• Journal of Chest Surgery
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• v.40 no.12
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• pp.817-824
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• 2007

Background: There are two choices for heart valve replacement-the use of a tissue valve and the use of a mechanical valve. Using a tissue valve, additional surgery will be problematic due to valve degeneration. If the risk of additional surgery could be reduced, the tissue valve could be more widely used. Therefore, we analyzed the risk factors and mortality of patients undergoing repeated heart valve replacement and primary replacement. Material and Method: We analyzed 25 consecutive patients who underwent repeated heart valve replacement and 158 patients who underwent primary heart valve replacement among 239 patients that underwent heart vale replacement in out hospital from January 1995 to December 2004. Result: There were no differences in age, sex, and preoperative ejection fraction between the repeated valve replacement group of patients and the primary valve replacement group of patients. In the repeated valve replacement group, the previously used artificial valves were 3 mechanical valves and 23 tissue valves. One of these cases had simultaneous replacement of the tricuspid and aortic valve with tissue valves. The mean duration after a previous operation was 92 months for the use of a mechanical valve and 160 months for the use of a tissue valve. The mean cardiopulmonary bypass time and aortic cross clamp time were 152 minutes and 108 minutes, respectively, for the repeated valve replacement group of patients and 130 minutes and 89 minutes, respectively, for the primary valve replacement group of patients. These results were statistically significant. The use of an intra aortic balloon pump (IABP) was required for 2 cases (8%) in the repeated valve replacement group of patients and 6 cases (3.8%) in the primary valve replacement group of patients. An operative death occurred in one case (4%) in the repeated valve replacement group of patients and occurred in nine cases (5.1%) in the primary valve replacement group of patients. Among postoperative complications, the need for mechanical ventilation over 48 hours was different between the two groups. The mean follow up period after surgery was $6.5{\pm}3.2$ years. The 5-year survival of patients in the repeated valve replacement group was 74% and the 5-year survival of patients in the primary valve replacement group was 95%. Conclusion: The risk was slightly increased, but there was little difference in mortality between the repeated and primary heart valve replacement group of patients. Therefore, it is necessary to reconsider the issue of avoiding the use of a tissue valve due to the risk of additional surgery, and it is encouraged to use the tissue valve selectively, which has several advantages over the use of a mechanical valve. In the case of a repeated replacement, however, the mortality rate was high for a patient whose preoperative status was not poor. A proper as sessment of cardiac function and patient status is required after the primary valve replacement. Subsequently, a secondary replacement could then be considered.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.5
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• pp.536-544
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• 2001

