• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4778-4787
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• 2011

The purpose of this study to develop IT Outsourcing service quality evaluation measurement have been frequently used to apply a model KS-SQI in the service industry. Primary needs fulfillment, unexpected benefits, reliability, individual empathy, positive assistance, accessibility and physical environment were selected as independent variable, they evaluate IT outsourcing service quality in order to verify their suitability as a tool for IT outsourcing service evaluation measurement, to analyze how that affects IT outsourcing satisfaction, and to investigate whether affecting IT outsourcing satisfaction on recontract intentions. To validate the hypothesis by path analysis conducted between variables using LISREL, primary needs fulfillment, reliability, individual empathy, positive assistance, accessibility and physical environment have significant effect on IT outsourcing satisfaction, but unexpected benefits don't have effect on IT outsourcing satisfaction, and IT outsourcing satisfaction showed significant effect on recontract intentions. Six Measurement tools has been proved to be suitable as a IT outsourcing service quality evaluation tool. Contribution of this study to evaluate the quality of IT outsourcing services, KS-SQI model developed by applying the measuring tool was achieved theoretical extensions and practical aspects of a recontract with the provider of IT outsourcing and IT outsourcing services for as a tool to assess the quality of can be used.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• International Journal of Oral Biology
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• v.48 no.2
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• pp.9-18
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• 2023

The rapid detection of bacteria in the oral cavity, its species identification, and bacterial count determination are important to diagnose oral diseases caused by pathogenic bacteria. The existing clinical microbial diagnosis methods are time-consuming as they involve observing patients' samples under a microscope or culturing and confirming bacteria using polymerase chain reaction (PCR) kits, making the process complex. Therefore, it is required to analyze the development status of substances and systems that can rapidly detect and analyze pathogenic microorganisms in the oral cavity. With research advancements, a close relationship between oral and systemic diseases has been identified, making it crucial to identify the changes in the oral cavity bacterial composition. Additionally, an early and accurate diagnosis is essential for better prognosis in periodontal disease. However, most periodontal disease-causing pathogens are anaerobic bacteria, which are difficult to identify using conventional bacterial culture methods. Further, the existing PCR method takes a long time to detect and involves complicated stages. Therefore, to address these challenges, the concept of point-of-care (PoC) has emerged, leading to the study and implementation of various chair-side test methods. This study aims to investigate the different PoC diagnostic methods introduced thus far for identifying pathogenic microorganisms in the oral cavity. These are classified into three categories: 1) microbiological tests, 2) microchemical tests, and 3) genetic tests. The microbiological tests are used to determine the presence or absence of representative causative bacteria of periodontal diseases, such as A. actinomycetemcomitans, P. gingivalis, P. intermedia, and T. denticola. However, the quantitative analysis remains impossible, and detecting pathogens other than the specific ones is challenging. The microchemical tests determine the activity of inflammation or disease by measuring the levels of biomarkers present in the oral cavity. Although this diagnostic method is based on increase in the specific biomarkers proportional to inflammation or disease progression in the oral cavity, its commercialization is limited due to low sensitivity and specificity. The genetic tests are based on the concept that differences in disease vulnerability and treatment response are caused by the patient's DNA predisposition. Specifically, the IL-1 gene is used in such tests. PoC diagnostic methods developed to date serve as supplementary diagnostic methods and tools for patient education, in addition to existing diagnostic methods, although they have limitations in diagnosing oral diseases alone. Research on various PoC test methods that can analyze and manage the oral cavity bacterial composition is expected to become more active, aligning with the shift from treatment-oriented to prevention-oriented approaches in healthcare.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.347-357
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• 2022

