• 한국정보컨버전스학회:학술대회논문집
• /
• 한국정보컨버전스학회 2008년도 International conference on information convergence
• /
• pp.145-150
• /
• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• 자원ㆍ환경경제연구
• /
• 제14권3호
• /
• pp.753-773
• /
• 2005

시장점유율을 고려한 OPEC와 비OPEC의 게임을 고려한 원유공급 투자모형을 분석한다. 국제유가의 불확실성을 반영하기 위하여 확률투자모형인 실물옵션 모형을 이용한다. 원유공급시설의 확장 및 감축을 위한 조정은 국제유가로 표시되는 분기점으로 나타난다. 국제유가가 확장(감축)분기점을 초과(하회)하면 OPEC는 공급시설을 확장(감축)한다. 최근 국제유가를 활용한 시뮬레이션 분석 결과, 확장분기점은 배스켓 가격 기준으로 높게는 56.93달러/배럴, 낮게는 48.44달러/배럴인 것으로 나타났으며, 감축분기점은 36.52달러/배럴과 36.93달러/배럴 사이에 머무는 것으로 나타났다.

• 정보처리학회논문지B
• /
• 제8B권6호
• /
• pp.693-698
• /
• 2001

본 논문은 주파수 대역 변환 방법을 사용하여 잡음을 제거하는 방법으로, 웨이블릿 변환의 고주파 성분의 통계적 특성을 활용하여 임계값을 선택하는 새로운 방법을 제안한다. 변환 영역의 각 고주파 성분(HL, LH, HH)에 대한 중앙편차를 이용하여 임계값을 설정함으로서 영상의 통계량의 변화에 대응할 수 있고, 잡음 분산의 크기에 적응할 수 있도록 하였다. 실험 결과 잡음 분산을 추정하거나 데이터의 개수를 이용하는 기존의 방법에 비하여 신호 대 잡음비(PSNR)가 향상되었다.

• 대한원격탐사학회지
• /
• 제31권1호
• /
• pp.39-46
• /
• 2015

Outgoing Longwave Radiation (OLR) is emitted energy from the Earth that is an important indicator of cooling effect in global scale and meteorological events in regional scale. Satellite-driven OLR products have its advantages overcoming spatially limited representation. The Korean geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has been producing OLR product in accordance with its own algorithm since Apr. 2011. This study introduces Spatio-Temporally Equalized Match-up (STEM) approach to evaluate the COMS OLR products. We have tested a number of cases of thresholds set by standard deviations of a subpixel $10.8{\mu}m$ to find optimal representation of OLR in the selective match-up. Each case was then validated with broadband reference data, Clouds and the Earth's Radiant Energy System (CERES). We found that selective STEM approach was useful to validate OLR product especially its distribution in homogeneous grids.

• 대한원격탐사학회지
• /
• 제35권1호
• /
• pp.93-115
• /
• 2019

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

• 대한정형도수물리치료학회지
• /
• 제27권2호
• /
• pp.87-92
• /
• 2021

Purpose: This study aimed to investigate the effects of myofascial release technique on pain threshold and hormonal changes in patients with adhesive capsulitis of the shoulder. Methods: Eight patients with adhesive capsulitis were treated with the myofascial release technique. Myofascial release is a form of manual therapy that involves the application of a low load, long duration stretch to the myofascial complex, intended to restore optimal length, decrease pain, and improve function. Blood tests and pressure pain threshold (PPT) examinations were performed on their first visit. On their second visit, the myofascial release technique was applied to the shoulder for 20 min. Then, blood tests and PPT were re-evaluated to determine the effects of the myofascial release technique on pain threshold and hormonal changes. Results: Pain threshold increased from 2.92 to 24.13 lb after treatment. Epinephrine decreased from .13 to .08 ng/mL whereas norepinephrine increased from .25 to .41ng/㎖ after treatment. Conclusion: Myofascial release technique in patients with adhesive capsulitis increased pain thresholds, norepinephrine and decreased epinephrine levels.

• Asia-Pacific Journal of Atmospheric Sciences
• /
• 제54권4호
• /
• pp.527-544
• /
• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.

• 대기
• /
• 제30권4호
• /
• pp.347-360
• /
• 2020

The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권4호
• /
• pp.1373-1391
• /
• 2022

We investigate mobile multiple-input multiple-output (MIMO) molecular communication via diffusion (MCvD) system which is consisted of two source nodes, two destination nodes and one relay node in the mobile three-dimensional channel. First, the combinations of decode-and-forward (DF) relaying protocol and network coding (NC) scheme are implemented at relay node. The adaptive thresholds at relay node and destination nodes can be obtained by maximum a posteriori (MAP) probability detection method. Then the mathematical expressions of the average bit error probability (BEP) of this mobile MIMO MCvD system based on DF and NC scheme are derived. Furthermore, in order to minimize the average BEP, we establish the optimization problem with optimization variables which include the ratio of the number of emitted molecules at two source nodes and the initial position of relay node. We put forward an iterative scheme based on block coordinate descent algorithm which can be used to solve the optimization problem and get optimal values of the optimization variables simultaneously. Finally, the numerical results reveal that the proposed iterative method has good convergence behavior. The average BEP performance of this system can be improved by performing the joint optimizations.

• 응용통계연구
• /
• 제33권4호
• /
• pp.395-407
• /
• 2020

최적분류점에 대한 대부분의 정확도 측도들은 두 종류의 누적분포함수와 확률밀도함수를 기반으로 정의하거나 또는 ROC 곡선과 AUC를 기반으로 정의하는 방법으로 구분하는데, Unal (2017)은 두 가지 방법을 혼합하여 누적분포함수와 AUC를 모두 고려하는 정확도 측도 Index of Union (IU) 통계량을 제안하였다. 본 연구에서는 IU 통계량을 포함한 열 개의 정확도 측도들을 여섯 종류의 범주로 구분하여 각 범주에 속하는 측도들을 비교하면서 IU의 장점을 연구한다. 다양한 정규혼합분포를 설정하여 각각의 측도들에 대응하는 최적분류점들을 구하고 각 분류점에 대응하는 제1종과 제2종 오류 그리고 두 종류의 오류합을 구해서 오류들의 크기를 비교하면서 분류정확도 측도들의 판별력을 비교하면서 IU의 성격과 특징을 탐색한다. 두 종류 분포들의 평균 차이가 증가할수록 IU 통계량의 제1종 오류와 오류합의 크기가 최고의 분류정확도를 갖는 제2범주의 정확도 측도의 오류에 수렴하는 것을 발견하였다. 그러므로 IU는 모형의 판별력을 평가하는 정확도 측도로 활용할 수 있다.