• Korean Journal of Materials Research
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• v.33 no.7
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• pp.273-278
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• 2023

In this study, based on the saturation magnetic flux density experimental values (B_s) of 622 Fe-based bulk metallic glasses (BMGs), regression models were applied to predict B_s using artificial neural networks (ANN), and prediction performance was evaluated. Model performance evaluation was investigated by using the F1 score together with the coefficient of determination (R² score), which is mainly used in regression models. The coefficient of determination can be used as a performance indicator, since it shows the predicted results of the saturation magnetic flux density of full material datasets in a balanced way. However, the BMG alloy contains iron and requires a high saturation magnetic flux density to have excellent applicability as a soft magnetic material, and in this study F1 score was used as a performance indicator to better predict B_s above the threshold value of B_s (1.4 T). After obtaining two ANN models optimized for the R² and F1 score conditions, respectively, their prediction performance was compared for the test data. As a case study to evaluate the prediction performance, new Fe-based BMG datasets that were not included in the training and test datasets were predicted using the two ANN models. The results showed that the model with an excellent F1 score achieved a more accurate prediction for a material with a high saturation magnetic flux density.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.63-63
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• 2017

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.224-226
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• 2003

In this paper, we succeeded SNP discrimination of DNA hybridization on microarray using new electrochemical system. Using the electrochemical method with a label-free DNA has Performed DNA chip microarray. This method is based on redox of an electrochemical ligand. We developed scanning system with high performance.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1324-1327
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• 2009

Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

• Quality Improvement in Health Care
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• v.10 no.2
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• pp.164-175
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• 2003

Objectives: To evaluate the performance of models to predict AMI patients death using severity adjustment measures in Korea. Methods: Medical records of 861 patients treated by AMI in 7 general hospitals during 1996 and 1997 were reviewed by trained nurses. We measured the severity of patients by APACHE III, MedisGroups, CSI and DS. Using each severity method a predictive mortality for each patient was calculated from a logistic regression model including the severity score. The statistical performance of each severity method model was evaluated by using c-statistics and R2. For each hospital, z scores compared actual and expected mortality rates. Results: The overall in-hospital mortality was 14.5%, ranged from 10.0% to 22.2%. The distributions of severity scores for each method was significantly different by hospitals. The four severity-adjusted models to predict AMI patients death varied in their statistical performance for discrimination power of patients death. Order of Severity-adjusted mortality rates and z scores by four severity measures was different. Conclusion: Severity-adjusted mortality rates of AMI patients might be applied as an indicator for hospital performance evaluation in Korea. Because different severity methods frequently produce different impressions about relative hospital performance, more studies has to be done to use it as quality indicator and more attention should be paid to select appropriate severity measures.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.2
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• pp.165-175
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• 2007

Performance indicators haven't been used for the assessment of the wastewater treatment facility or management in Korea yet, therefore they are going to be important parts in wastewater utilities because they are used to understand present situation and to compare one with other wastewater utilities. In this study, we used performance indicators to assess the condition of wastewater utilities and they were divided into four categories (A, B, C, and D). A category represented the condition of the planning & construction and composed of wastewater supply, disaster defence and employees. B category represented maintenance of wastewater utilities and were composed of manhole, sewer, and technical employees. C category showed the operation efficiency of wastewater utilities and D category represented the environmental load. To analyze the situation of wastewater utilities overall, cluster analysis was performed using four categori' es indicators. And CCC (Cubic Clustering Criterion) and R-square were used to decide the proper number of clusters, and wastewater utilities of 48 cities were divided into 5 groups(I, II, III, IV, and V groups). Each cluster was analyzed by average and standard deviation to understand the situation of wastewater utilities. A group analysis showed that IV and V clusters were insufficient, B group showed that I and IV groups were insufficient, C group showed all clusters are above average, and D group was also like C group.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.305-311
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• 2021

The purpose of this study is to examine and analyze product innovation and process innovation as an indicator of innovation that affects the performance of small and medium enterprises (SMEs). Government policy as a moderator of the effect of innovation on performance. This research was conducted during the COVID-19 pandemic. The population in this study are SMEs that produce clothes and t-shirts in Indonesia. Data collection is done through questionnaires and direct interviews. Online questionnaires were given to the managers and business owners. The sampling technique used is purposive sampling based on certain conditions of the research object, and in this study 100 business units were selected. The result of loading factor correlation between indicator and latent construct is significant. Hypothesis which explored the linear relationship between the construct variables was tested. Structural Equation Modeling (SEM) was used. The results of this study indicate that there is a positive relationship between innovation and business performance, and government policies have an important role as a full moderator in this relationship. The study findings concluded that the government policies are an important instrument in supporting the development of SMEs by innovating product and process innovation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.17-25
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• 2021

Ammunition Demilitarization facility (ADF) should be set up the feasible goals and continue to operate, taking into account non-profit characteristics. However, due to the lack of performance measurement methods in ADF, which are essential to national policy at a significant cost each year, the reliability of the evaluation results can be insufficient. In this paper, the Balanced Score Card (BSC) method was applied that could be evaluated to reflect the financial and non-financial features. The relevant literature research and army regulations reflected the results of various interviews of the expert group. The extraction of success performance area in ADF was confirmed using the BSC method and the Decision Variable (DV) candidate was created to use regression for selecting the DV. Additionally, the key performance indicator was presented by verification the feasibility of content by conducting the survey of experts. The implications of this paper are as follows. First, the proposed BSC model was found to be suitable for practical use in ADF reflecting the non-profit characteristics. Second, accurate evaluation of ADF can contribute to long-term development of ADF. Finally, it can be applied to the management process of the other military sector, so it can be expected to play a role in providing basic data and spreading it to other areas.

• Culinary science and hospitality research
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• v.15 no.4
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• pp.259-272
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• 2009

The purpose of this research is to provide practical implications for the management of the contracted foodservice business by developing a key performance indicator(referred to herein as a K.P.I.) which is to measure the performance of management of contracted foodservice business in Korea. For this study, a KPI is developed in different perspectives by conducting the delphi-3round test with industry professionals who have more than 8 year job experience at contracted foodservice business located in Korea. The KPI that was developed as a result of this research will be able to help contracted foodservice business in Korea to set a concrete direction to focus on in preparing for the future economic environment, and to utilize the KPI in indicating an area on which they must concentrate their capital. In addition, the KPI will help contracted foodservice business executives to clearly evaluate current and future value of existing contracted foodservice business, thus providing accurate standards in M&A. However, this research has a limitation in proving directions of KPI despite its own meaning because there was no actual proof of relationship between contracted foodservice business of strategies in Korea.

• Smart Structures and Systems
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• v.17 no.2
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• pp.347-361
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• 2016

A two-stage method for damage detection in truss systems is proposed. In the first stage, a modal residual vector based indicator (MRVBI) is introduced to locate the potentially damaged elements and reduce the damage variables of a truss structure. Then, in the second stage, a differential evolution (DE) based optimization method is implemented to find the actual site and extent of damage in the structure. In order to assess the efficiency of the proposed damage detection method, two numerical examples including a 2D-truss and 3D-truss are considered. Simulation results reveal the high performance of the method for accurately identifying the damage location and severity of trusses with considering the measurement noise.