• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.339-341
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• 2009

연안역에 대한 관심이 고조되면서 연안역을 따라 많은 산업화와 관광권화가 진행되고 있으나 안전시설에 대한 무관심으로 인해 많은 인적 및 물적 피해가 속출하고 있다. 충청권 연안역이 가지고 있는 지역적(관광, 산업, 방조제 등) 및 자연적(조수, 해일, 지진, 해양기름유출, 해안습지, 태풍 등) 특성을 고려한 연안역 안전시설을 개발하고자 연구를 수행하고 있다. 선행연구로 서해안 연안역 현장조사를 통한 안전시설물의 설치 현황을 살펴보고 이를 분석하였으며, 이를 통해 연안역 안전시설의 성능 및 설계기준, 건설재료 등에 대한 연구를 기획하였다. 연구과제의 최종 수행결과물로서 제시될 해안 안전 시설물 계획 설계 시공 유지관리에 대한 개발추진계획을 제시한다.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.576-578
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• 2010

현재 제주도의 주 수입원이 관광과 수자원이 되어감에 따라 용천수의 중요성이 부각되고 있다. 그러나 용천수의 관리에 문제가 발생하고 있어 이번 논문에서는 용천수 주변지역 원형 복원을 위한 송이 활용기법을 주제로 삼고 있으며 이번 실험을 통해 용천수 관리의 방안을 제시해 보고자 한다.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.287-290
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• 2007

We investigated the effect of ultrasound on the dewaterability of sewage sludge. Because, dewatering and disposal of waste sludge is a major economical factor in the operation of wastewater treatment plants. Capillary Suction Time(CST) and Specific Resistance to Filtration (SRF) were used to evaluate the sludge dewatering behaviors. From the results of the experiment, it was found that ultrasonic treatment can improve the dewaterability. We discovered that CST and SRF were highly related, according to the correlation coefficient($R^{2}$).

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.633-636
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• 2004

Airborne laser scanning thechnology has been studied in many applications, DSM(Digital Surface Model) development, building extraction, 3D virtual city modeling. In this paper, we will evaluate the possibility of airborne laser scanning technology for transportation application, especially for recognizing moving vehicles on road. First, we initially segment the region of roads from all LiDAR DATA using the GIS map and intensity image. Secondly, the segmented region is divided into the roads and vehicles using the height threshold value of local based window. Finally, the vehicles will be classified into the several types of vehicles by MDC(Minimum Distance Classification) method using the vehicle's geometry information, height, length, width, etc

• Proceedings of the KSRS Conference
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• v.1
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• pp.239-242
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• 2006

Impervious surface is an important index for the estimation of urbanization and environmental change. In addition, impervious surface has an influence on the parameters of rainfall-runoff model during rainy season. The increase of impervious surface causes peak discharge increasing and fast concentration time in urban area. Accordingly, impervious surface estimation is an important factor of urban rainfall-runoff model development and calibration. In this study, impervious surface estimation is performed by using remote sensing images such as landsat-7 ETM+ and high resolution satellite image and regression tree algorithm based on case study area ? Jungnang-cheon basin in Korea.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.79-88
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• 2017

The RapidEye satellite sensor has various spectral wavelength bands, and it can capture large areas with high temporal resolution. Therefore, it affords advantages in generating various types of thematic maps, including land cover maps. In this study, we applied a supervised classification scheme to generate high-resolution land cover maps using RapidEye images. To improve the classification accuracy, object-based classification was performed by adding brightness, yellowness, and greenness bands by Tasseled Cap Transformation (TCT) and Normalized Difference Water Index (NDWI) bands. It was experimentally confirmed that the classification results obtained by adding TCT and NDWI bands as input data showed high classification accuracy compared with the land cover map generated using the original RapidEye images.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.251-253
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• 2008

Erosion and landslide cause serious damage to forest areas. As a consequence, partial or complete destruction of vegetation occurs, which leads to many cascading problems. In this study, an attempt has been made to identify the forest areas, which are under different risk categories of erosion and landslide, in part of Eastern Ghats of Tamil Nadu. Relevantthematic maps were generated from satellite data, topographical maps, primary and secondary data and weights to each map were assigned appropriately. Weighted overlay analysis was carried out to identify the erosionprone forest areas. The result of erosion and landslide prone model reveals that 4712 ha(17%) of forest area is under high risk category and 15879 ha(58.65%) isunder medium risk category. The results of spatial modeling would be very much useful to the forest officials and conservationist to plan for effective conservation.

• Proceedings of KOSOMES biannual meeting
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• 2007.11a
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• pp.109-114
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• 2007

The changed environment on marine security and the security activities such as coast guard and sea patrol in civil domain are analyzed. In order to respond diverse threats and requirements of sea petrol, the system of civil patrolman and coast guard's auxiliary are discussed. The civil boats and aircraft and civilian's security activities make an important role to enhance the effectiveness and the efficiency of coast guard and patrol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1188-1203
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• 2020

The human expression contains a lot of information that can be used to detect complex conditions such as pain and fatigue. After deep learning became the mainstream method, the traditional feature extraction method no longer has advantages. However, in order to achieve higher accuracy, researchers continue to stack the number of layers of the neural network, which makes the real-time performance of the model weak. Therefore, this paper proposed an expression recognition framework based on densely concatenated convolutional neural networks to balance accuracy and latency and apply it to humanoid robots. The techniques of feature reuse and parameter compression in the framework improved the learning ability of the model and greatly reduced the parameters. Experiments showed that the proposed model can reduce tens of times the parameters at the expense of little accuracy.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.