Three harmful algal bloom species with similar morphology, Cochlodinium polykrikoides, Gyodinium impudicum and Gymodinium catenatum have damaged to aquatic animals or human health by either making massive blooms or intoxication of shellfishes in a food chain. Eco-physiological and hydrodynamic studies on the harmful algae offer useful informations in the understanding their bloom mechanism by giving promising data for the prediction and modelling of harmful algal blooms event. Thus, we studied the abundance of these species in the coastal area of South Sea of Korea and their effects of temperature, salinity, irradiance and nutrient on the growth for the isolates. The timing for initial appearance of the three species around the coastal area of Namhaedo, Narodo and Wando was between Bate July and late August in 1999 when water temperature ranged from $22.8^{\circ}C\;to\;26.5^{\circ}C$ Vegetative cells of C. polykrikoides and G. impudicum were abundant until late September when water temperature had been dropped to less than $23^{\circ}C$. By contrast, vegetative cell of G. catenatum disappeared before early September, showing shorter period of abundance than the other two species in the South Sea. Both G. impudicum and G. catenatum revealed comparatively low density with a maximal cell density of 3,460 cells/L and 440 cells/L, respectively without making any bloom, while C. polykrikoides made massive blooms with a maximal cell density more than $40\times10^6$cells/L, The three species showed a better growth at the relatively higher water temperature ranging from 22 to $28^{\circ}C$ with their maximal growth rate at $25^{\circ}C$ in culture, which almost corresponded with the water temperature during the outbreak of C. polykrikoides in the coastal area of South Sea. Also, they all showed a relatively higher growth at the salinity from 30 to $35\%$. Specially, G. impudicum showed the euryhalic characteristics among the species, On the other hand, growth rate of G. catenatum decreased sharply with the increase of water temperature at the experimental ranges more than $35\%$. The higher of light intensities showed the better growth rates for the three species, Moreover, C. polykrikoides and G. impudirum continued their exponential growth even at 7,500 lux, the highest level of light intensity in the experiment, Therefore, It is assumed that C. polykrikoides has a physiological capability to adapt and utilize higher irradiance resulting in the higher growth rate without any photo inhibition response at the sea surface where there is usually strong irradiance during its blooming season. Although C. poiykikoides and G. impudicum continued their linear growth with the increase of nitrate ($NO_3^-$) and ammonium ($NH_4^-$) concentrations at less than the $40{\mu}M$, they didn't show any significant differences in growth rates with the increase of nitrate and ammonium concentrations at more than $40{\mu}M$, signifying that the nitrogen critical point for the growth of the two species stands between 13.5 and $40{\mu}M$. Also, even though both of the two species continued their linear growth with the increase of phosphate ($PO_4^{2-}$) concentrations at less than the $4.05{\mu}M$, there were no any significant differences in growth rates with the increase of phosphate concentrations at more than $4.05{\mu}M$, signifying that the phosphate critical point for the growth of the two species stands between 1.35 and $4.05{\mu}M$. On the other hand, C. polykrikoides has made blooms at the oligotrophic environment near Narodo and Namhaedo where the concentration of DIN and DIP are less than 1.2 and $0.3{\mu}M$, respectively. We attributed this phenomenon to its own ecological characteristics of diel vertical migration through which C. polykrikoides could uptake enough nutrients from the deep sea water near bottom during the night time irrespective of the lower nutrient pools in the surface water.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.47-55
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• 2015

Recently, the environment of a hospital information system is a trend to combine various SMART technologies. Accordingly, various smart devices, such as a smart phone, Tablet PC is utilized in the medical information system. Also, these environments consist of various applications executing on heterogeneous sensors, devices, systems and networks. In these hospital information system environment, applying a security service by traditional access control method cause a problems. Most of the existing security system uses the access control list structure. It is only permitted access defined by an access control matrix such as client name, service object method name. The major problem with the static approach cannot quickly adapt to changed situations. Hence, we needs to new security mechanisms which provides more flexible and can be easily adapted to various environments with very different security requirements. In addition, for addressing the changing of service medical treatment of the patient, the researching is needed. In this paper, we suggest a dynamic approach to medical information systems in smart mobile environments. We focus on how to access medical information systems according to dynamic access control methods based on the existence of the hospital's information system environments. The physical environments consist of a mobile x-ray imaging devices, dedicated mobile/general smart devices, PACS, EMR server and authorization server. The software environment was developed based on the .Net Framework for synchronization and monitoring services based on mobile X-ray imaging equipment Windows7 OS. And dedicated a smart device application, we implemented a dynamic access services through JSP and Java SDK is based on the Android OS. PACS and mobile X-ray image devices in hospital, medical information between the dedicated smart devices are based on the DICOM medical image standard information. In addition, EMR information is based on H7. In order to providing dynamic access control service, we classify the context of the patients according to conditions of bio-information such as oxygen saturation, heart rate, BP and body temperature etc. It shows event trace diagrams which divided into two parts like general situation, emergency situation. And, we designed the dynamic approach of the medical care information by authentication method. The authentication Information are contained ID/PWD, the roles, position and working hours, emergency certification codes for emergency patients. General situations of dynamic access control method may have access to medical information by the value of the authentication information. In the case of an emergency, was to have access to medical information by an emergency code, without the authentication information. And, we constructed the medical information integration database scheme that is consist medical information, patient, medical staff and medical image information according to medical information standards.y Finally, we show the usefulness of the dynamic access application service based on the smart devices for execution results of the proposed system according to patient contexts such as general and emergency situation. Especially, the proposed systems are providing effective medical information services with smart devices in emergency situation by dynamic access control methods. As results, we expect the proposed systems to be useful for u-hospital information systems and services.

