• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.389-401
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• 2012

This paper derives a benchmark dose(BMD) and its 95% lower confidence limit(BMDL) using a semi-parametric regression model for small lead based changes in attention-deficit hyperactivity disorder(ADHD) scores in the first wave of the Children's Health and Environment Research(CHEER) survey data, which have been regularly collected in South Korea since 2005. Ha et al. (2009) showed that the appearance of ADHD symptoms had a borderline trend of increasing with the blood lead concentration. Butdz-J${\o}$rgensen (EFSA, 2010a) derived the BMDL of lead corresponding to a benchmark region of 1 full intelligent quotient (IQ) score using the raw data in Lanphear et al. (2005, EHP). European Food Safety Authority (EFSA, 2010b) determined the BMDL of $1.2{\mu}g/dl$ as a reference point for the characterization of lead when assessing the risk of the intellectual deficit measured by IQ scores. Kim et al. (2011) indicated that an even lower BMDL could be obtained based on the ADHD score; however, the BMDLs depended heavily upon the model assumptions. We show in this paper that a semi-parametric approach resolves the model dependence of BMDLs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.9-19
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• 2024

Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.6
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• pp.667-683
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• 2015

Since aged water treatment facilities could threaten the sustainable water supply, asset management system has been adopted for their systematic management. Level of Service(LoS) is one of critical components of asset management and could be quantified through benchmark index(BMI). Water supplier could estimate consumer's satisfaction and their performance through BMI to improve the LoS. We developed BMI for water treatment facilities from customer's satisfaction survey. BMI, represented with the Total Service Score(TSS), was assessed with water quality, water pressure, taste and odor, water rate, and service quality with weighing factors. BMI could, further, be used to assist the analysis of the life cycle cost to increase the unit of LoS.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.112-127
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• 2002

A useful pattern is a pattern that contributes much to learning. For a classification problem those patterns near the class boundary surfaces carry more information to the classifier. For a regression problem the ones near the estimated surface carry more information. In both cases, the usefulness is defined only for those patterns either without error or with negligible error. Using only the useful patterns gives several benefits. First, computational complexity in memory and time for learning is decreased. Second, overfitting is avoided even when the learner is over-sized. Third, learning results in more stable learners. In this paper, we propose a pattern 'utility index' that measures the utility of an individual pattern. The utility index is based on the bias and variance of a pattern trained by a network ensemble. In classification, the pattern with a low bias and a high variance gets a high score. In regression, on the other hand, the one with a low bias and a low variance gets a high score. Based on the distribution of the utility index, the original training set is divided into a high-score group and a low-score group. Only the high-score group is then used for training. The proposed method is tested on synthetic and real-world benchmark datasets. The proposed approach gives a better or at least similar performance.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.19 no.1
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• pp.11-18
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• 2012

Purpose: The aim of this study is to evaluate the efficiency of the outpatient clinics in a hospital, using DEA. Methods: Data were collected using an activity-based costing system, medical information system, and annual reports of customer satisfaction management team of a general hospital in a city. The input variables were the number of doctors, the number of nurses, and the number of staffs. The output variables were the number of treatment times, the number of outpatient clinic patients, the total profits from outpatient clinic, the patient's satisfaction score, and the number of re-visit appointments. EMS Window version 3.1 was used to measure the efficiency score and benchmarking analysis. Results: The average efficiency score of 24 outpatient clinics was about 82.01%. Thirteen outpatient clinics had 100% efficiency score among them. The lowest efficiency score was 57.56%. Conclusion: According to these results, we found that, generally, outpatient clinics were operated very efficiently. However, some outpatient clinics had low efficiency and they needed specialized outcome improvement strategies. To increase the efficiency of inefficient outpatient clinics, we will recommend using results of DEA, as a benchmark point of the most efficient outpatient clinics.

• Clinics in Shoulder and Elbow
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• v.25 no.2
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• pp.145-153
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• 2022

