• International Journal of Quality Innovation
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• v.9 no.2
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• pp.11-30
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• 2008

The purpose of this study is to develop BSC model of social enterprise. Performance analysis tool of BSC have been brought over from the business world, designed and created from the perspectives of profit-based businesses. The BSC is a strategic performance measurement and management tool designed for the private sector acting as a communication/information and learning system, to measure 'where we are now' and 'where to aim for next'. It prescribes a plan for translating 'vision' and 'strategy' into concrete action across four perspectives at different stages, depending on the business. These perspectives are 'financial', 'customer', 'internal processes' and 'learning and growth', each of which is connected by cause-and-effect relationships that reflect the firm's strategy. Social aims of social enterprise are to accomplish desired outcomes which are to employ vulnerable people and to provide social services. The measurement factors of financial perspective are stable funding, efficiency of budgeting, stakeholders' financial supports, and trade profit. The measurement factors of customer perspective are government, social service users, employees, local communities, sup plier, social activity company, and partnership with external organizations. The measurement factors of internal process perspective are organizational culture, organizational structure/management, internal/external communication, quality of products and services, information sharing. The measurement factors of learning and growth perspective are training and development, management participation, knowledge sharing, leadership of CEO and manager, and learning culture.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1442-1445
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• 2005

Several test methods, including micro strain/deformation measurement techniques, have been studied to more reliably measure the micro properties in micro/nano materials. Therefore, in this study, the continuous measurement of in-plane tensile strain in micro-sized specimens of thin film materials was introduced using the micro-ESPI technique. TiN and Au thin films 1 and $0.47\;\mu{m}$ thick, respectively, were deposited on the silicon wafer and fabricated into the micro-sized tensile specimens using the electromachining process. The micro-tensile loading system and micro-ESPI system were developed to measure the tensile strain during micro-tensile test. The micro-tensile stress-strain for these materials was determined using the algorithm for continuous strain measurement. Furthermore, algorithm for enhancing the sensitivity to measurement of in-plane tensile strain was suggested. According to the algorithm for enhancement of sensitivity, micro-tensile strain data between interfringe were calculated. It is shown that the algorithm for enhancement of the sensitivity suggested in this study makes the sensitivity to the in-plane tensile strain increase.

• The KSFM Journal of Fluid Machinery
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• v.2 no.2 s.3
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• pp.19-26
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• 1999

Thermal output in a nuclear power plant is verified with calorimetric heat balance on the secondary plant. The calorimetry involves the precise measurement of the feedwater flow rate. However, the correct indication of feedwater flow rate obtained by a pressure-difference measurement across a venturi can be affected by instrument errors, fouling or a poorly developed velocity profile. This can result in an inaccurate mass flow rate and consequently an inaccurate estimate of power. The purpose of this study is to develop verification methods with accuracy better than $0.5\%$ for high precision flow measurement to be used for measuring feedwater flow rate. This chemical tracer method is a testing process that uses tracers which can be applied to quantify losses in electrical output due to the incorrect measurements of feedwater flow rate. And this system has good response to the variation of the flow rate. Accuracy of better than 0.5 percent can be expected for feedwater flow measurement, providing that the system can be stabilized during the test. This methodology is applicable to other flow systems well.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.119-130
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• 2010

Reconstruction analysis of traffic accident is done by analyzing diverse data such as the road, accident traces and damage on the automobile. Most data can be a variable in the process of analysis, and measurement error of the data occurs from the investigator, tool and the given environment. Therefore, accident analysis always has some risks of measurement uncertainty. This research quantify the uncertainty in traffic accident analysis by conducting repetitive measurement experiments for variables with high probability of uncertainly such as length (i.e. geometric structure of the road, tire marks) and coefficient of friction. This paper also suggests an analysis result for the uncertainly of photographic observation of automobile crush measurement. These statistical distributions can help determine appropriate ranges for the input data in order to estimate the accident reconstruction uncertainty.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.3
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• pp.219-228
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• 2008

Purpose: The purpose of this study was to develop a measurement scale of nursing competence for nurses working in general wards, and to test the validity and reliability of the scale. Method: A methodological study design was used, consisting of 3 steps as conceptual framework decision, measurement items development, and testing of validity and reliability. In order to verify content validity, 16 experts reviewed the concept of each competences and measurement items. The developed measurement items were tested from 301 nurses in one hospital. Factor analysis and item analysis were applied to establish the scale's construct validity and reliability. Result: The final scale consists of nine dimensions with 70 items. The overall scale reliability had a Cronbach's alpha of 0.98, and the demensions Cronbach's alpha ranged from 0.88 to 0.95. The factor loading of construct validity was from 0.40 to 0.83. The explained variance from the 9 extracted factors was 70.93% of the total variance, and final factors were labeled as critical thinking, resources management and professional development, ability of ward management, application of nursing process, ethical accountability, respectful consideration, patient centered approach, crisis management, and leadership. Conclusion: This measurement scale can be utilized to evaluate nursing competence for nurses working in general wards.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.13 no.1
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• pp.69-76
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• 1995

This study is the 3-D precision deformation measurement of a bridge, obtain results of precision control points by GPS and 3-D measurement system and develope efficientlty technices which can solve precision 3-D analysis by CRP In the result, we could overcome the problems of former control point measurement in the way of the combination system of GPS and 3-D measurement system to positioning decision of reference points and control points. Then we could symplify old measurement process on the 3-D deformation analysis of a linear structure and complement parted analysis fault of measurement instrument.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.117-124
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• 2023

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.65-70
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• 2024

Tool wear is considered an important issue in manufacturing and engineering, as worn tools can negatively impact productivity and product quality. Given that the wear status of tools plays a decisive role in the production process, measuring tool wear is a key task. Consequently, there is significant attention in manufacturing fields on the precise measurement of tool wear. Current domestic methods for measuring wear are limited in terms of speed and efficiency, with traditional methods being time-consuming and reliant on subjective evaluation. To address these issues, we developed a measurement module implementing the DeepContour algorithm, which uses image processing technology for rapid measurement and evaluation of tool wear. This algorithm accurately extracts the tool's outline, assesses its condition, determines the degree of wear, and proves more efficient than existing, subjective, and time-consuming methods. The main objective of this paper is to design and apply in practice an algorithm and measurement module that can measure and evaluate tool wear using image processing technology. It focuses on determining the degree of wear by extracting the tool's outline, assessing its condition, and presenting the measured value to the operator.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.E2
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• pp.66-73
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• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• Journal of the Korean Dietetic Association
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• v.14 no.2
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• pp.186-197
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• 2008

The aim of this study was to measure the brand images of contract foodservice management companies by identifying brand image attributes and then developing a measurement scale to measure the weight of these attributes. The measurement scale was developed by following a 5-stage process that included face-to-face interviews with experts, literature review, questionnaire surveys, verification of scale validity, exploratory factor analysis, and confirmatory factor analysis. A total of 137 items measuring brand image were collected: 37 items from studies of brand image and corporate image, 55 items from studies of contract foodservice management companies and 45 items from the internet and websites of contract foodservice management companies. A survey was then conducted to assess the validity and reliability of the questionnaire items. Ultimately, the 137 items were reduced to 40 items. The calculated Cronbach's alpha for the 40 brand image items was 0.934, demonstrating good internal consistency. Based on exploratory factor analysis (EFA), employee attitude, menu content, corporate image, dining location and ambience, along with 33 subattributes, were identified as brand image attributes. Employee attitude was the most significant attribute influencing brand image. After confirmatory factor analysis (CFA) and a review process, four brand image attributes and 33 subattributes were finalized and incorporated into the scale.