In this paper through Honam high-speed railroad which is planned with the north and south axis, we will verify the feasibility of the coordinate conversion using railroad control points after regarding current planned-railroad as the linear central axises. From analysis, distortion of Y axis varies 21cm to 40cm diminishing to a gentle straight line, distortion of X axis varies 14cm to 29cm. Through a revision, the deviation value between the coordinates were 6mm to 9mm and it satisfied the allowable error of national geographic information institute which is following ITRF (International Terrestrial Reference Frame) and cadastral boundary survey(10cm). consequently the coordinate conversion is possible using railroad control points as common control points.
Underwater seismic refraction with advanced interpretation approaches makes important contributions to shallow marine exploration and geotechnical investigations in Australia's coastal areas. A series of case studies are presented to demonstrate the recent applications of continuous and static USR methods to river crossing and port infrastructure projects at various sites around Australia. In Sydney, static underwater seismic refraction (USR) with bottom-placed receivers and borehole seismic imaging assisted the development of improved geotechnical models that reduced construction risk for a tunnel crossing of the Lane Cove River. In Melbourne, combining conventional boomer reflection and continuous USR with near-bottom sources and receivers improved the definition of a buried, variably weathered basalt flow and assisted dredging assessment for navigation channel upgrades at Geelong Ports. Sand quality assessment with continuous USR and widely spaced borehole information assisted commercial decisions on available sand resources for the reclamation phase of development at the Port of Brisbane. Buried reefs and indurated layers occur in Australian coastal sediments with the characteristics of laterally limited, high velocity, cap layers within lower velocity materials. If these features are not recognised then significant error in depth determination to deeper refractors can occur. Application of advanced refraction inversion using wavefront eikonal tomography to continuous USR data obtained along the route of a proposed offshore pipeline near Fremantle allowed these layers and the underlying bedrock refractor to be accurately imaged. Static USR and the same interpretation approach was used to image the drowned granitic regolith beneath sediments and indurated layers in the northern area of Western Australia at a proposed new berthing site where deep piling was required. This allowed preferred piling sites to be identified, reducing overall pile lengths. USR can be expected to find increased application to shallow marine exploration and geotechnical investigations in Australia's coastal areas as economic growth continues and improved interpretation methods are developed.
Background: Breast cancer patients experience a variety of altered appearance - such as loss or disfigurement of breasts, discolored skin, and hair loss - which result in psychological distress that affect their quality of life. This study aims to evaluate the impact of socioeconomic status on the altered appearance distress, body image, and quality of life among Korean breast cancer patients. Materials and Methods: A cross-sectional survey was conducted at advocacy events held at 16 different hospitals in Korea. Subjects were eligible to participate if they were 18 years of age or older, had a histologically confirmed diagnosis of breast cancer, had no evidence of recurrence or metastasis, and had no psychological problems at the time of the survey. Employment status, marital status, education, and income were assessed for patient socioeconomic status. Altered appearance distress was measured using the NCI's cancer treatment side effects scale; body image and quality of life were measured by the EORTC QLC-C30 and BR23. Means and standard deviations of each outcome were compared by socioeconomic status and multivariate linear regression models for evaluating the association between socioeconomic status and altered appearance distress, body image, and quality of life. Results: A total of 126 breast cancer patients participated in the study; the mean age of participants was 47.7 (SD=8.4). Of the total, 83.2% were married, 85.6% received more than high school education, 35.2% were employed, and 41% had more than $3000 in monthly household income. About 46% had mastectomy, and over 30% were receiving either chemotherapy or radiation therapy at the time of the survey. With fully adjusted models, the employed patients had significantly higher altered appearance distress (1.80 vs 1.48; p<0.05) and poorer body image (36.63 vs 51.69; p<0.05) compared to the patients who were unemployed. Higher education (10.58, standard error (SE)=7.63) and family income (12.88, SE=5.08) was positively associated with better body image after adjusting for age, disease stage at diagnosis, current treatment status, and breast surgery type. Similarly, patients who were married and who had higher education had better quality of life were statistically significant in the multivariate models. Conclusions: Socioeconomic status is significantly associated with altered appearance distress, body image, and quality of life in Korean women with breast cancer. Patients who suffer from altered appearance distress or lower body image are much more likely to experience psychosocial, physical, and functional problems than women who do not, therefore health care providers should be aware of the changes and distresses that these breast cancer patients go through and provide specific information and psychosocial support to socioeconomically more vulnerable patients.
