• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.1
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• pp.8-15
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• 1995

The reliable measurement of metal in biological media in human body is one of critical indicators for the proper evaluation of its toxic effect on human health. Recently in Korea the necessity of quality assurance of measurement in occupational health and occupational hygiene fields brought out regulatory quality control program. Lead is often used as a standard metal for the program in both fields of occupational health and hygiene. During last 20 years lead poisoning was prevalent in Korea and still is one of main heavy metal poisoning and the capability of the measurement of blood lead is one of prerequisites for institute of specialized occupational health in Korea. Furthermore blood lead is most important indicator to evaluate lead burden of human exposure to lead and the reliable and accurate analysis is most needed whenever possible. To evaluate the extent of the interlaboratory differences of blood lead measurement in several well-known institute specialized in occupational health in Korea, authors prepared 68 blood samples from two storage battery industries and all samples were divided into samples with 2 ml. One set of 68 samples were analyzed by authors's laboratory(Soonchunhyang University Institute of Industrial Medicine: SIIM) and 40 samples of other set were analyzed by C University Institute of Industrial Medicine(CIIM) and the rest 28 samples of other set were analyzed by Japanese institute(K Occupational Health Center:KOHC). Authors also prepared test bovine samples which were obtained from Japanese Federation of Occupational Health Organization (JFOHO) for quality control. Authors selected 2 other well-known occupational health laboratories and one laboratory specialized for instrumental analysis. A total of 6 laboratories joined the interlaboratory comparison of blood lead measurement and the results obtained were as follows: 1. There was no significant difference in average blood lead between SIIM and CIIM in different group of blood lead concentration, and the relative standard deviation of two laboratories was less than 3.0%. On the other hand, there was also no significant difference of average blood lead between SIIM and KOHC with relative standard deviation of 6.84% as maximum. 2. Taking less than 15% difference of mean or less than 6 ug/dl difference in below 40 ug/dl in whole blood as a criteria of agreement of measurement between two laboratories, agreement rates were 87.5%(35/40) and 78.6%(22/28) between SIIM and CIIM, SIIM and KOHC respectively. 3. The correlation of blood lead between SIIM and CIIM was 0.975 (p=0.0001) and the regression equation was SIIM = 2.19 + 0.9243 ClIM, whereas the correlation between SUM and KOHC was O.965(p=0.0001) with the equation of SIIM = 1.91 + 0.9794 KOHC. 4. Taking the reference value as a dependent variable and each of 6 laboratories's measurement value as a independent variable, the determination coefficient($R^2$) of simple regression equations of blood lead measurement for bovine test samples were very high($R^2>0.99$), and the regression coefficient(${\beta}$) was between 0.972 and 1.15 which indicated fairly good agreement of measurement results.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.