• Journal of the Optical Society of Korea
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• 제13권1호
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• pp.22-27
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• 2009

Target design study to improve the quality of an accelerated proton beam from the interaction of a high-intensity short pulse laser with an overdense plasma slab has been accomplished by using a two-dimensional, fully electromagnetic and relativistic particle-in-cell (PIC) simulation. The target consists of a thin core part and a thick peripheral part of equivalent plasma densities, while the ratio of the radius of the core part to the laser spot size, and the position of the peripheral part relative to the fixed core part were varied. The positive effects of this core-peripheral target structure could be expected from the knowledge of the typical target normal sheath acceleration (TNSA) mechanism in a laser-plasma interaction, and were apparently evidenced from the comparison with the case of a conventional simple planar target and the case of the transversal size reduction of the simple planar target. Improvements of the beam qualities including the collimation, the forward directionality, and the beam divergence were verified by detailed analysis of relativistic momentum, angular directionality, and the spatial density map of the accelerated protons.

• 한국정보전자통신기술학회논문지
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• 제13권2호
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• pp.153-158
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• 2020

본 논문에서는 무선 통신 환경에서 잡음 및 간섭을 제거하여 원하는 목표물을 추정하는 알고리즘을 연구하였다. 잡음과 간섭이 포함된 정보신호가 수신기에 입사하면 원하는 목표물을 정확히 추정하기 어렵기 때문에 잡음 및 간섭 신호를 제거하는 방법이 필수적이다. 수신 신호영역을 두 공간으로 분리하기 위해서 상관행렬, 공분산, 고유특성벡터, 고유치를 분석하여 전력 스펙트럼을 획득한다. 제안한 전력 스펙트럼은 잡음을 제거할 수 있는 알고리즘으로서 목표물 추정성능을 분석하기 위해서 기존의 알고리즘과 모의실험을 통해서 확인한다. 모의실험 결과로, 기존 알고리즘의 목표물방향 추정 분해능은 10°이상이지만, 제안 알고리즘의 분해능은 10°미만을 나타내었다. 제안 알고리즘이 기존 알고리즘보다 약 5°의 분해능이 향상 되었다. 본 연구에서 제안된 알고리즘이 목표물 추정 정확도와 분해능이 기존 알고리즘보다 우수함을 입증하였다.

• 한국환경복원기술학회지
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• 제20권5호
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• pp.43-58
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• 2017

This study aims to provide basic understanding for evaluating the quantitative and qualitative progress of national protected areas, through the theoretical review of Aichi Biodiversity Target 11 in order to comply with recommendations of international community and to conserve biodiversity. As a result of the study, Aichi Biodiversity Target 11 sets out the specific contents that the Parties should achieve for protected areas by identifying them as temporal and spatial goals. The temporal goal, the time schedule for achieving the goal, is 2020, and the spatial goal is divided into quantitative expansion goals and qualitative improvement goals. The quantitative expansion goals present the target coverage of protected areas separately terrestrial and marine. The qualitative improvement goals include the target areas for conservation and five conservation considerations. The conservation targets focus on the important areas with regard to biodiversity and ecosystem services. The five conservation considerations mean effective management, equitable management, ecological representativeness, connectivity, and integration into the landscape and seascape for protected areas. Finally, it suggests that two tracks of protected areas and other effective area-based conservation measures(OECMs) should be used as conservation measures to build an integrated system. The results of this study can be applied to quantitative and qualitative evaluation methods for protected areas and it can contribute to achieve quantitative expansion goals and qualitative improvement goals for them.

• 한국작물학회지
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• 제50권4호
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• pp.238-246
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• 2005

Rice yield and protein content have been shown to be highly variable across paddy fields. In order to characterize this spatial variability of rice within a field, two-year experiments were conducted in 2002 and 2003 in a large-scale rice field of $6,600m^2$ In year 2004, an experiment was conducted to know if variable rate treatment (VRT) of N fertilizer, that was prescribed for site-specific management at panicle initiation stage, could reduce spatial variation in yield and protein content of rice while increasing yield compared to conventional uniform N topdressing (UN, 33kg N/ha at PIS) method. VRT nitrogen prescription for each grid was calculated based on the nitrogen (N) uptake (from panicle initiation to harvest) required for target rice protein content of $6.8\%$, natural soil N supply, and recovery of top-dressed N fertilizer. The required N uptake for target rice protein content was calculated from the equations to predict rice yield and protein content from plant growth parameters at panicle initiation stage (PIS) and N uptake from PIS to harvest. This model· equations were developed from the data obtained from the previous two-year experiments. The plant growth parameters for the calculation of the required N were predicted non-destructively by canopy reflectance measurement. Soil N supply for each grid was obtained from the experiment of year 2003, and N recovery was assumed to be $60\%$ according to the previous reports. The prescribed VRT N ranged from 0 to 110kg N/ha with an average of 57kg/ha that was higher than 33 kg/ha of UN. The results showed that VRT application successfully worked not only to reduce spatial variability of rice yield and protein content but also to increase rough rice yield by 960kg/ha. The coefficient of variation (CV) for rice yield and protein content was reduced significantly to $8.1\%$ and $7.1\%$ in VRT from $14.6\%$ and $13.0\%$ in UN, respectively. And also the average protein content of milled rice in VRT showed very similar value of target protein content of $6.8\%$. In conclusion the procedure used in this paper was believed to be reliable and promising method for reducing within-field spatial variability of rice yield and protein content. However, inexpensive, reliable, and fast estimation methods of natural N supply and plant growth and nutrition status should be prepared before this method could be practically used for site-specific crop management in large-scale rice field.

