• The Journal of Korean Physical Therapy
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• 제21권2호
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• pp.87-95
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• 2009

Purpose: This study reports the basic reference data of the specific gait parameters for Korean normal adults. Methods: The basic gait parameters were extracted from 73 Adults (35 men and 38 women), 18 to 33 years of age, using a Vicon MX motion analysis system. The segment kinetics, such as joint moment and power, was analyzed at the hip, knee and ankle. Results: The motion patterns are typically associated with a specific phase of the gait cycle. The temporal-spatial gait parameters of Korean normal adults, such as cadence, walking speed, stride length, single support and double support, were similar to the other western reference data. The kinetic parameters of Korean normal adults, such as joint moments of force, joint mechanical power generation or absorption and ground reaction forces, were also similar to other western reference datasets. Conclusion: This study demonstrates that objective gait analysis can be used to document the gait patterns of normal healthy adults. The techniques of 3-dimensional temporal-spatial gait parameters and kinematic parameters analysis can provide a detailed biomechanical description of a normal and pathological gait.

• Ocean and Polar Research
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• 제44권2호
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• pp.179-190
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• 2022

Data missing in optical satellite images caused by natural variations have been a crucial barrier in observing the status of marine surfaces. Although there have been many attempts to fill the gaps of non-observation, there is little research to analyze the ratio of missing grids to overall sea grids and their seasonal patterns. This report introduces the method of quantifying the distribution of missing points and then shows how the missing points have spatial correlation and seasonal trends. Both temporal and spatial integration methods are compared to assess the effectiveness of reducing missing data. The temporal integration shows more outstanding performance than the spatial integration. Moran's I and K-function with statistical hypothesis testing show that missing grids are clustered and there is a non-random distribution from daily integration. The result of the seasonality test for Moran's I through a periodogram shows dependency on full-year, half-year, and quarter-year periods respectively. These analysis results can be used to deduce appropriate integration periods with permissible estimation errors.

• 대한원격탐사학회지
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• 제31권4호
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• pp.321-330
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• 2015

Atmospheric correction is an essential part in time-series analysis on biophysical parameters of surface features. In this study, we tried to examine possible problems in atmospheric correction of multitemporal High Spatial Resolution (HSR) images obtained from two different sensor systems. Three KOMPSAT-2 and two IKONOS-2 multispectral images were used. Three atmospheric correction methods were applied to derive surface reflectance: (1) Radiative Transfer (RT) - based absolute atmospheric correction method, (2) the Dark Object Subtraction (DOS) method, and (3) the Cosine Of the Uun zeniTh angle (COST) method. Atmospheric correction results were evaluated by comparing spectral reflectance values extracted from invariant targets and vegetation cover types. In overall, multi-temporal reflectance from five images obtained from January to December did not show consistent pattern in invariant targets and did not follow a typical profile of vegetation growth in forests and rice field. The multi-temporal reflectance values were different by sensor type and atmospheric correction methods. The inconsistent atmospheric correction results from these multi-temporal HSR images may be explained by several factors including unstable radiometric calibration coefficients for each sensor and wide range of sun and sensor geometry with the off-nadir viewing HSR images.

• 대한원격탐사학회지
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• 제35권5_1호
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• pp.681-692
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• 2019

이 논문에서는 작물 분류를 목적으로 작물의 시공간 특징을 고려할 수 있는 딥러닝 모델 2D convolution with bidirectional long short-term memory(2DCBLSTM)을 제안하였다. 제안 모델은 우선 작물의 공간 특징을 추출하기 위해 2차원의 합성곱 연산자를 적용하고, 추출된 공간 특징을 시간 특징을 고려할 수 있는 양방향 LSTM 모델의 입력 자료로 이용한다. 제안 모델의 분류 성능을 평가하기 위해 안반덕에서 수집된 다중시기 무인기 영상을 이용한 밭작물 구분 사례 연구를 수행하였다. 비교를 목적으로 기존 딥러닝 모델인 2차원의 공간 특징을 이용하는 2D convolutional neural network(CNN), 시간 특징을 이용하는 LSTM과 3차원의 시공간 특징을 이용하는 3D CNN을 적용하였다. 하이퍼 파라미터의 영향 분석을 통해, 시공간 특징을 이용함으로써 작물의 오분류 양상을 현저히 줄일 수 있었으며, 제안 모델이 공간 특징이나 시간 특징만을 고려하는 기존 딥러닝 모델에 비해 가장 우수한 분류 정확도를 나타냈다. 따라서 이 연구에서 제안된 모델은 작물의 시공간 특징을 고려할 수 있기 때문에 작물 분류에 효과적으로 적용될 수 있을 것으로 기대된다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.143-148
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• 2006

