• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• International Commerce and Information Review
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• v.8 no.4
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• pp.105-121
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• 2006

This study is related with the judgements of our country's supremcourt against the transaction of Letter of Credit which is beneficiary's fraudulent trade deal. In this case I think to analyse the judgements and to present the basic grounds on which the judgements were established. In Letter of Credit transaction, there are the major parties, such as, beneficiary, issuing bank, or confirming bank and the other parties such as applicant, negotiating bank, advising bank and paying bank. Therefore, in this cases, the beneficiary, the French Weapons' Supplier who did not shipped the commodities, created the false Bill of Lading, let his dealing bank make payment against the documents presented by him and received the proceeds from the negotiating bank or collecting bank, thereafter was bankrupted and escaped. For the first time, even though the issuing bank conceived that the presented documents were inconsistent with the terms of L/C. it did not received the payment approval from the applicant against all the discrepancies, made the negotiating bank pay the proceeds to exporter and thereafter, delivered the documents to the applicant long after the time of the issuing bank's examination of documents. The applicant who received the documents from the issuing bank, instantly did not examine the documents and inform to the issuing bank whether he accepted the documents or not. Long time after, applicant tried to clear the goods through custom when he knew the bill of ladings were false and founded out the documents had the other discrepancies which he did not approved. As the results, the applicant, Korea Army Transportation Command claimed, that the issuing bank must refund his paid amount because issuing bank examined the documents unreasonably according to u.c.p 500 Act 13th, 14th. In spite of the applicant's claim, the issuing bank argued that it paid the proceeds of L/C reasonably after receiving the applicant's approval of an discrepancy of document, the delayed shipment, but for concerning the other discrepancies, the trivial ones, the applicant did not examined the document and noticed the discrepancies in reasonable time. Therefore the applicant sued the issuing bank for refunding it's paid proceeds of L/C. Originally, this cases were risen between Korea Exchange Bank and Korea Army Transportation Command. As result of analysing the case, the contents of the case case have had same procedure actually, but the lower courts, the district and high courts all judged the issuing bank was reasonable and did not make an error. As analysing these supreme court's judgements, the problem is that whether there are the applicant's liability of examining the documents and informing its discrepancies to the issuing bank or not, and if the applicant broke such a liabilities, it lost the right of claiming the repayment from issuing bank. Finally to say, such applicant's liabilities only must be existed in case the documents arrived to the issuing bank was delivered to the applicant within the time of the documents examination according to u.c.p 500 Act 14, d. i. But if any the documents were delivered to applicant after time of the documents examination, the applicant had not such liabilities because eventhough after those time the applicant would have informed to the issuing bank the discrepancies of documents, the issuing bank couldn't receive repayment of its paid proceeds of document from the negotiating bank. In the result after time of issuing bank's examination of documents, it is considered that there's no actual benefit to ask the applicant practice it's liability. Therefore finally to say. I concluded that the Suprem Court's judgement was much more reasonable. In the following, the judgements of the supreme court would be analysed more concretely, the basic reasons of the results be explained and the way of protecting such L/C transaction would be presented.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Progress in Medical Physics
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• v.11 no.2
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• pp.123-130
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• 2000

The performance of an electrometer directly affects on the accuracy and precision in radiation dosimetry. This study is to list of the quality control for maintaining performance and to perform evaluation tests of an electrometer. Performance tests selected include proper polarizing voltages, warm-up and equalization time, leakages, long-term stability, linearity, and effect of ambient conditions. An electrometer connected with a rigid stem ionization chamber was evaluated with a Strontium-90 check device. Bias voltage was measured directly on the input socket. Equalization time is the time required for reaching threshold of charged state after the power is on or the bias voltage is changed. Pre- and post-signal leakages are defined as the accumulation of signal with no exposure and after exposure, respectively. Over three months period, the electrometer's long-term stability was measured by comparison of the temperature-pressure corrected readings. Linearity was expressed as the deviation of readings from multiple short exposures from one continuous exposure. Effect of ambient conditions was expressed as the zero drift of the electrometer over 17-34$^{\circ}C$ temperature ranges. For two nominal values, 300 and 500 volts, measured voltages were lower by 2.5 and 5.8%, respectively. The warm-up time, 20 minutes, was longer than the lamp time by 9 minutes and the equalization time was less than 1 minute. Without exposure, the zero-drift was 0.002 scale-unit in 15 minutes and the leakage after 10 minutes exposure was minimal. The IQ-4 was stable over 99.4% for three-month periods. Deviation from the linearity was 0.9% for measurement scale, 0.000-9.991. Over 17-34$^{\circ}C$ temperature range, the zero-drift was minimal, less than 0.2%. For a clinically-used electrometer, a list for the basic peformance evaluations is proposed. By running this program, the measurement error using an electrometer can be reduced and in turn the improvement in accuracy and precision of radiation dosimetry can be achieved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4907-4921
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• 2010

