• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.65-81
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• 2015

As research management is growing in importance for research organizations, their disciplinary structures need to be interpreted. However, it is not only difficult but ambiguous to detect causal relations between subjects because diverse disciplines interacting with each other lead the development of organizational research. Therefore, this article summarizes the major concepts and results recently achieved in the related fields such as research management, bibliographic analysis, information theory, and networks to characterize organizational knowledge structures. Relevant analytical methods obtained from the literature can be applied to empirical situations. Predictive causal relations can be measured using an information theoretic indicator on a series of organizational research portfolios identified from bibliographic information. A network approach would be suitable to manage organizational research effort from a holistic view. Knowledge structures of the Government-funded Research Institutes in Korea are explored experimentally.

• Journal of Veterinary Clinics
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• v.32 no.4
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• pp.319-323
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• 2015

The performance of diagnostic test accuracy is usually summarized by a variety of statistics such as sensitivity, specificity, predictive value, likelihood ratio, and kappa. These indices are most commonly presented when evaluations of competing diagnostic tests are reported, and it is of utmost importance to compare the accuracies of diagnostic tests to decide on the best available test for certain medical disorder. However, it is important to emphasize that specific point values of these indices are merely estimates. If parameter estimates are reported without a measure of uncertainty (precision), knowledgeable readers cannot know the range within which the true values of the indices are likely to lie. Therefore, when evaluations of diagnostic accuracy are reported the precision of estimates should be stated in parallel. To reflect the precision of any estimate of a diagnostic performance characteristic or of the difference between performance characteristics, the computation of confidential interval (CI), an indicator of precision, is widely used in medical literatures in that CIs are more informative to interpret test results than the simple point estimates. The majority of peer-reviewed journals usually require CIs to be specified for descriptive estimates, whereas domestic veterinary journals seem less vigilant on this issues. This paper describes how to calculate the indices and associated CIs using practical examples when assessing diagnostic test performance.

• Journal of Korean Neurosurgical Society
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• v.64 no.5
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• pp.763-775
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• 2021

Objective : Hemorrhagic transformation (HT) can be occurred after acute cerebral infarction. HT can worse symptoms in severe cases and adversely affect long-term prognosis. As bone and vascular smooth muscle are composed of type 1 collagen, we aimed to identify a potential relationship between bone mineral density (BMD) and HT after acute cardioembolic stroke. Methods : As an indicator of BMD, we used mean frontal skull Hounsfield unit (HU) values on brain computed tomography (CT). Multivariative hazard ratios were calculated using Cox regression analysis to identify whether the osteoporotic condition was an independent predictor of HT after acute cardioembolic stroke. Results : This 11-year analysis enrolled 506 patients who diagnosed as acute cardioembolic infarction. The first tertile of skull HU value was an independent predictor of HT development compared to the third tertile (hazard ratio, 2.12; 95% confidence interval, 1.13-3.98; p=0.020). We observed no interactions between age and skull HU with respect to HT statistically. Conclusion : The results of this study revealed an association between osteoporotic conditions and HT development after acute cardioembolic stroke. A convenient method to measure the cancellous bone HU value of the frontal skull using brain CT images may be useful for predicting HT in patients with acute cerebral infarction.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• Clinical and Experimental Reproductive Medicine
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• v.19 no.1
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• pp.31-39
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• 1992

