• Journal of Information Management
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• v.41 no.3
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• pp.45-66
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• 2010

The purpose of this study is to develop service quality measurement model(DL-SQI model) which are able to measure objectively service quality of digital libraries in Korea and to measure user perceived service quality performance with DL-SQI model. This study also investigates the influence of service quality on customer satisfaction and customer loyalty. Before measurement, two principal rules and indicator formula were made to measure the service quality. Finally service quality of three digital libraries selected as samples was measured and analyzed in various points of view. It was developed a DL-SQI Consequences Model and testified it through path analysis using structural equation model.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.226-233
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• 2023

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

• Journal of Korean Library and Information Science Society
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• v.41 no.1
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• pp.121-147
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• 2010

The purpose of this study is to develop and prove service quality measurement model and indicators which are able to measure objectively service quality of digital libraries in Korea. Literature review and Delphi survey are used to investigate service quality dimensions. User perceived service quality performance was measured to validate DL-SQI model with three digital libraries. Finally DL-SQI(Digital Library-Service Quality Index) model was developed which is composed of four primary dimensions. The survey results reveal that reliability coefficient is 0.8 which means high reliability of survey and it suggests that DL-SQI model based on the above dimensions is proved through confirmatory factor analysis.

• Journal of Veterinary Clinics
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• v.17 no.1
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• pp.28-31
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• 2000

An animall health monitoring system in Gyeongnam area(near Chinju) was studied to analysis of biochemical risk factors in 617 herds. Clinical serum factors such as glutamate oxaloacetate transaminase(GOT), glutamate pyruvate transaminase(GPT), Ca, P, Mg, glucose, and cholesterol were measured with automatic biochemical analyzer(Ra-X7T Techmmicon, USA). In serum analysis, 613 cattle were within normal llimits(GOT: 9.5-85 IU-dl, GPT: 25-77IU/dl, total protein: 5.8-8.5g/dl, Ca: 4.2-12.4mg/dl, P: 4.6-9.7mg/dl, Mg: 1.5-3.0mg/dl, glucose: 48-120mg/dl, Cholesterol: 70-170mg/dl), the other cattle showed high glucose and high cholesterol level. It is proposed that clinical serum factors to be estimated may be valuable for developing of animal health monitoring system model.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.6 no.1
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• pp.88-96
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• 1996

This study was conducted to establish model between lead and ZPP concentration in blood of workers exposed to lead. Workers employed in secondary smelting manufacturing industry showed $85.1{\mu}g/dl$ of blood lead level, exceeding $60{\mu}g/dl$, the Criteria for Removal defined by Occupational Safety and Health Act of Korea. Average blood lead level of workers in the battery manufacturing industry was $51.3{\mu}g/dl$, locating between $40{\mu}g/dl$ and $60{\mu}g/dl$, the Criteria for Requiring Medical Removal. Blood lead level of in the litharge and radiator manufacturing industry was below $40{\mu}g/dl$, the Criteria Requiring Temporary Medical Removal. Blood lead levels of workers by industry were Significantly different(p<0.05). 50(21 %) showed blood lead levels above $60{\mu}g/dl$, the Criteria for Removal and 66(27.7 %) showed blood lead levels between the Criteria for Requiring Medical Removal, $40-60{\mu}g/dl$. Thus, approximately 50 percent of workers indicated blood lead levels above $40{\mu}g/dl$, the Criteria Requiring Temporary Medical Removal and should receive medical examination and consultation including biological monitoring. Average ZPP level of workers employed in the secondary smelting industry was $186.2{\mu}g/dl$, exceeding above $150{\mu}g/dl$, the Criteria for Removal. Seventy seven of all workers(32.3 %) showed ZPP level above $100-150{\mu}g/dl$, the Criteria for Requiring Medical Removal. The most appropriate model for predicting ZPP in blood was log-linear regression model. Log linear regression models between lead and ZPP concentrations in blood was Log ZPP(${\mu}g/dl$) = -0.2340 + 1.2270 Log Pb-B(${\mu}g/dl$)(standard error of estimate: 0,089, ${\gamma}^2=0.4456$, n=238, P=0.0001), Blood-in-lead explained 44.56 % of the variance in log(ZPP in blood).