The goal of this paper is to analyze, through simulations and experiments, GNSS interference mitigation performance under various types of antenna structures against wideband and narrowband interferences using spatial-temporal adaptive signal processing (STAP) techniques. The STAP approach, which combines spatial and temporal processing, is a viable means of GNSS array signal processing that enhancing the desired signal quality and providing protection against interference. In this paper, we consider four types of 3D antenna array structure - Uniform Linear Array (ULA), Uniform Rectangular Array (URA), Uniform Circular Array (UCA), and the Single-Ring Cylindrical Array (SRCA) under an interference environment. Analytical evaluation and simulations are performed to investigate the system performance. This is followed by simulation GPS orbits in interfered environment are used to evaluate the STAP performance. Furthermore, experiments using a 2x2 URA hardware simulator data show that with the removal of wideband and narrowband interference through the STAP techniques, the signal tracking performance can be enhanced.

• 한국농공학회논문집
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• 제62권1호
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• pp.51-60
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• 2020

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.

• Journal of the Korean Data and Information Science Society
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• 제27권5호
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권3호
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• pp.749-761
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• 2014

Improving spectrum utilization efficiency is a fundamental goal of dynamic spectrum access technology. The definition of spectrum holes determines how to detect and exploit them. Current definitions of spectrum holes are ineffective in exploiting spatial-temporal spectrum holes. In this paper, a novel definition of spectrum holes is proposed, in which throughput loss indicates the impact of secondary users on primary users. The definition specifies spectrum holes, unifies the impact of secondary users on primary users and is effective exploiting spatial-temporal spectrum holes. Theoretical analysis and numerical simulations show that the new definition proposed in this paper significantly improves the spectrum utilization efficiency.

• 대한공간정보학회지
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• 제19권4호
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• pp.3-12
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• 2011

침전물 변화의 이해는 수질모니터링에 있어서 중요한 요소이다. 수질 변수는 시공간에 의해 변하므로 시간분석이나 공간분석 한 가지만으로는 모형화하거나 명확히 설명하기 어렵다. 본 연구에서는 1985년부터 2005년까지 메콩강 하류 유역에서 수집된 침전물 기록과 공간 자료를 근거로 온도, 페하 수준 및 용존산소 수준을 파악하고, 역거리가중법을 이용하여 시공간 경향과 시각 분석을 평가하고자 한다. 그 결과, 온도와 페하의 최대값은 이 기간 동안 큰 변화없이 나타났고 최대 용존산소는 2002년까지 점점 증가하여왔다. 최소 페하와 용존산소는 이 기간 동안 불안정한 경향으로 변화하였다. 역거리가중법 보간을 이용한 경향 분석에서는 연구 지역의 전반적인 수온이 계속 증가했다는 것을 보여주었고, 페하는 1993년부터 2005년 동안 감소하는 경향을 나타냈다. 용존산소농도는 1989년 이후 증가하였고 2002년부터는 많이 확산되지 않았다.

• 수산해양기술연구
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• 제56권4호
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• pp.322-339
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• 2020

Temporal and spatial fluctuations of surface water temperature in Yeosu Bay for the period from 2010 to 2011 were studied using the data from temperature monitoring buoys deployed at 32 stations in the south coast of Korea. Temperatures in the northern part of the bay are higher in summer and lower in winter than in the southern part of the bay. The lowest and highest temperature of the annual mean are found at the eastern coast of POSCO and at the west of Dae Island, respectively. Cold water masses appear at estuarine area when the discharge of Sumjin river is affluent. Amplitude of temperature fluctuation whose period is less than semi-diurnal is largest at Hadong coast and around Dae Island. Spectral analysis of surface water temperature shows a significant peak at a periodic fluctuation of 0.5 to 24 days and about 15-day period of predominant fluctuation is most frequent in Yeosu Bay. From the cross-correlation analysis of temperature fluctuations, Yeosu Bay can be classified into six areas; the south area affected by South Sea of Korea, the mixed area in the center of the bay, the estuarine area affected by river discharge at the north of the bay, the hot waste water area near Hadong coast, the area around Dae Island and the area near Noryang Channel affected by the water in Jinju Bay, respectively.