The Journal of the Society of Korean Medicine Diagnostics
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v.12
no.1
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pp.42-62
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2008
Objectives: It is well known that some parameters of the photoplethysmogram (PPG) acquired by time domain contour analysis can be used as markers of vascular aging. But the previous studies that have been performed for frequency domain analysis of the PPG to date have provided only restrictive and fragmentary information. The aim of the present investigation was to determine whether the harmonics extracted from the PPG using a fast Fourier transformation could be used as an index of vascular aging. Methods: The PPG was measured in 600 recruited subjects for 30 second durations, To grasp the gross age-related change of the PPG waveform, we grouped subjects according to gender and age and averaged the PPG signal of one pulse cycle. To calculate the conventional indices of vascular aging, we selected the 5-6 cycles of pulse that the baseline was relatively stable and then acquired the coordinates of the inflection points. For the frequency domain analysis we performed a power spectral analysis on the PPG signals for 30 seconds using a fast Fourier transformation and dissociated the harmonic components from the PPG signals. Results: A final number of 390 subjects (174 males and 216 females) were included in the statistical analysis. The normalized power of the harmonics decreased with age and on a logarithmic scale reduction of the normalized power in the third (r=-0.492, P<0.0001), fourth (r=-0.621, P<0.0001) and fifth harmonic (r=-0.487, P<0.0001) was prominent. From a multiple linear regression analysis, Stiffness index, reflection index and corrected up-stroke time influenced the normalized power of the harmonics on a logarithmic scale. Conclusions: The normalized harmonic power decreased with age in healthy subjects and may be less error prone due to the essential attributes of frequency domain analysis. Therefore, we expect that the normalized harmonic power density can be useful as a vascular aging marker.
Korean Journal of Agricultural and Forest Meteorology
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v.11
no.2
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pp.72-78
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2009
The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.
The present survey was conducted to provide basic information on automatic milking system (AMS) in relation to purchase motive, milk yield and quality, customer satisfaction, difficulties of operation and customer suggestions, etc. Purchase motives of AMS were insufficient labor (44%), planning of dairy experience farm (25%), better performance of high yield cows (19%) and others (6%), respectively. Average cow performance after using AMS was 30.9l/d for milk yield, 3.9% for milk fat, 9,100/ml for bacterial counts. Sixty-eight percentage of respondents were very positive in response to AMS use for their successors but 18% were negative. The AMS operators were owner (44%), successor (44%), wife (6%) and company worker (6%), respectively. The most difficulty (31%) in using AMS was operating the system and complicated program manual. The rate of response to system error and breakdown was 25%. The reasons for culling cow after using AMS were mastitis (28%), reproduction failure (19%), incorrect teat placement (12%), metabolic disease (7%) and others (14%), respectively. Fifty-six percentages of the respondents made AMS maintenance contract and 44% did not. Average annual cost of the maintenance contract was 6,580,000 won. Average score for AMS satisfaction measurement (1 to 5 range) was 3.2 with decrease of labor cost 3.7, company A/S 3.6, increase of milk yield 3.2 and decrease of somatic cell count 2.8, respectively. Suggestions for the higher efficiency in using AMS were selecting cows with correct udder shape and teat placement, proper environment, capital and land, and attitude for continuous observation. Systematic consulting was highly required for AMS companies followed by low cost for AMS setup and systematization of A/S.
This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.
Korean Journal of Agricultural and Forest Meteorology
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v.19
no.1
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pp.19-26
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2017
Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.
Korean Journal of Agricultural and Forest Meteorology
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v.18
no.4
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pp.233-241
/
2016
Experiments were carried out to quantify the topographic effects on attenuation of sunshine in complex terrain and the results are expected to help convert the coarse resolution sunshine duration information provided by the Korea Meteorological Administration (KMA) into a detailed map reflecting the terrain characteristics of mountainous watershed. Hourly shaded relief images for one year, each pixel consisting of 0 to 255 brightness value, were constructed by applying techniques of shadow modeling and skyline analysis to the 3m resolution digital elevation model for an experimental watershed on the southern slope of Mt. Jiri in Korea. By using a bimetal sunshine recorder, sunshine duration was measured at three points with different terrain conditions in the watershed from May 15, 2015 to May 14, 2016. The brightness values of the 3 corresponding pixel points on the shaded relief map were extracted and regressed to the measured sunshine duration, resulting in a brightness-sunshine duration response curve for a clear day. We devised a method to calibrate this curve equation according to sky condition categorized by cloud amount and used it to derive an empirical model for estimating sunshine duration over a complex terrain. When the performance of this model was compared with a conventional scheme for estimating sunshine duration over a horizontal plane, the estimation bias was improved remarkably and the root mean square error for daily sunshine hour was 1.7hr, which is a reduction by 37% from the conventional method. In order to apply this model to a given area, the clear-sky sunshine duration of each pixel should be produced on hourly intervals first, by driving the curve equation with the hourly shaded relief image of the area. Next, the cloud effect is corrected by 3-hourly 'sky condition' of the KMA digital forecast products. Finally, daily sunshine hour can be obtained by accumulating the hourly sunshine duration. A detailed sunshine duration distribution of 3m horizontal resolution was obtained by applying this procedure to the experimental watershed.
KIPS Transactions on Software and Data Engineering
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v.4
no.11
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pp.509-520
/
2015
College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.
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