• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.88-90
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• 2004

주기억 징치 DBMS성능에 캐쉬 미스가 중요한 요소이다. 그래서 캐쉬 미스를 줄여주는 캐쉬 인식 트리(chash consclous trees)들이 개발되어 왔다. 캐쉬 인식 트리에서 사용한 기법들은 포인터 압축, 키 압축 개념으로 일반화 할 수 있다. 포인터 압축은 CS$B^{＋}$-트리처럼 노드에 각 자식 노드를 가리키는 포인터를 제거하고 대신 세그먼트에 저장된 자식 노드들 중 첫 번째 자식 노드를 가리키는 포인터를 저장하는 개념이다. 키 압축은 pkB-트리, R-트리처럼 키 길이를 출이는 개념이다. 본 논문에서는 키 압축 개념과 포인터 압축 개념을 동싱에 지원하고, 디스크 기반의 GiST를 캐쉬 인식하도록 확장한 CC-GiST를 제안한다. 본 논문의 공헌은 다음과 같이 요약된다. 1)기존의 캐쉬 인식 트리들의 기법을 분류하고 분석함으로써, 캐쉬 인식 트리에 적용할 수 있는 일반적인 방법을 도출하였다. 2)포인터 압축을 위해 세그먼트의 개념을 키 압축을 위하여 베이스 키의 개념을 CC-GiST에 도입하였다. 3)디스크 기반의 GiST를 위해 기정의된 메소드들을 캐쉬 인식하도록 완전하게 수정하였다. 4) 제안한 CC-GiST를 이용하여 기존의 대표적인 캐쉬 인식 트리인 CSB＋-트리와 CR-트리를 구현하는 방법을 기술하였다.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.165-171
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• 2017

Recently, the development and dissemination of smart devices linked to the network are being actively performed, and IOT(Internet of things) is issued form of mutually cooperative relationship through interoperation within smart devices. In this paper, we propose an innovative intelligent coffee shop management system by sharing and cooperatively controlling smart devices and Internet devices. The system can order smartphones including kiosk orders and beacon-based user identification. And it is a system that can make custom order without grasping user location information using geofence. The paper provides weather, temperature, time and user-based recommendation services based on Big Data. Therefore, the system is increased cost reduction and work efficiency than general coffee shops.

• Progress in Medical Physics
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• v.27 no.1
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• pp.1-7
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• 2016

In this work, we considered a compressed-sensing (CS)-based image deblurring scheme with a total-variation (TV) regularization penalty for improving image characteristics in digital tomosynthesis (DTS). We implemented the proposed image deblurring algorithm and performed a systematic simulation to demonstrate its viability. We also performed an experiment by using a table-top setup which consists of an x-ray tube operated at $90kV_p$, 6 mAs and a CMOS-type flat-panel detector having a $198-{\mu}m$ pixel resolution. In the both simulation and experiment, 51 projection images were taken with a tomographic angle range of ${\theta}=60^{\circ}$ and an angle step of ${\Delta}{\theta}=1.2^{\circ}$ and then deblurred by using the proposed deblurring algorithm before performing the common filtered-backprojection (FBP)-based DTS reconstruction. According to our results, the image sharpness of the recovered x-ray images and the reconstructed DTS images were significantly improved and the cross-plane spatial resolution in DTS was also improved by a factor of about 1.4. Thus the proposed deblurring scheme appears to be effective for the blurring problems in both conventional radiography and DTS and is applicable to improve the present image characteristics.

• Progress in Medical Physics
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• v.23 no.3
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• pp.162-168
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• 2012

In proton therapy, in vivo dose verification is one of the most important parts to fully utilize characteristics of proton dose distribution concentrating high dose with steep gradient and guarantee the patient safety. Currently, in order to image the proton dose distribution, a prompt gamma distribution detection system, which consists of an array of multiple CsI(Tl) scintillation detectors in the vertical direction, a collimator, and a multi-channel DAQ system is under development. In the present study, the optimal design of prompt gamma distribution detection system was studied by Monte Carlo simulations using the MCNPX code. For effective measurement of high-energy prompt gammas with enough imaging resolution, the dimensions of the CsI(Tl) scintillator was determined to be $6{\times}6{\times}50mm^3$. In order to maximize the detection efficiency for prompt gammas while minimizing the contribution of background gammas generated by neutron captures, the hole size and the length of the collimator were optimized as $6{\times}6mm^2$ and 150 mm, respectively. Finally, the performance of the detection system optimized in the present study was predicted by Monte Carlo simulations for a 150 MeV proton beam. Our result shows that the detection system in the optimal dimensions can effectively measure the 2D prompt gamma distribution and determine the beam range within 1 mm errors for 150 MeV proton beam.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.161-166
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• 2005

In KAERI, about 3,100 drums containing soil have been stored. The soils were generated from the decommissioning process of Seoul office in 1988. Those soils occupy about $27\%$ of the capacity of the radioactive waste storage facility and make it difficult to maintain the storage facility. The major radioactive nuclides contained in the soils were expected to be Co-60 and Cs-137. As 16 years have passed, the radioactivity of those nuclides have decayed a lot. In this study, as a basis of regulatory clearance, radionuclides and radioactivity concentration of soils were analyzed. As a result, there are only Co-60 and Cs-137 in soils as ${\gamma}-emitters$. The total concentration of ${\gamma}-emitters$ in soil is analyzed as about $0.01\;{\sim}\;0.12$ Bq/g. As the soils are expected to be regulatory cleared in 2009, those concentrations will decay to be less than 0.1 Bq/g. This concentration can be meet the regulatory criteria suggested by IAEA. The regulatory clearance will be proceeded based on not only the assessment results of environmental influence but also related regulations.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.335-344
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• 2021

The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.151-156
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• 2016

It has been constantly demanding for effective way to improve software development productivity and automation. In this paper, we did research to configure the component assets to reuse design information from the design phase domains based on the DMI. It is necessary abstracted information architecture of an independent platform development environment to reuse design information on the design stage. Also, It should be based on a well-designed to support the design architecture of the application domain. Therefore, in this paper, I want to use the DMI architecture that can be represented by formal level of architectural design information platform and application domain area. It is able to decomposition architecture asset with the part design information from the design phase composition or a high level of abstraction on DMI. Therefore, the metadata structure of the asset architecture will support a structure which can reuse the structure-based design of the domain areas.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.32-39
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• 2020

In the large-scale infrastructure of cloud environment, illegal access rights are frequently caused by sharing applications and devices, so in order to actively respond to such attacks, a strengthened access control system is required to prepare for each situation. We proposed an entity attribute-based access control(EABAC) model based on security level and relation concept. This model has enhanced access control characteristics that give integrity and confidentiality to subjects and objects, and can provide different services to the same role. It has flexibility in authority management by assigning roles and rights to contexts, which are relations and context related to services. In addition, we have shown application cases of this model in multi service environment such as university.