• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.95-100
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• 2013

Purpose: Since 2008, hepatitis A patients was rapidly increasing. So, Most of the health checkup examinees were interested in whether hepatitis A antibody was a lot. thereby The number of tests was increasing. In recent years, Antibody test results in the range of cut-off values were increased. According to the cause analysis, most examinees had a hepatitis A vaccine. This study was conducted to classify hepatitis A antibody as natural antibody and antibody after vaccination and compared the titer for seroconversion rate based on cut-off values. Materials and Methods: For a month in August 2012, First, We surveyed 185 health examinees and classified 119 health examinees who had acquired natural antibody. Second, for employees who were inoculated against hepatitis at our hospital, We classified into 53 primary inoculators and 59 secondary inculators. when the standard of cut-off value was 1, The seroconversion rate was compared the titer divided by 0.90-1.10 (${\pm}$), 0.60-0,89 (1+), 0.30-0.59 (2+), 0.01-0.29 (3+) and we compared the titer for seroconversion rate by each manufacturer after vaccination. Results: When the standard of cut-off value was 1, the titer of 119 health examinees who had acquired natural antibody was 0.90-1.10 (${\pm}$): 0%, 0.60-0.89 (1+): 0%, 0.30-0.59 (2+): 4.2%, 0.01-0.29 (3+): 96% and the titer of <0.60 ($${\geq_-}2+$$) was 100%. The titer of 53 primary inoculators was 0.90-1.10 (${\pm}:59.1%$), 0.60-0.89 (1+): 18.1%, 0.30-0.59 (2+): 18.1%, 0.01-0.29 (3+): 4.6% and the seroconversion rate was 45.3%. The titer of $${\geq_-}0.60$$ ($${\leq_-}1+$$) was 77.3%. The titer of 59 secondary inoculators was 0.90-1.10 (${\pm}:1.9%$), 0.60-0.89 (1+): 15.4%, 0.30-0.59 (2+): 36.54%, 0.01-0.29 (3+): 46.2% and the seroconversion rate was 88.1%. The titer of <0.60 ($${\geq_-}2+$$) was 82.7%. When we compared the titer for seroconversion rate by each manufacturer after vaccination, the seroconversion rate of 53 primary inoculators was BNIBT: 20.8% (${\pm}:24.5%$), GB: 15.7% (${\pm}:7.8%$), RIAKEY: 94.3% (${\pm}:3.8%$), ROCHE: 83% (${\pm}:0%$), ABBOTT: 73.1% (${\pm}:5.8%$) and the seroconversion rate of 59 secondary inoculators was BNIBT : 86.4% (${\pm}:1.7%$), GB: 88.5% (${\pm}:1.9%$), RIAKEY: 100% (${\pm}:0%$), ROCHE: 98.3% (${\pm}:0%$), ABBOTT: 98.2% (${\pm}:0%$). Conclusion: The study show that the titer of natural immune antibodies is higher than the titer of vaccination and the titer of secondary inoculation is mainly higher than the titer of primary inoculation. Consequently, if we know the titer of hepatitis A antibodies, it will help to give resullt reports. And then, when we compared the titer and the seroconversion rate by each manufacturer, There was a very distinct difference. As the test subjects inoculate against hepatitis A (HAV), it is considered BNIBT, GB will occur false negative rate and RIAKEY, ROCHE, ABOTT will occur false positive rate.

• 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.

• Journal of dental hygiene science
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• v.5 no.4
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• pp.211-220
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• 2005

The purpose of this study was to examine the job performance of dental coordinators and their perception of their job to lay the groundwork for utilizing dental personnels more efficiently. The subjects in this study were dental coordinators who worked at selected dental hospitals and clinics in Seoul, Gyeonggi province and Incheon. A survey was conducted to gather data from May 1 to August 8, 2005 and answer sheets from 108 respondents were analyzed. The findings of the study were as follows: 1. As for the length of service, 43.5 percent of the dental coordinators investigated had worked at dental institutes for five years or more, which was followed by less than two years(19.5%) and three years to less than five years(19.4%). Concerning the length of service as dental coordinators, 39.8 percent had served for less than two years, and 19.4 percent had worked for two years to less than three years and for five years or more respectively. Regarding the name of position, 38 percent were called team leaders, and 30.6 percent were called coordinators. As to duties, the largest group of them that stood at 30.6 percent were in charge of receiving, and in regard to department, the largest group, 57.4 percent, belonged to the treatment backup department. 2. Concerning education, the greatest number of them, 45.4 percent, had received education at private institutes, and 73.1 percent found it necessary for dental coordinators to take an authorized qualification test. 43.5 percent, the largest group, looked upon the central government as the best organization to authorize their qualifications and 70.8 percent believed that what they learned enabled them to perform their job successfully. As to the necessity of follow-up education as a means to improve job performance, 96.3 percent consented to it. As for the reason, 63.9 percent considered that necessary to enhance their own ability and 22.2 percent were in want of systematic education. Regarding educational expenses, 29.6 percent were subsidized by the dental institutes where they had worked and 25.9 percent had totally been responsible for that. Regarding a required course, medical service and marketing was most widely pointed out(66.7%), followed by theory and practice(65.7%) and introduction to dentistry(57.4%). As to what sort of education they wanted to receive more, dental service and marketing was selected the most, followed by practical health insurance(35.2%). 3. In regard to what type of job they performed as dental coordinators, 88.9 percent were in charge of appointment in the field of customer service, and 87.9 percent paid attention to having good manners as service providers in the area of self-management. In the field of hospital affairs, 81.3 percent were in charge of receiving. 4. As to their awareness of dental coordinator job, the largest group took pride in the job they performed ($3.99{\pm}0.76$), and the second largest group believed that dental coordinators made a great contribution to hospital management ($3.92{\pm}0.70$). The third largest group gave a great weight to their own job ($3.91{\pm}0.84$) in light of overall dental duties and the fourth largest group found themselves to get along with other employees regardless of position ($3.86{\pm}0.74$). The fifth largest group believed their job was of great use for promoting the oral health of patients ($3.76{\pm}0.75$), and the sixth largest group thought the future of dental coordinators was promising($3.74{\pm}0.86$). 5. In regard to their perception by age group, those who were older had a better opinion on every item of their job in general. Their age made a statistically significant difference to their view of the weight of dental coordinator job(P < 0.001) in light of overall dental duties, of being approved and trusted by managers(P < 0.01), of social awareness of dental coordinator, and of being understood and approved by other employees and dentists. Their pride in current job and their satisfaction with the name of their position were statistically significantly different according to their age as well. Besides, their age made a statistically significant difference to their opinion about whether or not there was an age limit to their occupation and about their contribution to hospital management (P < 0.05). 6. As for their perception by type of job, the dental hygienists were generally most satisfied with their job, followed by nursing aids and others. There was a statistically significant gap among their opinions about whether to make a job-related decision on their own(P < 0.001). the weight of their job in terms of overall dental duties, whether their job improved their ability, whether their job made a great contribution to enhancing the oral health of patients, whether their job was understood and approved by other employees(P < 0.01), social awareness of their job, whether they conflicted with other employees during job performance, and whether dental hospitals or clinics offered a self-development opportunity for them to take their ability to another level(P < 0.05). And their satisfaction with current pay was statistically significantly different as well.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.