• 소음진동
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• 제7권3호
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• pp.369-376
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• 1997

With recent progress of developing infrastructure, construction vibration from the sites and traffic vibration caused by high-speed rail, subway, and roads is becoming a hazardous factor for vibration environment. In order to predict the damages caused by the vibrations mentioned above the vibration sources, have to be distinguished between point vibration and line vibration. Once the character of the vibration source is determined vibration propagation phenomenon needs to be analyzed by using prediction formula, and compared to the limits authorized by the law. The main purpose of this thesis is to manage the efficient vibration by reflecting these finding in making a consrtuction plan. Therefore, Vibration Management System (VMS) was developed which can predict and analyze the extent of developed utilizing Geographic Information System (GIS) to build a database. This database contains the attribute and the location information of the sources for predicting the formula of explosive vibration and subway traffic vibration, the buildings, the surrounding area and measurement sites. VMS will be useful in the future for predicting the vibrations caused by pile drive, traffic vibrations such as high speed electric railway, highway and roads, and other explosive vibrations by supplementing and updating the database.

• 한국환경복원기술학회지
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• 제19권1호
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• pp.155-170
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• 2016

This study established the definition of invasive disturbance species for a sustainable management and biodiversity, and derived the influence factors caused by the species. To define the species, the paper reviewed similar words such as alien species and invasive species, using standard definitions. Also reviewed the results of recent research on the factors of the species. The paper defined the invasive disturbance species as an species whose establishment and spread threaten ecosystems, habitats or species with economic or environmental harm including native and non-native. Through the reviews, The factors were classified as geographic (altitude, slope, and soil, etc.), climate (temperature, precipitation, climate change, etc.) and, anthropogenic (land use, population, road, and human activity, etc.), and species & vegetation structure (species property, local-species richness, and canopy, etc.). Especially, human activity such as urbanization and highways may be associated with both higher disturbance and higher propagule pressure. In the further study, it is required development of mitigation strategies and vegetation structure model against invasive disturbance species in urban forest based on this study.

• 농촌계획
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• 제10권4호
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• pp.9-18
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• 2004

The purpose or this study is to simulate spatially the urban expansion phenomena with a cellular automata (CA) technique using GIS. A study area, Suwon city, was selected for test of model verification and application with the classified land-use maps of three data years: 1986, 1996, and 2000. The urbanized potential maps were generated with seven criteria of one geographic factor (slope of land), and six accessibility factors (time distances from city, national road, Seoul, station, and built-up boundary), considering their weighting values, which were optimized by WSM (weighted scenario method for intensity order) combined a ranking method and a AHP technique. The optimized weighting values at the urban expansion between 1986 and 1996 were applied to verify the CA model for the other expansion between 1996 and 2000. The results of model application showed that urban sprawl phenomena of the urban expansion toward rural area can be simulated spatially and temporally with several boundary conditions considering various scenarios for the criteria and parameters of the model. Ultimately, this study can contribute to reference data for land-use planning of urban fringe areas.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.294-297
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• 2004

The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and then to apply these to the selected study area of Janghung in Korea. We aimed to verify the effect of data selection on training sites. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use was constructed. Thirteen landslide-related factors were extracted from the spatial database. Using these factors, landslide susceptibility was analyzed using an artificial neural network. The weights of each factor were determined by the back-propagation training method. Five different training datasets were applied to analyze and verify the effect of training. Then, the landslide susceptibility indices were calculated using the trained back-propagation weights and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. The results of the landslide susceptibility maps were verified and compared using landslide location data. GIS data were used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool to analyze landslide susceptibility.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.710-712
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• 2006

The aim of this study was to analyze limestone deposits potential using an artificial neural network and a Geographic Information System (GIS) environment to identify areas that have not been subjected to the same degree of exploration. For this, a variety of spatial geological data were compiled, evaluated and integrated to produce a map of potential deposits in the Gangreung area, Korea. A spatial database considering deposit, topographic, geologic, geophysical and geochemical data was constructed for the study area using a GIS. The factors relating to 44 limestone deposits were the geological data, geochemical data and geophysical data. These factors were used with an artificial neural network to analyze mineral potential. Each factor’s weight was determined by the back-propagation training method. Training area was applied to analyze and verify the effect of training. Then the mineral deposit potential indices were calculated using the trained back-propagation weights, and potential map was constructed from GIS data. The mineral potential map was then verified by comparison with the known mineral deposit areas. The verification result gave accuracy of 87.31% for training area.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.717-720
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• 2006

