• Progress in Medical Physics
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• v.23 no.4
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• pp.252-260
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• 2012

The reduction of radiation dose from x-ray is a main concern in computed tomography (CT) imaging due to the side-effect of the dose on human body. Recently, the various methods for dose reduction have been studied in CT and one of the method is a iterative reconstruction based on total variation (TV) minimization at few-views data. In this paper, we evaluated the image quality between total variation (TV) minimization algorithm and Feldkam-Davis-kress (FDK) algorithm in micro computed tomography (CT). To evaluate the effect of TV minimization algorithm, we produced a cylindrical phantom including contrast media, water, air inserts. We can acquire maximum 400 projection views per rotation of the x-ray tube and detector. 20, 50, 90, 180 projection data were chosen for evaluating the level of image restoration by TV minimization. The phantom and mouse image reconstructed with FDK algorithm at 400 projection data used as a reference image for comparing with TV minimization and FDK algorithm at few-views. Contrast-to-noise ratio (CNR), Universal quality index (UQI) were used as a image evaluation metric. When projection data are not insufficient, our results show that the image quality of reconstructed with TV minimization is similar to reconstructed image with FDK at 400 view. In the cylindrical phantom study, the CNR of TV image was 5.86, FDK image was 5.65 and FDK-reference was 5.98 at 90-views. The CNR of TV image 0.21 higher than FDK image CNR at 90-views. UQI of TV image was 0.99 and FDK image was 0.81 at 90-views. where, the number of projection is 90, the UQI of TV image 0.18 higher than FDK image at 90-views. In the mouse study UQI of TV image was 0.91, FDK was 0.83 at 90-views. the UQI of TV image 0.08 higher than FDK image at 90-views. In cylindrical phantom image and mouse image study, TV minimization algorithm shows the best performance in artifact reduction and preserving edges at few view data. Therefore, TV minimization can potentially be expected to reduce patient dose in clinics.

• Journal of Life Science
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• v.24 no.9
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• pp.1030-1038
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• 2014

Platelet products are used to treat hemorrhagic or platelet dysfunction diseases. Plateletpheresis involves collecting the platelet components of blood using an apheresis blood-collection system. Various indicators are available for evaluating the qualities of the apheresis platelets. The productivity of platelet collection is evaluated through both the collection efficiency and collection rates. Platelet storage quality can be evaluated in vitro using several indicators, including visual appearance, metabolic activities, volume, platelet count, white blood cell count, microparticles, and various platelet activation markers. Platelet activation markers have been used as indicators of storage quality in various studies. Post-transfusion platelet quality can be evaluated based on the corrected count increment and the percentage of platelet recovery. Although various studies have investigated the aspects of plateletpheresis, no article has systemically presented assessments of the platelet products obtained from different plateletpheresis devices. The present study provides a review of plateletpheresis, including the specifics of the process, the types of devices employed, the platelet quality, the overall efficacy, and the evaluation indicator qualities. Furthermore, the differences in functionality among the different apheresis devices are discussed. Although adverse reactions to the citrate anti-coagulant have been reported, apheresis processing may provide a safer option for donors who are at a high risk for presyncopal or syncopal reactions related to whole blood collection.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.701-715
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• 2020

This study compared several reference evapotranspiration estimated using eight methods such as FAO-56 Penman-Monteith (FAO PM), Hamon, Hansen, Hargreaves-Samani, Jensen-Haise, Makkink, Priestley-Taylor, and Thornthwaite. In addition, by analyzing the monthly deviations of the results by the FAO PM and the remaining seven methods, monthly optimized correction coefficients were derived and the improvement effect was evaluated. These methods were applied to 73 automated synoptic observation system (ASOS) stations of the Korea Meteorological Administration, where the climatological data are available at least 20 years. As a result of evaluating the reference evapotranspiration by applying the default coefficients of each method, a large fluctuation happened depending on the method, and the Hansen method was relatively similar to FAO PM. However, the Hamon and Jensen-Haise methods showed more large values than other methods in summer, and the deviation from FAO PM method was also large significantly. When comparing based on the region, the comparison with FAO PM method provided that the reference evapotranspiration estimated by other methods was overestimated in most regions except for eastern coastal areas. Based on the deviation from the FAO PM method, the monthly correction coefficients were derived for each station. The monthly deviation average that ranged from -46 mm to +88 mm before correction was improved to -11 mm to +1 mm after correction, and the annual average deviation was also significantly reduced by correction from -393 mm to +354 mm (before correction) to -33 mm to +9 mm (after correction). In particular, Hamon, Hargreaves-Samani, and Thornthwaite methods using only temperature data also produced results that were not significantly different from FAO PM after correction. It can be also useful for forecasting long-term reference evapotranspiration using temperature data in climate change scenarios or predicting evapotranspiration using monthly or seasonal temperature forecasted values.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.81-90
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• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.504-515
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• 2021