This study was attempted to identify the health-related quality of life of Chronic Obstructive Pulmonary Disease (COPD) patients and factors influencing the quality of life, focusing on Health-related quality of life with 8 items (HINT-8). The subjects of this study were 451 adults aged 40 years or older who performed lung function tests and whose ratio is less than 0.7 by measuring forced respiratory volume in 1 second [FEV₁] to forced vital capacity in the 2019 National Health and Nutrition Examination Survey, It was analyzed using SAS program. As a result, both the HINT-8 index and EuroQol five-dimensions 3-level version (EQ-5D-3L) index were appropriate as tools to measure the health-related quality of life in COPD patients, and the factors affecting the health-related quality of life were age, gender, income, and smoking status, comorbidities, stress, and subjective health status. Therefore, in order to improve the health-related quality of life of COPD patients, an individualized management program suitable for the characteristics of subjects such as the low-income class and the elderly, including smoking cessation education and stress management, should be developed and applied.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.1-11
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• 2023

The purpose of this study is to develop and validate a tool that measures the satisfaction of virtual training learners' use of virtual training content. To this end, 491 copies of the basic questions derived from the satisfaction questions used by the K University Online Lifelong Education Center were used for the final analysis by conducting an online survey of learners who accessed STEP, the K University Online Lifelong Education Center portal. The 491 copies of data finally used were analyzed by methods such as basic question analysis, exploratory factor analysis, reliability analysis, and confirmatory factor analysis. First, in the basic question analysis, there were no questions that exceeded the acceptance criteria of an average of 4 points or more, skewness ±2, and kurtosis ±4. Second, the correlation coefficient for each sub-factor of virtual training content satisfaction derived after exploratory factor analysis was good as r=.682 to .822 (p<.01). The reliability coefficient for each sub-factor is content .849, content utilization .922, System and Operations Support .841, Intention to Continue Utilization .920, the overall reliability is. It was very high at .956 Fifth, as a result of confirmatory factor analysis, the compositional conceptual diagram is. It was .842 to .926, higher than the recommended standard of .7, and the average variance extraction degree. It appears to be .640 to .796, higher than the recommended standard of .5, which can be seen as representative of each constituent concept. As a result of verifying the validity of virtual training learners' content satisfaction recruitment, four factor models were derived: content substance, content utilization, system and operation support, and intention to continue use. This study is meaningful in that it empirically developed a tool to measure content satisfaction of virtual training learners and provided a reference frame and criteria.

• Journal of muscle and joint health
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• v.5 no.2
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• pp.238-252
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• 1998

Reumatic arthritis is a disease with joint pain being one of the key symptoms. The patient suffers from the pain, stiff sensation and edema due to the inflammation taking Place In one or more joints. Accompanying these problems are fatigue, unusual exhaustion, fever, tachycardia and weakness. Inaddition, joints are often deformed and muscles shrink along with the progress of edema, coupled with depression and psychological instability resulting from the loss of the mobile function and limitations on the daily life. Some patients become fed up with the long and hard flight with the disease and just give up, which aggravates the symptoms. Others come to the hospital only when the conditions have become serious. We need to prevent these and guide the patients in the right direction. Against this backdrop, this study aims to look into the relations between the knowledge on the part of the patients together with their feeling of self-efficacy and the compliance. The results are expected to help the patients improve their life, In addition to providing useful materials for setting up appropriate plan for nursing intervention. The study was conducted by distributing questionnaire to 88 patients selected from the out-patient department of a university hospital in Inchon, from April 6 to 27, 1998. The following tools were used the yardstick of self-efficacy, developed in 1997 by the Society for the Health of Rheumatism Patients, was used for measuring the levels of knowledge and the feeling of self-efficacy. The degree of compliance was measured by the data collected from documents in addition to the results of the analysis of the interviews with the patients. The reliability of the tools was confirmed. In the analysis, the general characteristics were expressed in figures and percentages. The levels of knowledge, feeling of self-efficacy, and compliance were expressed in the average values and standard deviations. The relations among the variables following the general characteristics were analysed by the t-test and one-way ANOVA. The Pearson correction coefficient was used for the analysis of factors. Multiple-loop analysis was used to identify the variables affecting the compliance. The following are the results of this study. 1. Among the 88 patients, 18 were men and the remaining 70 were women, with a ratio 1 : 3.87. Regarding the age groups, 23 were between 50 and 59 years old, with those between 50 and 69 accounting for 51.1% of the total. High school graduates or higher amounted to 58%. Religious patients was 67% or 59 persons. Fifty nine percent were unemployed, and 58.3% (49 persons) had two children or fewer. The period of suffering from rheumatism varied between 2 months and IS years, with 70% less than years. 2. The average figure In relation to the of knowledge was 17.63 points over 30 or 58. 76%, which means a medium level. 3. The average figure of the feeling of self-efficacy was 60.06 points. 4. The level of compliance was 3.26, which was above average. 5. The relation between the feeling of self-efficacy and compliance showed an "r" value of 0.37, which was significant. It means that the higher the feeling, the greater the compliance points. 6. The analysis of the knowledge level revealed that the difference is found only between the college graduates and junior-high graduates or lower. 7. The feeling of self-efficacy varied along with the age and education level. 8. The general characteristics of patients as discussed above did not show significant difference with the compliance. 9. Regarding the elements influencing the compliance, the number of children, period of suffering, income, age, feering of self-efficacy, knowledge, and compliance had 54% of significance. In conclusion, rheumatism victims can lead a better life if they are appropriately educated, based on efficient training program from the early days of the disease ; if they become able to manage themselves thanks to the training ; and if they are helped by a program focusing on the increase of the feeling of self-efficacy aimed at changing patient's behavior.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.77-85
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• 2014

