• Educational Technology International
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• v.17 no.1
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• pp.1-37
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• 2016

The purpose of this study was to develop a MOOC design model that would improve the current practice of MOOC development in Korea by specifying easy-to-use course development procedures and guiding strategies. Following Richey and Klein (2007)'s conceptual model development procedure, the first step was to perform critical review of relevant literature and observe typical MOOC development processes. As a result, the initial model was developed. The second step was to conduct the expert review with five educational technology and MOOC researchers to secure the internal validity of the model. Based on the experts' suggestions, the model was revised and once again reviewed by the same experts. This process resulted in the development of the 2^nd version of model. The third step was to carry out external validation research in order to test the effectiveness, efficiency, and usability of the model. A basic model may be confirmed or corrected based on examination of its results. Consequently, the model was elaborated as the final model. In the final model, 6 procedural phases and 9 specific steps were included. The six procedural phases are: Analysis (1st Iteration), Design, Development (Course Development), Implementation, Evaluation, and Analysis (2nd Iteration), a slight variation of ADDIE model. The specific steps include: 1) Goal Setting, 2) Environment Analysis, 3) Content Design, 4) Style Design, 5) Course Development, 6) Implementation Plan, 7) Course Implementation, 8) Summative Evaluation, and 9) Need Reflection. The study concluded with suggestions for further research and application of the MOOC design model.

• Atmosphere
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• v.24 no.3
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• pp.365-378
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• 2014

The limits of S-band dual-polarization radars in Korea are not reflected on the recent weather forecasts of Korea Meteorological Administration and furthermore, they are only utilized for rainfall estimations and hydrometeor classification researches. Therefore, this study applied four merging methods [SA (Simple Average), WA (Weighted Average), SSE (Sum of Squared Error), TV (Time-varying mergence)] to the QPE (Quantitative Precipitation Estimation) model [called RAR (Radar-AWS Rainfall) calculation system] using single-polarization radars and S-band dual-polarization radar in order to improve the accuracy of the rainfall estimation of the RAR calculation system. As a result, the merging results of the WA and SSE methods, which are assigned different weights due to the accuracy of the individual model, performed better than the popular merging method, the SA (Simple Average) method. In particular, the results of TVWA (Time-Varying WA) and TVSSE (Time-Varying SSE), which were weighted differently due to the time-varying model error and standard deviation, were superior to the WA and SSE. Among of all the merging methods, the accuracy of the TVWA merging results showed the best performance. Therefore, merging the rainfalls from the RAR calculation system and S-band dual-polarization radar using the merging method proposed by this study enables to improve the accuracy of the quantitative rainfall estimation of the RAR calculation system. Moreover, this study is worthy of the fundamental research on the active utilization of dual-polarization radar for weather forecasts.

• The Journal of Industrial Distribution & Business
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• v.10 no.7
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• pp.71-82
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• 2019

Purpose - This study aims to identify the priorities of medical service quality improvement by customer satisfaction characteristics and potential customer satisfaction improvement (PCSI) index based on the dualistic quality classification of Kano Model (1984) for Comprehensive Health Screeening Center in General Hospitals and Centers only for Comprehensive Health Screening and suggest a direction for future improvement. Research design, data, and methodology - Through advanced research on health screening medical service quality, this study set four service quality factors, including tangible, human, process and supportive factors, and 39 measurement items. Based on these items, the study used 117 questions, which consist of dualistic quality factors, customer satisfaction coefficients, positive and negative questions for PCSI index and questions for current satisfaction. 300 effective samples were collected for adults in their 20s who experienced health screening service in Seoul, Gyeonggi-do and Incheon within the past two years. Collected data were input in the quality evaluation duality table to categorize quality factors and calculate customer satisfaction coefficients by Timko(1993). The study also analyzed PCSI index in comparison with current satisfaction and identified priorities in quality improvement. Results - It was found that the most urgent factors to improve the quality in both groups were adequate waiting hours and emergency response for complications, which are process factors classified as unitary quality. It is urgently needed to improve the quality as the PCSI index was high in supportive factors (complaint response team) as attractive quality in Comprehensive Health Screening Center in General Hospitals and in process factors (prevention of infection) as unitary quality in Centers only for Comprehensive Health Screening. As the PCSI index was low in space use as a tangible factor, it was found that the current level can be maintained instead of improvement. Conclusions - To improve the health screening medical service quality, it is required to focus on process factors (adequate waiting hours, emergency response for complications, prevention of infection) and supportive factors (complaint response team) among service qualities perceived by users. It is proposed to ensure continuous efforts to manage and reinforce priorities as a direction for future improvement in health screening service.

