• Design Convergence Study
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• v.16 no.5
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• pp.125-140
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• 2017

This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.3
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• pp.196-210
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• 2009

The land surface precesses is very important to predict urban meteorological conditions. Thus, the latest land use data set to reflect the rapid progress in urbanization was applied to simulate urban thermal environment in Daegu. Because use of the U.S geological Survey (USGS) 25-category data, currently in the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), does not accurately described the heterogeneity of urban surface, we replaced the land use data in USGS with the latest land-use data of the Korea Ministry of Environment over Daegu. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 5 classes to account for heterogeneity of urban land cover. The new land cover classification (MC-LULC) improved the capability of MM5 to simulate the daytime part of the diurnal temperature cycle in the urban area. The 'MC-LULC' simulation produced the observed temperature field reasonably well, including spatial characteristics. The warm cores in western Daegu is characterized by an industrial area.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.599-608
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• 2018

As natural disasters are increasing due to the unusual weather and the modern society is getting complicated, the rapid change of the urban environment has increased human disasters. Thus, citizens are becoming more anxious about social safety. The importance of preparation for safety has been suggested by providing the disaster safety services such as regional safety index, life safety map, and disaster safety portal application. In this paper, we propose an application framework to predict the urban safety index based on user's location with realtime weather/atmosphere data after creating a predication model based on the machine learning using number of occurrence cases and weather/atmosphere history data. Also, we implement an application to provide traffic safety index with executing preprocessing occurrence cases of traffic and weather/atmosphere data. The existing regional safety index, which is displayed on the Si-gun-gu area, has been mainly utilized to establish safety plans for districts vulnerable to national policies on safety. The proposed system has an advantage to service useful information to citizens by providing urban safety index based on location of interests and current position with realtime related data.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.71-76
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• 2010

This paper is focused on implementing a real-time data acquisition system that checks power facility status by applying network based technology to Urban Transit substation power facilities and the results of its on-field tests. This system is composed of a sensor part, a measurement part, a transceiver part, a host computer, and a power source part. The system is designed to collect, save, analyze, and display the online state power facility AI (Analog Input). This system measures voltage and current from positive feeders and negative feeders where it is possible to check abnormalities of the substation‘s main power facilities. By monitoring abnormal data of the Urban Transit power facilities real-time and analyzing stored data, establishing procedures of optimized maintenance is possible.

• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.113-129
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• 2017

This paper presents the initial findings of a ground-breaking two-year CTBUH-funded research project investigating the real environmental and social sustainability of people's lifestyles in a number of high-rise residential towers in downtown Chicago, and a comparable number of low rise homes in suburban Oak Park, Chicago - based on actual energy bills and other real data. The study is ground-breaking because, to date, similar studies have been mostly based on very large data sets of generalized data regarding whole-city energy consumption, or large-scale transport patterns, which often misses important nuances. This study has thus prioritized quality of real data (based on around 250 households in both high rise and low rise case studies), over quantity. In both urban and suburban cases, the following factors have been assessed: (i) home operational energy use, (ii) embodied energy of the dwelling, (iii) home water consumption, (iv) mobility and transport movements, (v) urban/suburban Infrastructure, and (vi) quality of life. The full results of this seminal study will be published in the form of a CTBUH Research Report publication in 2017. Presented below is an overview of the initial (and, currently, unverified) findings of the research, together with the limitations of the study that should be taken into account, as well as future plans for developing this important pilot study.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.905-907
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• 2003

In this study, the correlation between the heat island effect and the vegetation in Deagu Korea was performed through using Landsat TM data. the island effect, presents high temperature on air like island, is connected with correlation between the surface temperature and the temperature on the air. In this study, surface temperature was analyzed by detecting the change of urban forestry with remote sensing using the vegetation vitality statistics reference (ratio change of the Park greens in Daegu) the heat island effect not only brings the environment pollution but also brings serious problem such as the destruction of ecosystem to city as a whole. Jeff Luvall has studied to restrain the heat island effect by making urban forestry. Even though Daegu had been the serious high temperature urban area the current temperature of Daegu has been dropped. The correlation between the heat island effect and the vegetation index was analyzed by using satellite images.

• Asian Journal of Business Environment
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• v.2 no.2
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• pp.23-26
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• 2012

Purpose - The study on the consumption structure of urban residents can help us to understand demand law and to grasp the changing consumption trend of people. Consumption structure is an important indicator reflecting the people's living standard. It is of realistic significance to study urban consumption structure. Research data and methodology - This study is carried out with data connected with urban residents from Shandong Statistical Yearbook for the period 2000-2010 analyzing eight commodity groups. The almost ideal demand system (AIDS) is one of the important models related to consumption structure. Results - This paper shows that firstly gives a brief introduction to AIDS. Then it makes an empirical analysis on the urban residents' consumption structure in Shandong province, China on the basis of AIDS model. Conclusions - the authorities are supposed to control the prices of HC, Foodstuff and Housing and encourage the consumption of HC, Housing, EE accordingly. At the same time, local government should increase the supply of goods connected with housing, HA, HC, and EE so as to attract more consumption from the urban residents in Shandong.

• Journal of Korean Society on Water Environment
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• v.34 no.1
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• pp.67-76
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• 2018

There are 34 mega-cities with a population of more than 10 million in the world. One of the highly populated cities in the world is Seoul in South Korea. Seoul receives $1,140million\;m^3/year$ for domestic water, $2million\;m^3/year$ for agricultural water and $6million\;m^3/year$ for industrial water from multi-purpose dams. The maintenance water used for water conservation, ecosystem protection and landscape preservation is $158million\;m^3/year$, which is supplied from natural precipitation. Recently, the use of the other water for preservation of water quality and ecosystem protection in urban areas is increasing. The objectives of this study is to develop the seasonal forecast method of environmental water in urban areas (Seoul, Daejeon, Gwangju, Busan) and to evaluate its predictability. In order to estimate the seasonal outlook information of environmental water from Land Surface Model (LSM), we used the observation weather data of Automated Synoptic Observing System (ASOS) sites, forecast and hind cast data of GloSea5. In the past 30 years (1985 ~ 2014), precipitation, natural runoff and Urban Environmental Water Index (UEI) were analyzed in the 4 urban areas. We calculated the seasonal outlook values of the UEI based on GloSea5 for 2015 year and compared it to UEI based on observed data. The seasonal outlook of UEI in urban areas presented high predictability in the spring, autumn and winter. Studies have depicted that the proposed UEI will be useful for evaluating urban environmental water and the predictability of UEI using GloSea5 forecast data is likely to be high in the order of autumn, winter, spring and summer.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.2
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• pp.18-26
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• 1992

The purpose of this study is to suggest a method for identifying target markets of potential urban park users by their sociodemographic variables. Data was classified into(ⅰ) users vs. nonusers ; (ⅱ) of chosen three urban parks ; or(ⅲ) users of each urban park then analyzed by discriminant analysis. The results showed that linear combination of selected sociodemographic variables could be used for identifying target markets in some cases. In general, season and sex were the most powerful discriminant variables. But the other cases were not satisfactory. The weak points of this study due to adapting secondary data for analysis were discussed.