A goal of Bizcool entrepreneurship education targeting on the youth falls on letting understand the process of starts-up, enhance entrepreneurship will and their business creativities rather than training trivial starts-up skills such as writing business plan for successful starts-up. The effects of education enable Bizcoo students to recognize rightly the concept of starts-up training and lead to spread out demand for entrepreneurship education. The feedback check-up for how entrepreneurship education affects students getting through of it is necessary and possible to bring its' improvement alternatives. Despite of such highlight, not many measuring tools and indexes of evaluating an effectiveness of entrepreneurship education are developed and studied up until. This research suggests for the optimal indexes for them. In specific, this research 49 the first question sets of evaluating an effectiveness of entrepreneurship education classified 3 large categories and 11 following sub categories each of them such as entrepreneurship orientation, creativity, entrepreneurship preparing activities etc,. representing embedding education effects though entrepreneurship education. This research carry out the empirical survey research utilizing driven question sets against 5 different Bizcools sampling 287 students. The survey research delivers the final 3 large categories and 8 following sub categories(Innovativeness, risk-taking, problem-solving potent, cooperative decision-making potent, efficient behavior capacity, data collecting potent, career search, starts-up search and preparation), and 38 measuring indexes by search and confirming factor analysis. This research never drop the confidence test over each indexes and obtain the proper figures. Last but not least, this research confirm the gap between starts-up club members and non members as to an effectiveness of entrepreneurship education and 9 different indexes.

• The korean journal of orthodontics
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• v.27 no.5 s.64
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• pp.815-824
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• 1997

The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.65-73
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• 2019

In order to increase the production efficiency of the ship and shorten the production cycle, it is important to evaluate the accuracy of the ship components efficiently during the drying cycle. The accuracy control of the block is important for shortening the ship process, reducing the cost, and improving the accuracy of the ship. Some systems have been developed and used mainly in large shipyards, but in some cases, they are measured and managed using conventional measuring instruments such as tape measure and beam, optical instruments as optical equipment, In order to perform accuracy control, these tools and equipment as well as equipment for recording measurement data and paper drawings for measuring the measurement position are inevitably combined. The measured results are managed by the accuracy control system through manual input or recording device. In this case, the measurement result is influenced by the work environment and the skill level of the worker. Also, in the measurement result management side, there are a human error about the lack of the measurement result creation, the lack of the management sheet management, And costs are lost in terms of efficiency due to consumption. The purpose of this study is to improve the working environment in the existing accuracy management process by using the augmented reality technology to visualize the measurement information on the actual block and to obtain the measurement information And a smart management system based on augmented reality that can effectively manage the accuracy management data through interworking with measurement equipment. We confirmed the applicability of the proposed system to the accuracy control through the prototype implementation.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.