By means of the results of In vitro fertilization(IVF) of supernumerary oocytes, the possibility of predicting a pregnancy outcome following gamete intrafallopian transfer(GIFT) and the prognostic implications for future pregnancy were evaluated in 46 GIFT cycles excluding simultaneous program of GIFT and IVF from February, 1989 to July, 1991. IVF of supernumerary oocytes were identified in 21 cycles, but not in remaining 25 cycles. There was no significant difference in age, duration and etiologic factors of infertility, and serum levels of FSH, LH and $E_2$ on MCD #3 and $E_2$ on the day of hCG injection between fertilized(N=21) and unfertilized group(N=25). The number of oocytes retrieved was similar in both groups. The number of supernumerary oocytes available for IVF after transfer was $5.43{pm}2.95$ ranging from 2 to 12. The prenancy rate in fertilized group, 33.3%(7/21), was higher without statistical significance, compared with 8.0%(2/25) in unfertilized group. Using IVF of supernumerary oocytes as a test of pregnancy following GIFT, sensitivity was 77.8 %; specificity, 61.2%; positive predictive value(PPV), 33.3%; negative predictive value(NPV), 92%. The fertilization rate of supernumerary oocytes in pregnant group, $86.4{\pm}22.8%$ was significantly higher compared with $56.1{\pm}20.2%$ in nonpregnant group. In cases with fertilization rate ${\geq}80%$, pregnancy was expected with PPV of 85.7%. In conclusion, IVF of supernumerary oocytes in GIFT program can be a profitable method as a prognostic indicator of pregnancy following GIFT. More aggressive diagnostic and therapeutic measures should be performed in cases with failure in IVF of supernumerary oocytes.

• Clinical and Experimental Pediatrics
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• v.48 no.8
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• pp.820-825
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• 2005

Purpose : The presence and degree of fever in children is a useful indicator of illness. This project aimed to assess the accuracy and usefulness of infrared tympanic membrane(TM) & forehead feverscan thermometers for measuring children's temperatures. Methods : Data were obtained from 1,050 children with a median age of 4.5 years. They visited the pediatric clinics at Chung-Ang University Yongsan Hospital from January 2004 to December 2004. We measured body temperatures at axilla by mercury thermometer, at ear by infrared TM thermometer and at forehead by feverscan. Then we analyzed the correlation between these data. Results : Mercury and TM thermometer, and Mercury and forehead feverscan thermometer very well correlated with each others(P<0.05). And the sensitivity of infrared TM thermometer(right and left) to correctly identify febrile children was 81.1 percent and 82.4 percent, the positive predictive value to detect a fever was 81.8 percent and 73.6 percent. The sensitivity of forehead feverscan was 83.3 percent and the positive predictive value was 74.4 percent. Conclusion : The tympanic membrane temperature measured by the BRAUN IRT $3020^{(R)}$ and forehead arterial temperature measured by the HubDIC $DOTORY^{(R)}$ feverscan accurately reflects mercury axillary temperature, validly assesses the presence of fever in children, and is easy to use. The Braun IRT $3020^{(R)}$ & HubDIC $DOTORY^{(R)}$ therefore is an adequate tool to assess fever and may be used both in a clinical setting and for research purposes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.6
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• pp.788-794
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• 2013

Mastitis set apart as clinical and sub clinical is a disease complex of dairy cattle, with sub clinical being the most important economically. Of late, laboratories showed interest in developing biochemical markers to diagnose sub clinical mastitis (SCM) in herds. Many workers reported noteworthy alternation of acute phase proteins (APPs) and nitric oxide, (measured as nitrate+nitrite = NOx) in milk due to intra-mammary inflammation. But, the literature on validation of these parameters as indicators of SCM, particularly in riverine milch buffalo (Bubalus bubalis) milk is inadequate. Hence, the present study focused on comparing several APPs viz. ${\alpha}_1$-anti trypsin, ${\alpha}_1$-acid glycoprotein, fibrinogen and NOx as indicators of SCM in buffalo milk. These components in milk were estimated using standardized analytical protocols. Somatic cell count (SCC) was done microscopically. Microbial culture was done on 5% ovine blood agar. Of the 776 buffaloes (3,096 quarters) sampled, only 347 buffaloes comprising 496 quarters were found positive for SCM i.e. milk culture showed growth in blood agar with $SCC{\geq}2{\times}10^5$ cells/ml of milk. The cultural examination revealed Gram positive bacteria as the most prevalent etiological agent. It was observed that ${\alpha}_1$-anti trypsin and NOx had a highly significant (p<0.01) increase in SCM milk, whereas, the increase of ${\alpha}_1$-acid glycoprotein in infected milk was significant (p<0.05). Fibrinogen was below detection level in both healthy and SCM milk. The percent sensitivity, specificity and accuracy, predictive values and likelihood ratios were calculated taking bacterial culture examination and $SCC{\geq}2{\times}10^5$ cells/ml of milk as the benchmark. Udder profile correlation coefficient was also used. Allowing for statistical and epidemiological analysis, it was concluded that ${\alpha}_1$-anti trypsin indicates SCM irrespective of etiology, whereas ${\alpha}_1$-acid glycoprotein better diagnosed SCM caused by gram positive bacteria. NOx did not prove to be a good indicator of SCM. It is recommended measuring both ${\alpha}_1$-anti trypsin and ${\alpha}_1$-acid glycoprotein in milk to diagnose SCM in buffalo irrespective of etiology.