Background: While online orthopedic resources are becoming an increasingly popular avenue for patient education, videos on YouTube are not subject to peer review. The purpose of this cross-sectional study was to evaluate the quality of YouTube videos for patient education in ulnar collateral ligament (UCL) injuries of the elbow. Methods: A search of keywords for UCL injury was conducted through the YouTube search engine. Each video was categorized by source and content. Video quality, reliability, and accuracy were assessed by two independent raters using five metrics: (1) Journal of American Medical Association (JAMA) benchmark criteria (range 0-4) for video reliability; (2) modified DISCERN score (range 1-5) for video reliability; (3) Global Quality Score (GQS; range 1-5) for video quality; (4) ulnar collateral ligament-specific score (UCL-SS; range 0-16), a novel score for comprehensiveness of health information presented; and (5) accuracy score (AS; range 1-3) for accuracy. Results: Video content was comprised predominantly of disease-specific information (52%) and surgical technique (33%). The most common video sources were physician (42%) and commercial (23%). The mean JAMA score, modified DISCERN score, GQS, UCL-SS, and AS were 1.8, 2.4, 1.9, 5.3, and 2.7 respectively. Conclusions: Overall, YouTube is not a reliable or high-quality source for patients seeking information regarding UCL injuries, especially with videos uploaded by non-physician sources. The multiplicity of low quality, low reliability, and irrelevant videos can create a cumbersome and even inaccurate learning experience for patients.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.18 no.2
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• pp.118-125
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• 2011

Purpose: The aim of this study was to evaluate the efficiency of nursing units in a hospital using DEA. Methods: Data were collected using the medical information system of a general hospital in a city. Input variables were number of nurses, number of nurse-aides, number of beds, and overhead costs. Output variables included number of admitted patients, rate of bed utilization, satisfaction of discharged patients, and prevention rate of safety accidents and sores. EMS Window version 3.1 was used to measure the efficiency score and descriptive statistics were applied to analyze the general characteristics of variables. Results: The average efficiency score of 18 general nursing units was approximately .99. Nine nursing units had a 1.00 efficiency score. Conclusion: Our findings reveal that nursing units operated very efficiently. To increase efficiency of inefficient nursing units, we recommend results of the DEA slack analysis as a benchmark of the most efficient nursing unit.

• Journal of the Korean Society of Food Culture
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• v.19 no.4
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• pp.407-418
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• 2004

A study of the comparison of customers' satisfaction and loyalty at McDonald's two types of outlets is presented. The objective of this study is to test correlation among selection attributes, customer satisfaction and loyalty of customers patronizing two types of Mcdonald's restaurants - stand alone and co-branded, as Mcdonald's is known to be actively participating in co-branding with discount stores such as E-Mart. In order to measure customer loyalty, benchmark scores from customers showing extreme satisfaction are compared to the mean scores of total sample customers at each outlet. Meeting or exceeding benchmarking scores does not automatically bring in and create loyal customers but in doing so will certainly help build up strong customer relationship which will create additional loyalty. Marketers should be well aware that statistically significant difference do exist between these two groups of customers and should take into consideration these findings in opening up new outlets or renovating existing outlets.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.2
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• pp.29-40
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• 2022

The study investigated the challenges of recruitment and selection process of librarians in federal university libraries in South-South, Nigeria. The study adopted a descriptive survey. The population of the study consists of 108 librarians. 95 copies of the questionnaire were filled and returned. The questionnaire was used in collecting data. The overall reliability of the instrument yielded 0.95 with the use of Cronbach Alpha Coefficient. Standard deviation and mean was used to generate the data that was gathered. The rating scale of 4 points was subjected to an estimation procedure using SPSS version 17.0. A mean score of 2.5 and above on any item was accepted. The findings revealed that the librarians identified the challenges to include ethnicity influence; favouritisms; recruitment based on godfatherism; dwindling budgetary allocation. The librarians also identified some of the strategies to include performance at interview as benchmark; equity and fairness as benchmark; recruitment should be done according to relevant discipline; and having channels for reporting cases of corruption during recruitment. Based on the above findings the study recommended among others that recruitment and selection of qualified librarians should be done according to the laid down procedures.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.2
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• pp.125-136
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• 2017

This study focuses on a relative efficiency of 109 operating food companies out of 22 regions in Jeollanam-do. The relative efficiency has been analyzed by 5 input factors(capital, number of employees, annual labor costs, raw material purchase, and site area) and 2 output factors(annual exports and annual production of the companies in Jeollanam-do). This study suggests efficient companies which inefficient companies can benchmark to improve their system in short-mid-long term in phases. The main result of empirical analysis are as follows: Firstly, according to the Traditioanl DEA analysis, 7 companies out of 109 DMU indicate the optimal production scale in score 1 of CCR efficiency value, BCC efficiency value, and scale efficiency value. Secondly, a result from the Tier 1 step of inefficient companies by Post-DEA suggests that it would be better to apply each Tier step to the proper stage of the worst 5 inefficient companies such as Tier 3 step(short-term benchmark)${\rightarrow}$Tier 2 step(mid-term benchmark)${\rightarrow}$Tier 1 step(long-term benchmark) in step. This study expects that the result of the study can reduce the trial and error in inefficient part, lead to improvement, and have a big help in food exporting industry in the end.