• 한국측량학회지
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• 제30권5호
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• pp.485-492
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• 2012

최근 디지털 항공영상 센서는 다양한 국가 공간정보기반구축에 큰 역할을 하고 있다. 하지만 고정밀의 신뢰성 있는 자료를 확보하기 위해서는 취득된 디지털영상에 대한 적절한 품질 평가 작업이 선행되어야 한다. 따라서 현재 관련분야의 연구가 국내외적으로 크게 주목을 받고 있다. 디지털카메라의 성능을 테스트하기 위한 영상해상력 검증용 테스트필드가 유럽과 미국 등에서 이미 설치 및 활용되고 있다. 이러한 테스트필드에는 카메라의 기하학적 성능분석을 위한 대공표지를 비롯하여 공간해상력 및 방사해상력 분석을 위한 다양한 형태의 타겟 역시 설치되어 있다. 본 연구에서는DMC 카메라의 공간해상력을 검증하기 위하여 영상에서 인식 가능한 크기의 바 타겟(bar target)을 제작 설치 후 항공촬영을 수행하였다. 연구에 사용된 DMC 영상의 이론적인 지상표본거리(GSD ; Ground Sample Distance)는 12cm 급으로, 촬영 비행방향과 비행방향의 직각방향에 대하여 보조영상과 집성영상에 대하여 각각 실제 해상력을 분석하였다. 연구결과 이론적인 해상력과 영상의 실제 해상력간의 차이는 약 0.6cm로 나타났으며, 블록의 가장자리에 위치한 영상에서 최대 1.5cm 정도로 나타났다.

• 한국전산구조공학회논문집
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• 제31권4호
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• pp.207-213
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• 2018

본 연구에서는 건물 실내 공간 정보 획득을 위해 Microsoft사의 $Kinect^{(R)}$ v2를 활용한 point cloud 기법을 도입하였다. 카메라로 취득한 2차원의 투영 공간 이미지 픽셀 좌표를 각 카메라의 보정을 거쳐 3차원 이미지 변환하며 이를 토대로 공간 정보를 구현하였다. 기준점을 중심으로 $360^{\circ}$ 회전하여 취득한 3차원 이미지를 통해 거리 측정이 불가한 기존의 2차원 이미지의 한계를 개선하였으며, 이 과정을 통해 얻은 point cloud를 통해 3차원 map을 형성하였다. 형성된 3차원 map은 기존의 공간정보 융 복합을 위한 센서와 비슷한 수준의 측정 효율을 가지면서 동시에 렌즈 왜곡 현상에 대한 후처리 과정을 통해 공간 정보를 정확하게 측정할 수 있도록 하였다. 측정한 결과를 2D 도면과 실제 공간 및 구조부재의 길이 및 위치 등과 비교하여 검증하였다.

• 한국정보전자통신기술학회논문지
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• 제12권4호
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• pp.419-424
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• 2019

본 논문에서는 광대역 재밍 신호 환경에서 원하는 목표물을 추정하기 위한 알고리즘을 제안 한다. 재밍 신호를 억제하는 방법으로, 본 연구에서는 시공간적응 알고리즘과 QR분해를 사용하여 최적의 가중치를 획득한다. 시공간적응 알고리즘은 적응배열안테나시스템에서 탭 지연 신호에 복소 가중치를 곱하여 가중치를 생성하고, 역행렬로 인한 전력소모를 최소화하기 위해서 QR분해를 이용하여 최적의 가중치를 획득한다. 모의실험을 통하여, 본 연구에서 제안한 알고리즘과 기존 알고리즘의 성능을 비교 분석한다. [-40o,0o,+40o]의 목표물 추정에서 본 연구에서 제안 한 알고리즘이 3개의 목표물을 모두 추정하였지만 기존 알고리즘은 재밍 신호 때문에 [0o]에서만 추정하였다. 본 연구의 제안 알고리즘이 재밍 신호를 제거하고 원하는 목표물을 정확히 추정하여 성능이 향상되었음을 입증하였다.

• 한국측량학회지
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• 제34권2호
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• pp.111-120
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• 2016

Prior knowledge about the SNS (Social Network Services) datasets is often required to conduct valuable analysis using social media data. Understanding the characteristics of the information extracted from SNS datasets leaves much to be desired in many ways. This paper purposes on analyzing the detail of the target social network services, Twitter, Instagram, and YouTube to establish the spatial informatization process to integrate social media information with existing spatial datasets. In this study, valuable information in SNS datasets have been selected and total 12,938 data have been collected in Seoul via Open API. The dataset has been geo-coded and turned into the point form. We also removed the overlapped values of the dataset to conduct spatial integration with the existing building layers. The resultant of this spatial integration process will be utilized in various industries and become a fundamental resource to further studies related to geospatial integration using social media datasets.

• 디지털산업정보학회논문지
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• 제10권4호
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• pp.71-78
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• 2014

Method a target estimation in spatial are mobile wireless communication using network cell and GPS. It have much error that mobile wireless communication depend on cell size. GPS method can't find a target in shadow and inner area. In this paper, we estimate a target as direction of arrival method using adaptive array antenna system. Adaptive array antenna system can obtain desired signal to remove other signal This paper studied digital beamforming method in order to estimation a target. Proposed method is modified optimum weight and antenna error correction to estimation an optimal receive signal. Digital beamforming method decided a signal phase and amplitude from received signal on array antenna element. But if it is not to do error correction of received signal, system performance have decreased. Firstly, we proposed modified optimum weight in order to finding desired target. Secondly, we are error correction of antenna incident signals by optimal weight before digital beamforming method. Thirdly, throughly simulation, we showed that system performance of proposed method compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.