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.31-42
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• 2010

GPM(Generic Product Model) developed by Hitachi in Japan is a common data model to integrate and share life cycle data of nuclear power plants. GPM consists of GPM core model, an abstract model, implementation language for the model and reference library written in the language. GPM core model has a feature that it can construct a semantic network model consisting of relationships among objects. Initial GPM developed and provided GPML as an implementation language to support the feature of the core model, but afterwards the GPML was replaced by GPM-XML based on XML to achieve data interoperability with heterogeneous applications accessing a GPM data model. However, data models written in GPM-XML are insufficient to be used as a semantic network model for lack of studies which support GPM-XML and enable the models to be used as a semantic network model. This paper proposes OWL as the implementation language for GPM core model because OWL can describe ontologies similar to semantic network models and has an abundant supply of technical standards and supporting tools. Also, OWL which can be expressed in terms of RDF/XML based on XML guarantees data interoperability. This paper uses OWL DL, one of three sublanguages of OWL, because it can guarantee complete reasoning and the maximum expressiveness at the same time. The contents of this paper introduce the way how to overcome the difference between GPM and OWL DL, and, base on this way, describe how to convert the reference library written in GPML into ontologies based on OWL DL written in RDF/XML.

• Journal of Information Management
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• v.30 no.3
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• pp.27-43
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• 1999

The digital library operated in the environment of computer-mediated-communication offered new successful alternative plans for the field and communication methods of the information services that have been provided by the traditional library and this causes the traditional library to move to the new paradigm. In this situation, the information services of the digital library raised the necessity for the communication channels that would cope actively on the spot and for the extention of information services that would supply an unspecified number of the general public with a considerable extention of information services that neglect time and space. This study looked into the communication channels in general for interactions between the digital library and the users in the environment of computer-mediated-communication and observed patterns of communication chennels that the digital library could supply. For the development of the communication model in the digital library, the study presented the communication model for effective information services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.627-634
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• 2016

The aim of this study was to examine the impact of the obesity status on serum uric acid in health check-up examinees. The study subjects were 1,118 adults, 20 years and over (636 males, 482 females), the health package check-up at the general hospital in Gwang-Ju from January to December, 2011. This study assessed the serum uric acid, blood urea nitrogen, and creatinine levels, as well as the anthropometric variables (SBP, DBP, and BMI). In a model I, after adjusting for the variables, such as age, SBP, DBP, TC, TG, HDL-C, and FBG, the mean uric acid level ($M{\pm}SE$) increased with increasing obesity status in males (p<0.001) or females (p=0.036). In model II, after adjusting for BUN and creatinine, the mean uric acid ($M{\pm}SE$) in males increased with increasing obesity status (Normal weight [BMI <$23.0kg/m^2$], $4.89{\pm}0.07mg/dl$; overweight [BMI $23.0-24.9kg/m^2$], $5.01{\pm}0.09mg/dl$; obesity [BMI ${\geq}25.0kg/m^2$], $5.35{\pm}0.08mg/dl$) (p<0.001). In the females, however, the mean uric acid ($M{\pm}SE$) did not increase with increasing obesity status (Normal weight, $5.03{\pm}0.08mg/dl$; overweight, $5.19{\pm}0.11mg/dl$; obesity, $5.27{\pm}0.09mg/dl$) (p=0.191). In conclusion, these results suggest that an increase in obesity status is associated with an increase in the serum uric acid levels in males, but not in females.

• Journal of Chest Surgery
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• v.57 no.5
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• pp.460-466
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• 2024

Background: Numerous studies have investigated methods of predicting postoperative pulmonary complications (PPCs) in lung cancer surgery, with chronic obstructive pulmonary disease (COPD) and low forced expiratory volume in 1 second (FEV₁) being recognized as risk factors. However, predicting complications in COPD patients with preserved FEV₁ poses challenges. This study considered various diffusing capacity of the lung for carbon monoxide (DL_CO) parameters as predictors of pulmonary complication risks in mild COPD patients undergoing lung resection. Methods: From January 2011 to December 2019, 2,798 patients undergoing segmentectomy or lobectomy for non-small cell lung cancer (NSCLC) were evaluated. Focusing on 709 mild COPD patients, excluding no COPD and moderate/severe cases, 3 models incorporating DL_CO, predicted postoperative DL_CO (ppoDL_CO), and DL_CO divided by the alveolar volume (DL_CO/VA) were created for logistic regression. The Akaike information criterion and Bayes information criterion were analyzed to assess model fit, with lower values considered more consistent with actual data. Results: Significantly higher proportions of men, current smokers, and patients who underwent an open approach were observed in the PPC group. In multivariable regression, male sex, an open approach, DL_CO <80%, ppoDL_CO <60%, and DL_CO/VA <80% significantly influenced PPC occurrence. The model using DL_CO/VA had the best fit. Conclusion: Different DL_CO parameters can predict PPCs in mild COPD patients after lung resection for NSCLC. The assessment of these factors using a multivariable logistic regression model suggested DL_CO/VA as the most valuable predictor.