• Title/Summary/Keyword: city classification

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IMAGE CLASSIFICATION OF HIGH RESOLTION MULTISPECTRAL IMAGERY VIA PANSHARPENING

  • Lee, Sang-Hoon
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.18-21
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    • 2008
  • Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

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An Application of Decision Tree Method for Fault Diagnosis of Induction Motors

  • Tran, Van Tung;Yang, Bo-Suk;Oh, Myung-Suck
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2006.11a
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    • pp.54-59
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    • 2006
  • Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data.

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Classification and Preparation of checklist of ecological and cultural resources of rural area in point of Green tourism

  • Kim, Bum-Soo
    • Journal of Environmental Science International
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    • v.12 no.2
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    • pp.145-149
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    • 2003
  • This study was carried out to present rural functional resources through classification and preparation of checklist for ecological and cultural resources which considered various aspect of agriculture and rural area. In this study the function of ecological and cultural resources classified 6 functions such as natural environment, free environmentally agricultural products, experience of agricultural products, recreational places, rural life experience, and Interchanges of human resources. Prepared evaluation list through this study can explain a local characteristics based on 6 functions of agricultural and mountain village. This evaluation list was focused on the magnitude of the resources which motivate the visiting of city-dweller as a consumer, for an actual regional plan, investigation of the inhabitant consciousness survey should be needed, simultaneously.

Family System Model and Adolescent Adjustment - The Olson Circumplex and Beavers Systems Models - (가족체계모델과 청소년의 적응)

  • 전귀연
    • Korean Journal of Human Ecology
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    • v.2 no.1
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    • pp.38-51
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    • 1999
  • The purpose of this study was to test the validity of Olson Circumplex Model and Beavers Systems Model related to adolescent adjustment. The 830 subjects were selected from the second grade of middle and high schools and adolescents of Juvenile Judge in the city of Taegu. The survey instruments were FACESIII, SFIII, State-Trait Anxiety Inventory, Depression Scale, and Delinquency Scale. Factor Analysis, Cronbach's ${\alpha}$. MANOVA, Scheff'e test were conducted for the data analysis. The major findings of this study were as follows: 1) Family system classification method on Olson Circumplex Model was partially useful in evaluating anxiety, depression, and delinquency of adolescent. 2) Family system classification method on Beavers Systems Model was partially useful in evaluating anxiety and depression of adolescent. (Korean J Human Ecology 2(1) : 38~51, 1999)

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Development of Land Suitability Classification System for Rational Agricultural Land Use Planning (농지이용계획의 합리적 책정을 위한 농지적성 평가기법의 개발)

  • 황한철;최수명
    • Journal of Korean Society of Rural Planning
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    • v.3 no.2
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    • pp.102-111
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    • 1997
  • For rational agricultural land use planning, it is quite necessary to get hold of land suitability precisely and to make decision on land use patterns accordingly. In the methodological viewpoint, objective and scientific evaluation techniques for land suitability classification should be supported for the systematic land use planning. As one of technical development approaches to rational land use planning, this study tried to frame a land suitability evaluation system for agricultural purposes. Evaluation unit is defined as a tract of land bounded by road, other land units and topographical features. And quantification theory was applied in the determination works of evaluation criteria. The administrative area of Namsa-myon(district), Yongin-si(city), Kyunggi-do(province) was selected for the case study. In order to check the feasibility of the evaluation system developed in the study, field check team, consisting of 2 government officers and 2 representative farmers, carried out evaluation works by observation on 148 sample land units, 10% of total 1,480 ones. Between estimated and observed results, there showed very good relationship of its multiple correlation coefficient, R=0.9467.

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Land Use Classification Using GIS based Statistical Unit data (GIS기반의 통계정보를 이용한 토지이용 분류)

  • 민숙주;김계현;박태옥;전방진
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.343-347
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    • 2004
  • Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

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Development of Smart Trash Box for Automatic Classification of Recyclables based on IoT (IoT 기반 재활용품 자동 분류 스마트 쓰레기통 개발)

  • Ji-Hoon Kim;Su-Bin Lee;Soo-Min Park;Ga-In Seo;Jaisoon Baek;Sung Jin Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.145-146
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    • 2024
  • 본 논문에서는 최근 몇 년 동안 스마트시티 인프라 투자가 크게 성장하였으며 글로벌 스마트 쓰레기통 시장은 성장 가능성이 높을 것으로 예상된다. 본 논문에서는 이에 발맞추어 CNN과 MQTT를 활용한 스마트 쓰레기통을 제작하였다. 쓰레기의 종류를 구별하고 해당되는 쓰레기통의 뚜껑을 골라 여는 것은 현대인의 생활에서 비효율을 야기한다. 이러한 문제를 해결하고자 CNN을 통한 효율적인 분류와 MQTT를 통한 통신, 센서들을 활용한 더 나은 쓰레기 수거 방식을 제공한다. 스마트 쓰레기통으로 일상을 더욱 편하고 효율적이게 만드는 데 기여하고자 한다.

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Development for City Bus Dirver's Accident Occurrence Prediction Model Based on Digital Tachometer Records (디지털 운행기록에 근거한 시내버스 운전자의 사고발생 예측모형 개발)

  • Kim, Jung-yeul;Kum, Ki-jung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.1
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    • pp.1-15
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    • 2016
  • This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.

Development of a method for urban flooding detection using unstructured data and deep learing (비정형 데이터와 딥러닝을 활용한 내수침수 탐지기술 개발)

  • Lee, Haneul;Kim, Hung Soo;Kim, Soojun;Kim, Donghyun;Kim, Jongsung
    • Journal of Korea Water Resources Association
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    • v.54 no.12
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    • pp.1233-1242
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    • 2021
  • In this study, a model was developed to determine whether flooding occurred using image data, which is unstructured data. CNN-based VGG16 and VGG19 were used to develop the flood classification model. In order to develop a model, images of flooded and non-flooded images were collected using web crawling method. Since the data collected using the web crawling method contains noise data, data irrelevant to this study was primarily deleted, and secondly, the image size was changed to 224×224 for model application. In addition, image augmentation was performed by changing the angle of the image for diversity of image. Finally, learning was performed using 2,500 images of flooding and 2,500 images of non-flooding. As a result of model evaluation, the average classification performance of the model was found to be 97%. In the future, if the model developed through the results of this study is mounted on the CCTV control center system, it is judged that the respons against flood damage can be done quickly.

Location and Analysis on Effects of Subway Station using GIS and RS (GIS와 RS를 이용한 전철역의 영향권 분석 및 위치선정)

  • 양인태;천기선;박재국;오이균
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.10a
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    • pp.359-364
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    • 2003
  • Population concentration phenomenon of city need large-scale ride, and ride is important urea that develop area and is armed surrounding land utilization. but, it is difficult to evaluate effect that ride gets land utilization change and community development as quantitative. Therefore, this research evaluates change and effect of land utilization as political to subway station that is main ride of Seoul City, and chose standard and position for right place arrangement of electric railway station. Research contents analyzed subway station effect area interior and external land utilization change taking advantage of GIS's buffer function and RS's classification technique, and decide precedence at subway station establishment and chose position of subway station for effect area outside area.

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