• Applied Biological Chemistry
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• v.16 no.1
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• pp.18-30
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• 1973

The flag and lower leaves (4th or 5th) of rice plant from the field of NPK simple trial and from three low productive area were analyzed in order to find out certain diagnostic criteria of nutritional status at harvest. 1. Nutrient contents in the leaves from no fertilizer, minus nutrient and fertilizer plots revealed each criterion for induced deficiency (severe deficient case induced by other nutrients), deficiency (below the critical concentration), insufficiency (hidden hunger region), sufficiency (luxuary consumption stage) and excess (harmful or toxic level). 2. Nitrogen contents for the above five status was less than 1.0%, 1.0 to 1.2, 1.2 to 1.6, 1.6 to 1.9 and greater than 1.9, respectively. 3. It was less than 0.3%, 0.3 to 0.4, 0.4 to 0.55 and greater than 0.55 for phosphorus $(P_2O_5)$ but excess level was not clear. 4. It was below 0.5%, 0.5 to 0.9, 0.9 to 1.2, 1.2 to 1.4 and above 1.4 for potassium. 5. It was below 4%, 4 to 6, 6 to 11 and above 11 for silicate $(SiO_2)$ and no excess was appeared. 6. Potassium in flag leaf seemed to crow out nitrogen to ear resulting better growth of ear by the inhibition of overgrowth of flag leaf. 7. Phosphorus accelerated the transport of Mg, Si, Mn and K in this order from lower leaf to flag, and retarded that of Ca and N in this order at flowering while potassium accelerated in the order of Mn, and Ca, and retarded in the order of Mg, Si, P and N at milky stage. 8. Transport acceleration index (TAI) expressed as (F_2L_1-F_1L_2)\;100/F_1L_1$ where F and L stand for other nutrient cotents in flag and lower leaf and subscripts indicate the rate of a nutrient applied, appears to be suitable for the effect of the nutrient on the translocation of others. 9. The content of silicate $(SiO_2)$ in the flag was lower than that of lower leaf in the early season cultivation indicating hinderance in translocation or absorption. It was reverse in the normal season cultivation. 10. The infection rate of Helminthosporium frequently occurred in the potassium deficient field seemed to be related more to silicate and nitrogen content than potassium in the flag leaf. 11. Deficiency of a nutrient occured simultaniously with deficiency of a few other ones. 12. Nutritional disorder under the field condition seems mainly to be attributed to macronutrients and the role of micronutrient appears to be none or secondary.

• Journal of Animal Environmental Science
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• v.12 no.3
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• pp.141-150
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• 2006

To optimise the efficient use of nutrients in pig slurry is to cultivate friendly environmental crops. This field survey is to investigate the actual conditions of pig slurry utilization for cultivation of crops in the agricultural farm, based on the survey for 407 selected farms in 9 provinces included 78 counties in Korea. The results obtained in this survey were summarized as follow ; The motive which came to use pig slurry in the agricultural farm were production of friendly environmental crops (29.7%), economy of chemical fertilizer (25.1%), spontaneously (19.2%), inducement of neighboring farmhouse (16.0%), increase of soil fertility (9.3%), and the others (0.7%), respectively. The proportions of pig slurry application land were 56.5% for.ice paddy, 22.6% for dry field, 13.3% for orchard, 4.4% for controlled agriculture and 3.2% for other, respectively. The number of times of pig slurry utilization per year were once (48.9%), twice (31.9%), thrice (14.0%), and the others (5.2%), respectively. The controversial points of pig slurry utilization were malodor (54.1%), insufficiency of spread equipment (22.1%), inconvenience (14.5%), over application (3.4%), over cost (2.9%), heavy metal (1.7%), sanitation (1.0%) and the other (0.2%), respectively. The results indicated that pig slurry could be used as fertilizer source of friendly environmental crops, but further studies are needed to determine the application method and value of the pig slurry for crop cultivation.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.1
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• pp.50-59
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• 2019

