• Journal of The Korean Society of Integrative Medicine
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• v.7 no.4
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• pp.265-272
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• 2019

Purpose : Excessive computer use frequently results in musculoskeletal disorders of the neck and shoulder such as forward head posture (FHP). The purpose of this study was to investigate effects of neck and shoulder exercise program on spino-pelvic alignment and the correlation between change in head and neck posture and spino-pelvic alignment in FHP. Methods : The study included 44 participants with FHP. The participants performed the exercise for correction of FHP 2-3 times a week for 4 weeks. We examined whole spine X-ray images in the lateral standing position with both arms crossed. We measured anterior head translation distance (AHT), craniovertebral angle (CVA), cervical lordosis (CL), thoracic kyphosis (TK), lumbosacral lordosis (LSL), sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI) of the subjects. The association between change in AHT and each spino-pelvic parameter was also subjected to Pearson's correlation coefficient analysis. Results : There were statistically significant differences before and after exercise in the parameters of AHT, CVA, and SS (p<.05). Significant negative correlation was observed between the change in AHT and CVA (r=-.768, p<.001), and CL (r=-.388, p<.05). There was significant positive correlation between the change in AHT and SS (r=.328, p<.05), and PI (r=.333, p<.05). However, no significant correlation was observed in change in AHT with that of TK, LSL, and PT. Conclusion : Based on the above results, we conclude that there is a relationship between change in AHT, which is a parameter associated with forward displacement of the head, and that of CVA, CL, SS, and PI after exercise in cases of FHP.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1227-1241
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• 2012

In this study, a novel water surface detection method was proposed. In the method water surface is detected by analysis on correlation coefficients obtained from rectangular control areas of the same vertical position in two successive images including both water surface and staff gauge. Four methods respectively based on threshold, peak, slope and variance ratio, are used to identify water surface from vertical distribution of correlation coefficient. In addition, swaying correction algorithm and statistical filtering are applied to minimize outliers caused by positional image mismatch. Images taken from 28 different sites during low flow were tested to evaluate the method. Mean relative error to eye measurement was approximately from 3.4 to 5.7 cm. As long as water surface moves, this method can be used to improve image stage gauge by supplementing the previous water surface detection method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.113-122
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• 2017

Natural disasters caused by climate change are increasing globally. There are few studies on the quantitative analysis methods for predicting damages in the island area due to sea level rise. Therefore, it is necessary to study the damage prediction analysis method using the GIS which can quantitatively analyze. In this paper, we analyze the cause and status of sea level rise, quantify the vulnerability index, establish an integrated terrestrial modeling method of the ocean and land, and establish a method of analyzing the damage area and damage scale due to sea level rise using GIS and the method of making the damage prediction figure was studied. In order to extract the other affected areas to sea level rise are apart of the terrain model is generated by one requires a terrain modeling of target areas are offshore and vertical reference system differences in land, found the need for correction by a tidal observations and geoid model there was. Grading of terrain, coastline erosion rate, coastal slope, sea level rise rate, and even average by vulnerable factors due to sea level rise indicates that quantitative damage prediction is possible due to sea level rise in the island area. In the case of vulnerable areas extracted by GIS, residential areas and living areas are concentrated on the coastal area due to the nature of the book area, and field survey shows that coastal changes and erosion are caused by sea level rise or tsunami.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.227-234
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• 2009

In this study, cross correlations among sample data at each site are calculated to obtain the asymptotic cross correlations among probability weighted moments at each site using Monte Carlo simulation. As a result, the relations between the asymptotic cross correlations among probability weighted moments and the inter-site dependence among sample data at each site are nearly a linear relation with slope 1. The smaller ratio of concurrent data size to entire sample size is, the weaker the relationship grows. Simple power function which the correction term in power function accounts for the differences of the sample size between two sites was fitted to each case to estimate the parameter. It is noted that this result can be used in the various researches which include the estimation of the variance of quantile considering cross correlations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.111-118
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• 2002

These days, surveying instruments are developing rapidly and the precision is improving continuously. The building of three dimensional terrains of high precision are possible and the calculation of the areas or the volumes have high precision due to the development of the technique of the spatial information system using computer. But actually, in construction site they calculate two-dimensional area using the traditional method, plate table surveying, planimeter, and then get three-dimensional area through multiplying two-dimensional area by the slope correction factor. In this study, we show the defect and inefficiency of the calculation of area by the traditional methods and survey the area with Electric Distance Measurement and GPS instrument. With this data, we made the three dimensional terrain model and calculated two-dimensional area, three-dimensional area. After that, we compared areas that calculated by algorithm of triangulated irregular network and analysis of grid method with standard area that calculated by the traditional method. Finally, this paper suggested more effective and precious method in calculating three-dimensional area.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.302-315
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• 2018

Highly non-linear electro-optical transfer function of the Perceptual Quantizer was approximated by a truncated Taylor series, resulting in a closed form solution for luma adjustment. This previous solution is fast and quite suitable for the hardware implementation of luma adjustment, but the approximation error becomes relatively large in the range of 600~3,900 cd/m2 linear light. In order to reduce such approximation error, we propose a new linear model, for which a correction is performed on the position and the slope of line based on the scope of approximation. In order to verify the approximation capability of the proposed linear model, a comparative study on the luma adjustment schemes was conducted using various high dynamic range test video sequences. Via the comparative study, we identified a significant performance enhancement over the previous fast luma adjustment scheme, where a 4.65dB of adjusted luma t-PSNR gain was obtained for a test sequence having a large portion of saturated color pixels.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.721-730
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• 1999

A Grid-based daily evapotranspiration(ET) prediction model which calculates temporal and spatial ET with a complementary relationship of Morton(1983) was developed. The model was programmed by C-language and uses ASCII formatted map data of DEM(Digital Elevation Model) and land use. Daily ET within the watershed is calculated and the results of temporal variations and spatial distributions of ET are presented by using GRASS(Geographic Resources Analysis Support System). To verify the applicability of the model, it was applied to the part of Bocheong stream basin (76.5$\textrm{km}^2$) located in the upstream of Dacheong Dam watershed. The result shows that the estimated evapotranspiration in 1995 was 766.1mm and 22% increased after correction radiation for slope and area.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.77-84
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• 2024

In this paper, we propose a method for accurately and rapidly detecting defects in wire harnesses by utilizing computer vision to calculate six crucial measurement values: the length of crimped terminals, the dimensions (width) of terminal ends, and the width of crimped sections (wire and core portions). We employ Harris corner detection to locate object positions from two types of data. Additionally, we generate reference points for extracting measurement values by utilizing features specific to each measurement area and exploiting the contrast in shading between the background and objects, thus reflecting the slope of each sample. Subsequently, we introduce a method using the Euclidean distance and correction coefficients to predict values, allowing for the prediction of measurements regardless of changes in the wire's position. We achieve high accuracy for each measurement type, 99.1%, 98.7%, 92.6%, 92.5%, 99.9%, and 99.7%, achieving outstanding overall average accuracy of 97% across all measurements. This inspection method not only addresses the limitations of conventional visual inspections but also yields excellent results with a small amount of data. Moreover, relying solely on image processing, it is expected to be more cost-effective and applicable with less data compared to deep learning methods.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.