• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.41-49
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• 2017

The 'NIST Framework and Road Map for Smart Grid Interoperability Standards' proposes an architecture framework to secure the direction of development and standard interoperability of smart grid and provides a list of identified standard, standard cyber security strategies, and certification framework. In particular, SEP 2.0 and OpenADR 2.0 are the examples. SEP 2.0 and OpenADR 2.0 can functionally link HEMS and Smart Grid, but interoperability standards between the two protocols are not planned in above document. The OpenADR Alliance also announced that work is underway to define mapping tables for interoperability between OpenADR 2.0 and SEP 2.0, but no information is yet available. Therefore, In this paper, in developing energy efficiency improvement HEMS, we propose a mapping model that supports syntactic and semantic founded interoperability between SEP 2.0 and OpenADR 2.0b for ICT grid convergence based on the standard specification document of each protocol and confirmed through an example of the semantic mapping function based on the demand response service scenario.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.475-484
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• 2006

Recently, the studies on the extraction of 3-dimension coordinate and attribute information of objects using LiDAR data are carried out widely. LiDAR data has high locational accuracy, and advantage that can process data more fast because there's not coordinate transform when acquire of Data justly the ground coordinate by Acquiring. The purpose of the paper using only LiDAR data Manufacture road, building, contour That occupy a many parts of Digital Map. Estimated for possibility of Digital mapping using only LiDAR data As that compare accuracy with traditional Digital map.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.911-916
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• 2005

Noise map is a presentation of existing data or predicted noise situation in terms of noise indicator. However, it has shortcoming for assessing the number of people exposed, or the number of dwellings affected to any relevant limit values of noise level in certain areas. In this study, so called over-ride value noise mapping is proposed to make up for the shortcoming by using over-ride function of object-oriented programming and it is to show the guard of the area where it is satisfied the standard of option, or it is not satisfactory. Over-ride value noisemap data is combined with topography layer, population and house statistics, and GIS space statistical analysis. The over-ride value noise mapping can also he applied to make the road traffic noisemap, the railroad noisemap, the aircraft noisemap, and the industrial site noisemap This can express noise damage information more exactly.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.59-65
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• 1998

A thematic land cover map of Pusan port area was developed using Landsat satellite TM(Thematic Mapper) image. Two types of digital data which are road and sea water layer are extracted from existing paper map were overlayed over the developed land cover map. SPIN-2(KNR-1000) image was utilized to make a facility map of JaSungDae port. SPIN-2 image, which has a cell resolution of 1.56 m showed higer accuracy than TM image, which has a cell resolution of 30 m for facility mapping. Overall, the techniques of digital mapping using satellite image are very useful, effective and efficient.

• Journal of computational fluids engineering
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• v.9 no.4
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• pp.7-12
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• 2004

In the present study a semi-automatic mesh generation program has been developed by using DXF file containing contour line data. The program consists of DXF file reader and mapping algorithm. Pre-generated 2-D planar mesh points are to be mapped one by one onto triangular surface whose three vertices are three nearest contour points surrounding the mapping point. The present program has been successfully tested for mesh generations for the road tunnel ventilation analysis and analysis of lava movement in mountain area.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.7 s.100
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• pp.859-864
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• 2005

Noise map is a presentation of existing data or predicted noise situation in terms of noise indicator. However, it has shortcoming for assessing the number of people exposed, or the number of dwellings affected to any relevant limit values of noise level in certain areas. In this study, so called over-ride value noise mapping is Proposed to make up for the shortcoming by using over-ride function of object-oriented programming and it is to show the guard of the area where it is satisfied the standard of option, or it is not satisfactory. Over-ride value noise map data is combined with topography layer, population and house statistics, and GIS space statistical analysis. The over-ride value noise mapping can also be applied to make the road traffic noise map, the railroad noise map, the aircraft noise map, and the industrial site noise map. This can express noise damage information more exactly.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.131-134
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• 2005

This study examine the annoyance of transportation noise exposure and found the survey method about which noise induces more disturbance or annoyance when more than two kinds of noise exist. This study describes the noise annoyance survey performed in the vicinity of Sin-wol interchange. This residential area was exposed to aircraft noise and traffic noise simultaneously and aircraft noise exposure of this area is about 81 WECPNL, traffic noise exposure is about 81.2 dB(A) nearby road. Noise sources are grouped into three part, traffic noise, aircraft noise and community noise. The questionnaire includes how often, how loud each noise is heard. Also this deals with comparative annoyance reaction from specific noise sources such as aircraft or traffic and its disturbance of daily activities. Facade noise mapping are executed by using a commercial noise mapping software.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.4
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• pp.275-283
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• 2015

The aim of this study is to estimate the noise exposure of roadside apartment complex according to the characteristics of apartment complex. The facade noise level of residential buildings and the ground noise level inside apartment complexes were predicted and analyzed using noise mapping based on a computerized noise model. In addition, the correlation analysis between these noise levels and the characteristics of apartment complex such as traffic volume, building coverage, the number of adjacent roads, etc. was done in a total of 21 apartment complexes. The results showed that building facade noise level and ground noise level were positively correlated with traffic volume (correlation coefficient, r=0.616~0.623) and the number of adjacent roads (r=0.340~0.496). On the other hand, they were negatively correlated with building coverage (r=-0.413~-0.477) and complex area per the number of roads (r=-0.478~-0.615).

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.235-244
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• 2006

The MMS(Mobile Mapping System) using the vehicle equipped GPS, IMU and CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. The image, vehicle's 3 dimensional position and attitude information provided MMS is a important source for positioning objects included the image. In this research we applied the tracking technique to the specific object in image. The extraction of important object from immense MMS data makes more effectiveness in this system.