In this study, we predicted locations vulnerable to ground subsidence hazard using fuzzy logic and geographic information system (GIS). Test was carried out at an abandoned underground coal mine in Samcheok City, Korea. Estimation of relative ratings of eight major factors influencing subsidence and determination of effective fuzzy operators are presented. Eight major factors causing ground subsidence were extracted and constructed as a spatial database using the spatial analysis and the probability analysis functions. The eight factors include geology, slope, landuse, depth of mined tunnel, distance from mined tunnel, RMR, permeability, and depth of ground water. A frequency ratio model was applied to calculate relative rating of each factor, and the ratings were integrated using fuzzy membership function and five different fuzzy operators to produce a ground subsidence susceptibility map. The ground subsidence susceptibility map was verified by comparing it with the existing ground subsidences. The obtained susceptibility map well agreed with the actual ground subsidence areas. Especially, ${\gamma}-operator$ and algebraic product operator were the most effective among the tested fuzzy operators.

• KIEAE Journal
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• 제12권2호
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• pp.25-32
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• 2012

This paper focused on the daylighting performance of residential high-rise buildings in South-Korea. the purpose of this study is to estimate the visual environment of sunlight coming into opening according to sky conditions, orientation of windows and each space of Apartment buildings. Season of the year, weather, and time of day combine with predictable movement patterns of the sun to create highly variable and dynamic daylighting conditions. Daylighting design is usually based on the dominant sky condition and the micro-climate for the building site. There are three common sky conditions: clear sky, overcast sky, and partly cloudy sky. The clear sky includes sunshine and is intense and brighter at the horizon than at the zenith, except in the area around the sun. Daylight received within a building is directly dependent upon the sun's position and the atmospheric conditions. Easily used charts, diagrams, and software programs allow study of solar geometry for any geographic location and time of day. on the other hand, the overcast sky is characterized by diffuse and variable levels of light and has dense cloud cover over 90% of the sky. This paper was calculated by a Desktop Radiance program. The space dimensions were based on a unit module of real constructed apartment having divided into five sections such as living room, room1, room2, room3 and kitchen.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.77-82
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• 2003

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the developed techniques to the study area of janghung in Korea. Landslide locations were identified in the study area from interpretation of satellite image and field survey data, and a spatial database of the topography, soil, forest and land use were consturced. The 13 landslide-related factors were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods, and the susceptibility map was made with a e15 program. For this, the weights of each factor were determinated in 5 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated using the weights and the susceptibility maps were made with a GIS to the 5 cases. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to analyze the landslide susceptibility.

• Asian Pacific Journal of Cancer Prevention
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• 제17권7호
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• pp.3469-3476
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• 2016

Background: The cancer research literature suggests that women, especially premenopausal women, have lower cancer mortality rates than men. However, it is unclear if that is true for populations at all age levels in all countries and what factors affect such sex differences. This paper attempts to fill that gap. Materials and Methods: Sex- and country-specific cancer mortality data were statistically analyzed with particular attention to geographic, social, and economic factors that may affect the sex differences. Results: The sex differences were age and country specific, rather than universal. Premenopausal women actually tend to have a disadvantage compared to men or postmenopausal women. Male cancer mortality appears to be the affecting factor in explaining variations in sex differences. Latitude of residence and literacy rate are the affecting factors in cancer mortality and sex differences. African and Latin American countries tend to have a female disadvantage, while East Asian and Eastern European countries are more likely to have a female advantage. Conclusions: The findings challenge the cancer mortality literature and indicate that the sex differences and their possible causes are more complicated than the current literature suggests. They also highlight the urgency of adapting age- and country- specific health systems and policies to better meet the needs of younger women.

• 유통과학연구
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• 제16권7호
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• pp.47-56
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• 2018

Purpose - This study aims to not only investigate spatial pattern of immigrants' residence and crime occurrences in South Korea, but shed light on how geographic distribution of immigrants and immigrant segregation affect crime rates. Research design, data, and methodology - Th unit of analysis is Si-Gun-Gu municipal level entities of South Korea. The crime data was obtained by Korea National Police Agency and two major types(violence and property) of crime were measured. Most demographic, social, and economic variables were derived from Korean Census Data in 2015. In order to examine spatial patterns of immigrants' distribution and crime rates in South Korea, the present study utilized GIS mapping technique and Exploratory Spatial Data Analysis(ESDA) tools. The causal linkage was investigated by a series of regression models using STATA. Results - Spatial inequality between urban metropolitan vs rural areas was visualized by mapping. Assuming large Moran's I value, spatial autocorrelation appeared to be quite strong. Several neighborhood characteristics such as residential stability and economic prosperity were found to be important factors leading to crime rate change. Residential distribution and segregation for immigrants were negatively significant in the regression models. Conclusions - Unlike the traditional arguments of social disorganization theory, immigrant segregation appeared to reduce violent crime rate and the high proportion of immigrants also turned out to be a crime prevention factor.