• 한국환경과학회지
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• 제11권10호
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• pp.1031-1037
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• 2002

CCA (Canonical Correspondence Analysis) was used so as to analyze the relation between vegetation and soil environment of Mankyeong river located in Jeollabuk-do. Vegetation survey consulted 1:5,000 topographical map, set up 30 plot and analyzed from June, 2001, to september, 2001. Plant communities of Mankyeong river was investigated by phytosocialogical method. The species composition of plant communities showed high correlation to soil pH, soil organic matter, $P_2$$O_5$, total nitrogen, EC, when they were analyed by CCA. According to the results of CCA hydrophyte communities were distributed in the region that high pH. But the vegetation of disturbed site and wetland plants were distributed in a good nutrients.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.971-976
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• 2000

In this paper a new method for head gesture recognition is proposed. A the first stage, face image data are transformed into low dimensional vectors by principal component analysis (PCA), which utilizes the high correlation between face pose images. The a self organization map(SM) is trained by the transformed face vectors, in such a that the nodes at similar locations respond to similar poses. A sequence of poses which comprises each model gesture goes through PCA and SOM, and the result is stored in the database. At the recognition stage any sequence of frames goes through the PCA and SOM, and the result is compared with the model gesture stored in the database. To improve robustness of classification, probabilistic relaxation labeling(PRL) is used, which utilizes the contextural information imbedded in the adjacent poses.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1368-1370
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• 2003

Conventional methods investigating soil Hg contamination are time-consuming and expensive. A quicker method is developed to predict soil Hg content with convolved HyMap, ASTER, and TM spectra. The prediction accuracy for each sensor is satisfactory and similar. It suggests that low spectral resolution is not a limitation for predicting soil Hg content. Correlation analysis reveals that Hg -sorption by iron oxides is the mechanism by which to predict spectrally featureless Hg with reflectance spectra. Future study with field measurements and remote sensing data is recommended.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1609-1618
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• 2016

is a service providing the story synopses that match user's query. This paper analyzes the user log of which is the answers to the queries to find stories from database, and shows the tendency distribution of user creation. Specially, we analyze a joint distribution of the genres and actions of stories to get better understanding of the tendencies that cannot be found in the analysis of independent distribution. Furthermore, we define a correlation factor between genre and action, and investigate what combinations of the genres and actions are highly, less, and negatively correlated. Finally, we investigate how the tendencies of characters are related to genres and actions, and propose a visualization method to show the tendencies.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.36-36
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• 2017

일반적으로 유역의 지형학적 특성을 나타내는 인자들은 유역면적, 유로연장, 유로경사 등 여러가지가 있다. Horton (1945)은 수계의 발달 형태에 기초한 하천의 차수를 이용하여 분기비, 길이비, 면적비, 하천 밀도 등 지형학적인 매개변수로 제시하였다. 유역 지형학적 매개변수는 Horton이 제시한 유역내 하도망의 지형학적인 구성에 대한 특성을 반영하는 것으로 유출에 지배적인 영향을 미친다. 한강 유역 19개 하천의 27개 지점을 대상으로 유출 특성과 지형학적 특성의 상관 분석을 위하여 유역과 하천의 지형학적 특성을 Arc-Map을 이용하여 구하였다. 하천차수법칙에 의한 지형학적인 매개변수로 분기비, 길이비, 함몰도, 면적비를 산정하였고, 유역의 지형학적 인자는 유역면적, 유로연장, 유로경사, 형상계수, 단일형상계수, 세장률, 수계밀도, 수계빈도를 산정하였다. 수계의 연간 유출률은 실측 유출량과 강수량 자료를 이용하여 산정하였다. 각각의 지형학적 특성인자에 대한 상관 매트릭스를 분석하고 그 상관특성을 분석하였다. 특히 지형학적 매개변수와 지형학적 요소와 연간 유출률과의 상관관계식을 제시하였다.

• 소성∙가공
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• 제31권2호
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• pp.64-72
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• 2022

Since aluminum alloys experience both tensile and compression deformation modes during forming process, it is important to understand the role of deformation mode on the hot formability of metallic alloys. In the present work, the hot formability of Al7050 alloy was investigated by conducting both tensile and Gleeble tests at various temperatures and strain rates. Processing maps representing low efficiency regions were observed at low temperature and high strain rate in both tensile and compressive deformation modes while the maximum efficiency regions depended on different deformation modes. Moreover, samples tested at stable processing conditions presented a smaller pore fraction than those at instable conditions that resulted in crack initiation during plastic deformation. This result shows that different deformation modes during plastic forming can affect formability changes of metallic alloys. Understanding of tension-compression behaviors will help us solve this problem.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• Current Optics and Photonics
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• 제7권6호
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• pp.655-664
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• 2023

Ghost imaging (GI) technology is developing rapidly, but there are inevitably some limitations such as the influence of atmospheric turbulence. In this paper, we study a ghost imaging system in atmospheric turbulence and use a gamma-gamma (GG) model to simulate the medium to strong range of turbulence distribution. With a compressed sensing (CS) algorithm and generative adversarial network (GAN), the image can be restored well. We analyze the performance of correlation imaging, the influence of atmospheric turbulence and the restoration algorithm's effects. The restored image's peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) increased to 21.9 dB and 0.67 dB, respectively. This proves that deep learning (DL) methods can restore a distorted image well, and it has specific significance for computational imaging in noisy and fuzzy environments.

• 한국음향학회지
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• 제36권6호
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• pp.413-418
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• 2017

수중 운동체의 방사소음을 측정하는 경우 음원과 수신기 사이의 거리 정보가 중요한 평가 요소이지만 GPS를 사용할 수 없다. GPS를 대신하여 음원의 거리를 찾는 방법으로써 상호 상관도를 사용하는 방법이 있다. 하지만 이는 많은 계산량을 갖는다. 본 논문에서는 상대적으로 적은 연산량을 갖는 고속 퓨리에 변환 기반의 방법을 사용하여 거리를 추정한다. 제안한 방법은 다수의 수신기에 수신되는 CW 신호로부터 고속 퓨리에 변환을 사용하여 도플러 주파수를 추정하고, 수신기 위치, 음원 수심 정보들을 이용하여 이론적으로 미리 산출된 도플러 주파수 맵을 비교하여 거리를 추정한다. 성능검증을 위해 모의 및 호수실험을 수행하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.