• The korean journal of orthodontics
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• v.43 no.6
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• pp.279-287
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• 2013

Objective: To investigate the dentoskeletal factors which may predict soft-tissue chin strain during lip closure. Methods: The pretreatment frontal and lateral facial photographs and lateral cephalograms of 209 women (aged 18-30 years) with Angle's Class I or II malocclusion were examined. The subjects were categorized by three examiners into the no-strain and strain groups according to the soft-tissue chin tension or deformation during lip closure. Relationships of the cephalometric measurements with the group classification were analyzed by logistic regression analysis, and a classification and regression tree (CART) model was used to define the predictive variables for the group classification. Results: The lower the value of the overbite depth indicator (ODI) and the higher the values of upper incisor to Nasion-Pogonion (U1-NPog, mm), overjet, and upper incisor to upper lip (U1-upper lip, mm), the more likely was the subject to be classified into the strain group. The CART showed that U1-NPog was the most prominent predictor of soft-tissue chin strain (cut-off value of 14.2 mm), followed by overjet. Conclusions: To minimize strain of the soft-tissue chin, orthodontic treatment should be oriented toward increasing the ODI value while decreasing the U1-NPog, overjet, and U1 upper lip values.

• Journal of Preventive Medicine and Public Health
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• v.34 no.3
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• pp.244-252
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• 2001

Objective : Health insurers and policy makers are increasingly examining the hospital mortality rate as an indicator of hospital quality and performance. To be meaningful, a risk-adjustment of the death rates must be implemented. This study reviewed 5 severity measurement methods and applied them to the same data set to determine whether judgments regarding the severity-adjusted hospital mortality rates were sensitive to the specific severity measure. Methods : The medical records of 584 patients who underwent coronary artery bypass graft surgery in 6 general hospitals during 1996 and 1997 were reviewed by trained nurses. The MedisGroups, Disease Staging, Computerized Severity Index, APACHE III and KDRG were used to quantify severity of the patients. The predictive probability of death was calculated for each patient in the sample from a multivariate logistic regression model including the severity score, age and sex to evaluate the hospitals' performance, the ratio of the observed number of deaths to the expected number for each hospital was calculated. Results : The overall in-hospital mortality rate was 7.0%, ranging from 2.7% to 15.7% depending on the particular hospital. After the severity adjustment, the mortality rates for each hospital showed little difference according to the severity measure. The 5 severity measurement methods varied in their statistical performance. All had a higher c statistic and $R^2$ than the model containing only age and sex. There was a little difference in the relative hospital performance evaluation by the severity measure. Conclusion : These results suggest that judgments regarding a hospital's performance based on severity adjusted mortality can be sensitive to the severity measurement method. Although the 5 severity measures regarding hospital performance concurred, more often than would be expected by chance, the assessment of an individual hospital mortality rates varied by the different severity measurement method used.