• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.115-123
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• 2005

Quantitative understanding of spatial characteristics of the study site is a prerequisite to investigate water and carbon cycles in agricultural and forest ecosystems, particularly with complex, heterogeneous landscapes. The spatial characteristics of variables related with topography, vegetation and soil in Gwangneung forest watershed are quantified in this study. To characterize topography, information on elevation, slope and aspect extracted from DEM is analyzed. For vegetation and soil, a land-cover map classified from LANDSAT TM images is used. Four satellite images are selected to represent different seasons (30 June 1999, 4 September 2000, 23 September 2001 and 14 February 2002). As a flux index for CO₂ and water vapor, normalized difference vegetation index (NDVI) is calculated from satellite images for three different grid sizes: MODIS grid (7km x 7km), intensive observation grid (3km x 3km), and unit grid (1km x 1km). Then, these data are analyzed to quantify the spatial scale of heterogeneity based on semivariogram analysis. As expected, the scale of heterogeneity decreases as the grid size decreases and are sensitive to seasonal changes in vegetation. For the two unit grids where the two 40 m flux towers are located, the spatial scale of heterogeneity ranges from 200 to 1,000m, which correspond well to the climatology of the computed tower flux footprint.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.1009-1011
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• 2005

그리드 환경으로 구성된 다양한 컴퓨팅 자원을 효율적으로 이용하기 위해 글로벌 스케줄러의 필요성이 강조되고 있다. 하지만, 글로벌 스케줄러는 각 자원에 대한 영향력이 약해, 자원을 효율적으로 관리하는데 작업 상태 파악, 자원 사이트의 균형 조절, 사용자의 자원 독점 등과 같은 문제점이 있다. 본 논문에서는 기존의 글로벌 스케줄러의 문제점을 기준으로 사용자의 수준의 정보를 기반으로 한 스케줄러의 설계를 통해 해결하고자 한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.539-547
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• 2011

In this paper, a method of generating path planning map is developed using digitalized geographic information such as FDB(Feature DataBase). FDB is widely used by the Army and needs to be applied to all weapon systems of newly developed. For the autonomous navigation of a robot, it is necessary to generate a path planning map by which a global path can be optimized. First, data included in FDB is analyzed in order to identify meaningful layers and attributes of which information can be used to generate the path planning map. Then for each of meaningful layers identified, a set of values of attributes in the layer is converted into the traverse cost using a matching table in which any combination of attribute values are matched into the corresponding traverse cost. For a certain region that is gridded, i.e., represented by a grid map, the traverse cost is extracted in a automatic manner for each gird of the region to generate the path planning map. Since multiple layers may be included in a single grid, an algorithm is developed to fusion several traverse costs. The proposed method is tested using a experimental program. Test results show that it can be a viable tool for generating the path planning map in real-time. The method can be used to generate other kinds of path planning maps using the digitalized geographic information as well.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.1
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• pp.215-234
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• 2012

The purpose of this study is to investigate asymmetric and nonlinear nature of the relationship between service attributes and global customer satisfaction, and to identify improvement strategies of service quality in libraries. In this study, two methods(such as kano's analysis and importance grid) were used to analyze the factor structure of customer satisfaction in libraries. The results show that two quality elements are classified as excitement factors, twelve quality elements are sorted as hybrid factor and eight quality elements are classified as dissatisfiers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.157-160
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• 2016

최근 모바일 쇼핑 시장의 거래액 규모는 해마다 기하급수적으로 증가하고 있으며, 기업들은 모바일 애플리케이션의 어떤 특성들이 자사의 매출을 증대시킬 수 있는지에 대해 관심이 있다. 그러므로 본 논문에서는 텍스트 마이닝을 이용하여 사용자들이 많이 쓰는 모바일 쇼핑 애플리케이션의 리뷰에서 자주 쓰는 명사를 추출하고 내용분석을 통해 평가 항목들을 도출한다. 그리고 도출된 평가항목에 레퍼토리 그리드 기법을 적용하여 모바일 쇼핑 애플리케이션을 평가하고 시장 포지셔닝을 실시한다. 이를 통해 모바일 쇼핑 애플리케이션의 어떤 특성이 이용자들의 서비스 선호도에 영향을 미치는지 분석한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1027-1037
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• 2012

With response to the critical issue of global warming, Smart Grid system has been extensively investigated as next efficient power grid system. Domestically, Korean is trying to expand the usage of Electric Vehicles (EVs) and the charging infrastructure in order to replace the current transportation using fossil fuels holding 20% of overall CO2 emission. The EVs charging infrastructures are combined with IT technologies to build intelligent environments but have considerable number of cyber security issues because of its inherent nature of the technologies. This work not only provides logical architecture of EV charging infrastructures with security threats based on them but also analyses security requirements against security threats in order to overcome the adversarial activities to Smart Grid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.813-816
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• 2018

X-ray 진단에서 그리드 하드웨어의 사용은 산란선에 의한 영상의 왜곡을 보정할 수 있는 장점이 있는 반면, 반복되는 라인 형태의 그리드 아티팩트를 발생시키는 부작용을 수반한다. 본 논문에서는 이러한 그리드 라인을 제거하는 방법론으로서 이산코사인변환(DCT: discrete cosine transform)을 사용 하는 기법을 제안한다. X-ray 영상에서 그리드 라인의 특성은 피사체의 형태와 영상의 영역에 따라 서로 다른 특성을 갖는다. 이에 본 연구에서는 동적으로 재구성되는 분할 구조를 기반으로 DCT 변환을 적용하고 개별 영역별로 필터전달함수를 최적화하는 방법을 채택하였다. 추출된 주파수 영역 데이터에 대하여 그리드 라인의 대역을 검출하는 알고리즘을 제안하였으며, 필터전달함수로 Kaiser윈도우와 Butterworth 필터를 조합한 형태의 밴드스톱필러(BSF: band stop filter)를 구현하였다. 또한 블로킹 현상을 개선하기 위하여 다중 영상으로부터 경계선 부분의 픽셀값을 결정하는 방법론을 제안하였다. 제안된 이론에 대하여 실제 영상을 사용한 실험결과로부터 그 타당성을 평가하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.907-910
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• 2019

본 연구에서는 X-ray 영상에서 비산란 그리드 장치의 영향으로 인한 아티팩트를 제거하기 위하여 이산코사인변환(DCT: discrete cosine transform) 기반의 주파수 분석 기법과 딥러닝 네트워크의 학습 기법을 상호 보완적으로 결합하는 방법론을 제안한다. 피사체의 특성에 따라 다양하게 나타나는 그리드 라인의 억제 기능을 학습하기 위하여 서로 다른 특성을 반영하는 3 종류의 학습데이터를 생성한다. 학습에 사용되는 그리드 라인 영상의 타겟 데이터를 산출하기 위하여 DCT 기반의 밴드스톱 필터링 기법을 사용하였으며 학습데이터의 양적인 부족을 해결하기 위하여 패치 기반의 학습 방법을 적용하였다. 제안된 방법에 대해 기존의 방법과 비교하여 피사체 경계선 영역에서 발생하는 성능저하 현상, 분할의 가장자리에서 발생하는 블로킹 현상, 배경 영상에서의 성능저하 현상 등을 상대적으로 개선할 수 있음을 실험적으로 평가하였다.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.