The object of this descriptive survey research was to provide basic information source for building objective standards of DNR (Do Not Resuscitate) that can be clinically applied, by analyzing college students' awareness and attitude toward DNR. The participants of the study were 1,267 students from one college of Daegu, South Korea. The structured survey questionnaire was used for data collection, and the survey was conducted from 1-31 July, 2010. The error and percentage was estimated by SPSS 17.0 program, and analyzed with $x^2$-test. As a result of comparing the nursing students' and non-health care major students' awareness and attitude toward DNR, the significant differences were found in the necessity of DNR, reason for supporting DNR, reason for opposing DNR, and DNR decision-maker, among the awareness dimension; among the attitude dimension, significant differences were found in implication of family DNR and self-DNR. Comparing the nursing students' and non-health care major students' awareness toward DNR related information provision, researchers have found significant differences in the necessity of giving information on DNR, timing of the DNR information provision, result of the DNR-related information provision, and guidelines for the DNR information provision. In terms of the difference in DNR's necessity recognition by the demographic information, the significant differences existed based on the religion and the history of blood donation; in terms of the differences in attitude toward DNR decision-maker, the differences were found on the religion and the number of siblings. For the attitude toward family member's DNR, the significant differences existed for the sex, age, economic status, religion, the number of siblings, the history of familial illness and death, and experience of blood donation; the attitude toward the DNR for the self was significantly differed by the sex, economic status, the number of siblings, and the history of familial illness and death. To establish the standards for DNR based on the study, we suggest more well-designed future studies.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korean Wood Science and Technology
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• v.44 no.3
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• pp.370-380
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• 2016

The black pine logs damaged by pine wilt disease in Jeju-do were heat-treated to extend the utilization of domestic trees damaged by pine wilt disease. The heat-treatment of wood requires wood to be heated to $56^{\circ}C$ for 30 min at the core. The average moisture content and top-diameter of the black pine logs were ranged from 46% to 141% and from 180 mm to 500 mm, respectively. And the basic specific gravity and oven-dry specific gravity of the black pine logs were 0.47 and 0.52, respectively. The time required for heat-treatment at $105^{\circ}C$ temperature was ranged from 7.7 h to 44.2 h, depending on moisture content and top-diameter. The temperature distribution was used to predict the time required for heat-treatment of black pine log with various moisture contents and top-diameters using finite difference method. The thermal properties of wood including the thermal conductivity and specific heat in accordance with moisture content were calculated. Heat transfer coefficient for mixed convection in form of adding natural convection and forced convection was used for heat transfer analysis. The error between the measured and predicted values ranged from 3% to 45%. The predicted times required for heat-treatment of black pine log with 50% moisture content and 200 mm, 300 mm, and 400 mm top-diameter were 10.9 h, 18.3 h, and 27.0 h, respectively. If the initial moisture content of black pine log is 75%, heat treatment times of 13.6 h, 22.5 h, and 32.8 h were predicted in accordance with top-diameter. And if the initial moisture content of black pine log is 100%, heat treatment times of 16.2 h, 26.5 h, and 38.2 h were predicted in accordance with top-diameter. When the physical properties of logs damaged by pine wilt disease are presented, these results can be applicable to the heat-treatment of red pine and Korean pine logs as well.