Objectives : Many of the patients with type 2 diabetes are associated with sleep problems, and the rate of insomnia is known to be higher in the general population. The aims of this study were to know the frequency and clnical characteristics of insomnia, and related variables to insomnia in patients diagnosed with type 2 diabetes. Methods : For 99 patients from 18 to 80 years of age (65 males and 34 females) with type 2 diabetes, interviews were performed. Total sleep time and sleep latency was evaluated. Insomnia was evaluated using the Korean Version of the Insomnia Severity Index (ISI-K). Severity of depressive symptoms were evaluted using the Korean version of the Hamilton Depression Scale (K-HDRM). According to the cutoff score of 15.5 on the ISI-K, subjects were divided into the group of type 2 diabetics with insomnia (N=34) and those without insomnia (N=65) at first, and then statistically analyzed. Results : TInsomnia could be found in 34.34% of type 2 diabetics. Type 2 diabetics with insomnia had significantly more single or divorced (respectively 11.8%, p<0.05), higher total scores of the K-HDRS ($11.76{\pm}5.52$, p<0.001), shorter total sleep time ($5.35{\pm}2.00hours$, p<0.001), and longer sleep latency ($50.29{\pm}33.80minutes$, p<0.001). The all item scores of the ISI-K in type 2 diabetics with insomnia were significantly higher than those in type 2 diabetics without insomnia, that is, total ($18.38{\pm}2.69$), A1 (Initial insomnia) ($2.97{\pm}0.76$), A2 (Middle insomnia) ($3.06{\pm}0.69$), A3 (Terminal insomnia) ($2.76{\pm}0.61$), B (Satisfaction) ($3.18{\pm}0.72$), C (Interference) ($2.09{\pm}0.97$), D (Noticeability) ($2.12{\pm}1.09$) and E (Distress) ($2.21{\pm}0.81$) (respectively p<0.001). Variables associated with insomnia in type 2 diabetics were as following. Age had significant negative correlation with A3 items of the ISI-K (${\beta}=-0.241$, p<0.05). Total scores of the K-HDRS had significant positive correlation, while total sleep time had significant negative correlation with all items of the ISI-K (respectively p<0.05). Sleep latency had significant positive correlation with total,, A1, B and E item scores of the ISI-K (respectively p<0.05). Conclusions : Insomnia was found in about 1/3 of type 2 diabetics. According to the presence of insomnia, clinical characteristics including sleep quality as well as quantity seemed to be different. Because depression seemed to be correlated with insomnia, clinicians should pay attention to early detection and intervention of depression among type 2 diabetics.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.3
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• pp.242-252
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• 1984

A port experiment was conducted to compare the effect of chemical forms of nitrogen fertilizers on the rice growth and soil characteristics. The nitrogen fertilizers used for this study were ammonium sulfate, ammonium nitrate, ammonium chloride and urea. The results are summarized as follows. 1. The differences in pH of the soil and surface water between treatments during the first week after fertilizer application were great and the pH values were in the order of urea > ammonium nitrate > ammonium sulfate > ammonium chloride treatment. However the differences were insignificant after the first week. 2. The differences in pH of the air-dried soil somewhat increased and pH values were in the order of urea > ammonium nitrate > ammonium chloride > ammonium sulfate treatment. 3. Sulfur contents of the soil and the rice leaf and N content of the rice leaf were highest when ammonium sulfate was applied. But there were few differences between the treatments in total N content of the soil and in P, K, Ca and Mg contents of the soil and the rice leaf. 4. Number of tillers and dry matter weight of the rice plant were highest in ammonium sulfate plot throughout all the growing stages. 5. Number of panicle per hill was highest in ammonium sulfate plot, and this brought the highest grain yield in ammonium sulfate plot. The lowest grain yield in ammonium nitrate plot resulted from the lowest number of panicle per hill and ripened grain ratio.