To examine the relationship between environmental factors influencing the habitat of Aconitum austrokoreense Koidz., this study employed the MexEnt model to evaluate 21 environmental factors. Fourteen environmental factors having an AUC of at least 0.6 were found to be the age of stand, growing stock, altitude, topography, topographic wetness index, solar radiation, soil texture, mean temperature in January, mean temperature in April, mean annual temperature, mean rainfall in January, mean rainfall in August, and mean annual rainfall. Based on the response curves of the 14 descriptive factors, Aconitum austrokoreense Koidz. on the Baekun Mountain were deemed more suitable for sites at an altitude of 600 m or lower, and habitats were not significantly affected by the inclination angle. The preferred conditions were high stand density, sites close to valleys, and distribution in the northwestern direction. Under the five-age class system, the species were more likely to be observed for lower classes. The preferred solar radiation in this study was 1.2 MJ/m². The species were less likely to be observed when the topographic wetness index fell below the reference value of 4.5, and were more likely observed above 7.5 (reference of threshold). Soil analysis showed that Aconitum austrokoreense Koidz. was more likely to thrive in sandy loam than clay. Suitable conditions were a mean January temperature of - 4.4℃ to -2.5℃, mean April temperature of 8.8℃-10.0℃, and mean annual temperature of 9.6℃-11.0℃. Aconitum austrokoreense Koidz. was first observed in sites with a mean annual rainfall of 1,670- 1,720 mm, and a mean August rainfall of at least 350 mm. Therefore, sites with increasing rainfall of up to 390 mm were preferred. The area of potential habitats having distributive significance of 75% or higher was 202 ha, or 1.8% of the area covered in this study.

• Journal of vocational education research
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• v.36 no.1
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• pp.77-103
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• 2017

The purposes of this study are 1) to analyse the importance and performance of the success factors in steps of Formation process Of Cooperation NetWork(FoCNW) of educational institutions and businesses, and 2) to draw the success factors that need improvement. To achieve these purposes a survey research was conducted with a group of 1,098 (professors, teachers and workers in charge of cooperation at universities, technical colleges, vocational high schools and businesses which are equipped with a cooperation system), and 339 questionnaires were analyzed. The major results of the study are as follows. Firstly, while cooperation workers showed high recognition on the importance of success factors in steps of FoCNW, their performance of those factors was relatively low. Secondly, both the recognition of importance and performance of success factors in steps of FoCNW was higher in educational institutions than in businesses. Thirdly, the success factors in need of improvements from both educational institutions and businesses are 'collecting outer information and consulting' and 'publicizing cooperation competency', 'setting cooperative activities (programs) and contents of agreements', 'managing cooperation quality formally', 'drawing plans for sustainable cooperation improvement' and 'diffusing cooperation network'. The success factors in need of improvements from educational institutions are 'perceiving necessity of and forming consensus on cooperation' and 'deciding and supporting the worker in charge of cooperation', and 'participating and sharing of organization members'. The success factors in need of improvements from businesses are 'deciding goals and performance strategies', 'developing mutual understanding and checking possibility of cooperation with potential partners', and 'evaluating cooperation activities and their outcomes and providing feedback' and 'adjusting contents of agreements and deciding whether to maintain cooperation'. Therefore, efforts from each partner to improve those factors and support from related organizations are necessary.

• Korean Journal of Community Nutrition
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• v.24 no.3
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• pp.232-244
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• 2019

Objectives: This study evaluated the nutritional status and prevalence of metabolic syndrome of the people who participated in the KNHANES according to the number of household members. They were assessed by using information from the 2013~2014 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: A total of 6,088 persons aged 19 years and over participated in 2013~2014 KNHANES, and they were classified into three groups according to the number of household members (single-person, two-person, three-person & over). The dietary behavior, nutritional status, health-related factors and the prevalence of metabolic syndrome of the subjects were investigated with using information from the survey questionnaires of KNHANES. The nutrient intake data of the subjects were obtained by the 24-hour recall method and this was analyzed for evaluating the nutrition adequacy ratio and the index of nutritional quality. The prevalence of metabolic syndrome among the subjects, and according to the study groups, was estimated using the blood and physical measurement data of the subjects. Results: As for EQ-5D index available for all the health states generated by the EQ-5D descriptive system, the single-person household member was the lowest among all the household types. The index of nutrition quality for protein, crude fiber, calcium, phosphorus, potassium, riboflavin and vitamin C in the single-person household was lower than that of the two-person or the three-person and over households (p<0.001). The mean adequacy ratio of single-person households was significantly decreased compared with that of the other types of households (p<0.001). The prevalence of metabolic syndrome was higher in the single-person households than that in the multiple-person households (p<0.001). Conclusions: These results showed that dietary behaviors, nutrition status and health status might be influenced by the number of household members. The results from this study would be useful for improving Korean people's dietary life and health status by implementing evidence-based, specialized intervention for the members of diverse types of households.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.89-96
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• 2019

This study was conducted to investigate 106 grassland farms in six provinces including Chungcheongbuk-do, Gangwon-do, Gyeonggi-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeju-do, and Jeollanam-do to present their problems and causes by surveying the actual state of grassland farms during three years(2014~2016). The grassland survey was divided into three categories; used as the perennial grasses and annual forage crops (Complied with Grassland Act), not used as the perennial grasses and annual forage crops (Not complied with Grassland Act) and failed to meet the farmer and some items are missing or inaccurate (Insufficient contents). Among the surveyed grassland farm, 68 farms (64.2 %) were complied with Grassland Act but 30 farms (28.3 %) were not complied with Grassland Act. Especially, the 8 farms (26.7 %) not complied with Grassland Act used the grassland as other purposes such as tree growing, golf club and swine farm etc.. Therefore, strict on-site investigation by local governments is required to prevent the grassland from being used by illegal purposes. And there's a strong likelihood that 5 farms (62.5 %) avoided the survey violate the positive law. Grassland grades used by the local administrative agencies were not influenced by the factors affecting the yield (existence and non-existence of overseeding and fertilization by grassland grade, soil pH and organic matter content). This results suggest that there is a fundamental problem on the current grassland grade system based on the yield and the irregular time of investigation and lack of on-site investigation are another causes for inaccurate grassland grade. Therefore, the new method evaluating grassland grades which is not based on yield and the thorough on-site investigation by local administrative agencies are necessary when the grassland grade is evaluated.