• Journal of dental hygiene science
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• v.14 no.2
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• pp.158-166
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• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• Journal of Korean Society of Forest Science
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• v.61 no.1
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• pp.37-44
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• 1983

This study was to estimate total annual volume growth by the measurement of mean tree growth during the last 10 years. Surveyed Forest stand was the second block (20.80 ha.)of Kyung Hee University Forests located at San 58 and 64, Gaegok-Ri, Gapyung-Yeup, Gapyung-Goon, Kyunggi province in Korea. The stand was mainly composed of uneven-aged Pinus densiflora and the estimation of tree volume was conducted by taking the cores at the D.B.H. of the sample tree which was selected by sub-sampling. The results obtained were as follows; 1) The regression between the diameter (D) and diameter growth ($\hat{I}$) was $\hat{I}=0.5499+0.0101D$. 2) The estimated equation of confidence interval for the diameter growth was $S^2{\hat{I}}=0.00817(0.09538-0.00952D+0.00027D^2$) 3) The equation for estimating tree height (H) from diameter was $H=1.32376D^{0.77958}$ 4) The equation for estimating tree volume from diameter and height $V=0.0000622D^{1.6918}H^{1.1397}$ 5) Total annual tree volume growth was $5.4041m^3/ha$, and ranged from 5.6131 to $5.1984m^3/ha$. 6) Annual growth rate of total tree volume and its error were 8.8% and 3.9%, respectively. The annual volume growth per tree for any districts can be estimated by this method, and the annual volume growth will be successfully predicted. Because of poor forest growing stock in Korea, annual amount of allowable cut should not exceed annual tree volume growth for better forest management. Accordingly, annual amount of allowable cut should be either equal to or less than annual tree volume growth for the balanced establishment between timber supply and demand in Korea. Demand shortage will be substituted with imported timber. Such plans enable Korean Government to develop a better policy of forest resources management.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.1
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• pp.37-41
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• 2016

Purpose The importance of quality control by the error to a minimum, which for the purpose of enhancing the reliability of the examination is not be emphasized excess. Currently, most nuclear medicine laboratory are conducting the internal and external quality control, and they are applying the Levey-Jennings or Westgard Multi-Rules by using the commercialized quality control materials. The reliability of the nuclear medicine blood test which affects the diagnosis of patients and the treatment policy is being secured through this quality control activity. Therefore, researchers will evaluate the utility of the statistic quality control using the population distribution of the nuclear medicine blood test conducted targeting the checkup examinees by the additional technique of the reliability improvement. Materials and Methods A statistic analysis was performed about 12 items of the nuclear medicine blood test targeting 41,341 peoples who used the health screening and promotion center in Asan Medical Center from January, 2014 to December, 2014. The results of 12 items of the nuclear medicine blood test was divided into the monthly percentage of three groups: within reference values, over reference, and under reference to analyze the average value of the population distribution, standard deviation, and standard deviation index (SDI). Results The standard deviation of the population distribution mostly showed a result within ${\pm}2SD$ in all groups. However, When the standard deviation of the population distribution represented a result over ${\pm}2SD$, it was confirmed SDI was showing a result of SDI > -2 or SDI > 2. As a result of analyzing the population distribution of 12 items(AFP, CEA, CA19-9, CA125, PSA, TSH, FT4, Anti-Tg-Ab, Anti-TPO-Ab, Calcitonin, 25-OH-VitD3, Insulin) of the nuclear medicine blood part basic test, when SDI of the monthly percentage which deviated from the reference values was over ${\pm}2.0$, CA19-9 September was 2.2, Anti-Tg-Ab may was 2.2, Insulin January was 2.3, Insulin March was 2.4. It was confirmed these cases were attributed to the abnormality of the test reagent (maximum combination rate of isotope reagent declined) and the decline of the test response time. Conclusion The population distribution includes the entire attribute which becomes the study object. It is expected the statistic quality management using the population distribution which was conducted targeting the checkup examinees by dividing into three groups: within reference values, over reference, and under reference by means of this characteristics will be able to play a role of complementing the internal quality control program which is being carried out in the laboratory.