the small wind turbine generators to have low cost, high reliability as well as high efficiency. To meet these requirements, development of various maximum-power-point-tracking (MPPT) control schemes should be required. Generally, the output of the controller can be connected to a 48V battery to supply power to a DC load. In this work, the design and implementation of an FPGA-based MPPT controller for small-sized wind turbine generating system is presented. For the verification of the practical performance of various MPPT algorithms, CRIO controller from NI has been used.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.89-102
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• 2024

Land Surface Phenology (LSP) plays a crucial role in understanding vegetation dynamics. The near-infrared reflectance of vegetation (NIRv) has been increasingly adopted in LSP studies, being recognized as a robust proxy for gross primary production (GPP). However, NIR v is sensitive to the terrain effects in mountainous areas due to artifacts in NIR reflectance cannot be canceled out. Because of this, estimating phenological metrics in mountainous regions have a substantial uncertainty, especially in the end of season (EOS). The topographically corrected NIRv (TCNIRv) employs the path length correction (PLC) method, which was deduced from the simplification of the radiative transfer equation, to alleviate limitations related to the terrain effects. TCNIRv has been demonstrated to estimate phenology metrics more accurately than NIRv, especially exhibiting improved estimation of EOS. As the topographic effect is significantly influenced by terrain properties such as slope and aspect, our study compared phenology metrics estimations between south-facing slopes (SFS) and north-facing slopes (NFS) using NIRv and TCNIRv in two distinct mountainous regions: Gwangneung Forest (GF) and Odaesan National Park (ONP), representing relatively flat and rugged areas, respectively. The results indicated that TCNIR v-derived EOS at NFS occurred later than that at SFS for both study sites (GF : DOY 266.8/268.3 at SFS/NFS; ONP : DOY 262.0/264.8 at SFS/NFS), in contrast to the results obtained with NIRv (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). Additionally, the gap between SFS and NFS diminished after topographic correction (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). We conclude that TCNIRv exhibits discrepancy with NIR v in EOS detection considering slope orientation. Our findings underscore the necessity of topographic correction in estimating photosynthetic phenology, considering slope orientation, especially in diverse terrain conditions.