• 응용통계연구
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• 제25권3호
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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.

• 산업경영시스템학회지
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• 제47권1호
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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.

• 상하수도학회지
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• 제29권6호
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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.

• 대한산업공학회지
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• 제28권1호
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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.

• 가정간호학회지
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• 제19권1호
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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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• 제25권2호
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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.

• 가정간호학회지
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• 제18권2호
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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.

• 한국식생활문화학회지
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• 제19권4호
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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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• 제12권2호
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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.

• 벤처창업연구
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• 제12권2호
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• pp.125-136
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• 2017

본 연구에서는 전남지역 22시군의 109개의 가동 식품수출업체를 분석 대상으로 상대적 효율성을 5개의 투입요소(자본금, 고용인원, 연간 인건비, 원료 구입비 및 부지면적)와 2개의 산출요소(전남식품수출업체의 연간수출액과 연간생산량)를 이용하여 분석하였다. Tier 분석을 통해 비효율적인 업체들이 단기-중기-장기적으로 실현가능성이 있는 단계별 벤치마킹 업체들을 제시하였다. 실증분석의 주요한 결과는 다음과 같다. 첫째, 전통적인 DEA 분석에 109개의 DMU 중에서 7개 업체가 CCR 값과 BCC 값이 모두 효율적인 값으로 규모의 효율성도 효율적으로 분석되어 최적의 생산규모를 나타내고 있다. 둘째, Post-DEA를 활용한 비효율적인 업체들의 Tier 1단계의 분석을 실시한 결과, 가장 비효율적인 5개 업체들의 Tier 분석결과 값을 단계별 Tier 3단계(단기적 벤치마킹)${\rightarrow}$Tier 2단계(중기적 벤치마킹)${\rightarrow}$Tier 1단계(장기적 벤치마킹)로 제시하였다. 비효율적인 전남식품수출업체들이 DEA 기본모형에서 제시한 효율적인 벤치마킹 업체들을 찾아냈지만 비현실적인 격차해소 가능성으로 인해 벤치마킹에 실패할 가능이 크다. 따라서 실현가능성이 있는 단계별 벤치마킹 업체들을 제시하고 이를 통해 식품산업발전을 위한 시행 착오를 줄일 수 있으며 각 업체들의 비효율성 부분에 대해서도 개선방안을 유도할 수 있어 종국적으로 장기적 경영개선에 큰 도움을 주고 향후 전남지역 식품수출기업들의 효율성 개선을 위한 기초적 자료로 활용 될 것으로 기대된다.