• Journal of the Korean Solar Energy Society
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• v.37 no.3
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• pp.47-59
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• 2017

As the global warming threats to humanity, renewable energy is considered the key solution to overcome the climate change. In this circumstance, distributed PV systems are being expanded significantly its market share in the renewable energy industry. The performance of inverter is the most important component at PV system and numerous researches are focusing on it. In order to improve the inverter, PV simulator is an essential device to experiment under various load and conditions. This paper proposes the PV Power-Hardware-In-Loop simulator (PHILS) with real-time processing converted electrical and mathematical models to improve computation speed. Single-diode PV model is used in MATLAB/SIMULINK for the PV PHILS to boosting computation speed and dynamic model accuracy. In addition, control algorithms for sub-components such as DC amplifier, measurement device and several interface functions are implemented in the model. The proposed PV PHILS is validated by means of experiments with commercial PV module parameters.

• The KIPS Transactions:PartA
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• v.18A no.5
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• pp.181-192
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• 2011

Information superiority is an essential factor in modern warfare and it can be archived by efficient information exchange between systems. Various computing systems are installed on the today's navy vessels. However, it is hard to improve interoperability and efficiency of information exchange since the configurations of installed systems are varying. The military standard and commercial standard are mix-used between systems. In this paper, we propose an information exchange architecture based on Pub/Sub model as a communication middleware to improve interoperability as well as enhancing scalability. We also propose a novel tree matching algorithm to improve a performance of PubSub broker. In the proposed algorithm, each tree nodes have information about predicates of subscription that can reduce event matching time. The performance evaluation results show our proposed algorithm reduces time for matching predicates compare with other algorithms.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.145-161
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• 2014

Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.239-249
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• 2013

The role of software process is getting more important to make good quality softwares. One of the measures to improve the software process is Defect Removal Efficiency(DRE). DRE gives a measure of the development team ability to remove defects prior to release. It is calculated as a ratio of defects resolved to total number of defects found. Software Engineering Levels are usually decided by CMMI Model. The model is designed to help organizations improve their software product and service development, acquisition, and maintenance processes. The score of software engineering levels can be calculated by CMMI model. The levels are composed of the three groups(absent, average, and advanced). This study is to find if there is any difference among the three categories in term of the result of software engineering levels on DRE. We propose One way ANOVA to analyze influence of software engineering levels on DRE. Bootstrap method is also used to estimate the sampling distribution of the original sample because the data are not sampled randomly. The method is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample. The data were collected in 106 software development projects by the survey. The result of this study tells that there is some difference of DRE among the groups. The higher the software engineering level of a specific company becomes, the better its DRE gets, which means that the companies trying to improve software process can increase their good management performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.17-30
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• 2021

In the context of Sharing Accommodation has become a new type of accommodation choice for customers. The purpose of this study is to improve the existing defects of Sharing Accommodation Services through insight into the pain points of customer experience, so as to improve customer satisfaction. In this study, Airbnb and Tujia were selected as the subjects for comparative study. By collecting and sorting out references, the research background of Sharing Accommodation is analyzed in depth. Research methods of Service Design, such as Customer Journey Map and Service Blueprint, are adopted to gain insight into customer needs, identify pain points and propose hypothesis of service optimization. Tools such as Kano Model and Potential Customer Satisfaction are used to test and determine three schemes for optimizing the service. Finally, the results are displayed through Service Scenario. The research results can help operators of Sharing Accommodation to identify and improve the elements of service and provide a higher quality customer experience, thus promoting the healthy development of Sharing Accommodation market.

• Korean Journal of Exercise Nutrition
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• v.23 no.3
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• pp.29-38
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• 2019

[Purpose] Effective nutritional intervention can help reduce the risk of nutritional problems and improve athletic performance in adolescents. The five A's (assess, advise, agree, assist, and arrange) model is widely used as the theoretical framework for advice on nutrition, smoking, drinking, and physical activity and it recommends that practitioners in primary health care promote behavior change to facilitate positive outcomes. This model has also been useful in understanding the underlying processes of behavior change. This study aimed to develop both a novel evidence-based nutritional intervention protocol, rooted in sound nutritional theory, and a customizable nutritional intervention program to support sustainable healthy eating, enhance nutrient intake, and improve athletic performance in adolescent athletes. [Methods] In this study, we adapted the 5 A's behavioral change model and motivational interview to develop a theoretical framework to help adolescent athletes change their behavior and achieve their goals. [Results] During each step of the 5 A's protocol, a customized nutritional intervention protocol was developed by nutrition experts for each of adolescent athletes. Each plan was developed to improve the eating habits of adolescent athletes through group education and counseling. All nutritional counseling sessions were designed to enable participants to apply nutritional knowledge and practical action plans to their training and competition conditions to enable each of them to achieve individual athletic goals and facilitate self-management. [Conclusion] A theoretical and evidence-based nutritional intervention protocol was developed to identify and address obstacles to healthy dietary habits in adolescent athletes. This could be used as the basis for further studies aimed at improving nutrient intake and athletic performance in adolescent athletes.