• Korean Journal of Adult Nursing
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• v.17 no.3
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• pp.411-424
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• 2005

Purpose: The purpose of this study was to develop and evaluate e-EBPP(Evidence-based Practice Protocol) system for nursing care for patients with dementia to facilitate the best evidence-based decision in their dementia care settings. Method: The system was developed based on system development life cycle and software prototyping using the following 5 processes: Analysis, Planning, Developing, Program Operation, and Final Evaluation. Result: The system consisted of modules for evidence-based nursing and protocol, guide for developing protocol, tool for saving, revising, and deleting the protocol, interface tool among users, and tool for evaluating users' satisfaction of the system. On the main page, there were 7 menu bars that consisted of Introduction of site, EBN info, Dementia info, Evidence Based Practice Protocol, Protocol Bank, Community, and Site Link. In the operation of the system, HTML, JavaScript, and Flash were utilized and the content consisted of text content, interactive content, animation, and quiz. Conclusion: This system can support nurses' best and cost-effective clinical decision using sharable standardized protocols consisting of the best evidence in dementia care. In addition, it can be utilized as an e-learning program for nurses and nursing students to learn use of evidence based information.

• Journal of Animal Science and Technology
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• v.56 no.4
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• pp.15.1-15.10
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• 2014

Background: Morphologically classifying embryos is important for numerous laboratory techniques, which range from basic methods to methods for assisted reproduction. However, the standard method currently used for classification is subjective and depends on an embryologist's prior training. Thus, our work was aimed at developing software to classify morphological quality for blastocysts based on digital images. Methods: The developed methodology is suitable for the assistance of the embryologist on the task of analyzing blastocysts. The software uses artificial neural network techniques as a machine learning technique. These networks analyze both visual variables extracted from an image and biological features for an embryo. Results: After the training process the final accuracy of the system using this method was 95%. To aid the end-users in operating this system, we developed a graphical user interface that can be used to produce a quality assessment based on a previously trained artificial neural network. Conclusions: This process has a high potential for applicability because it can be adapted to additional species with greater economic appeal (human beings and cattle). Based on an objective assessment (without personal bias from the embryologist) and with high reproducibility between samples or different clinics and laboratories, this method will facilitate such classification in the future as an alternative practice for assessing embryo morphologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.906-909
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• 2015

The smart educational environment using the IWB(Interactive White Board) system has been built and developed since e-learning industry was developed significantly in the early 2000's. Basically the IWB system includes the board writing software, and instructors can further increase the training effect by handwriting on the IWB. In this paper we propose new menu layout mechanism of board writing software that only a few menu buttons are displayed based on the frequency of menu usage and the position of menu layout is dynamically moved according to user's writing position. The implementation of our proposed mechanism shows that it is simple and easy to use without user's unnecessary movement. Therefore it is expected to contribute greatly to the development of a future smart education.

• Journal of Agricultural Extension & Community Development
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• v.21 no.1
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• pp.35-82
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• 2014

It was main objectives to find the learners characteristics and educational effects of cyber agricultural technology courses in RDA. For the research, it was followed by literature reviews and internet based survey methods. In internet based survey, two staged stratified sampling method was adopted from cyber training members database in RDA along with some key word as open course or certificate course, and enrollment years. Instrument was composed through literature reviews about cyber education effects and educational effect factors. And learner characteristics items were added in survey documents. It was sent to sampled persons by e-mail and 316 data was returned via google survey systems. Through the data cleaning, 303 data were analysed by chi-square, t-test and F-test. It's significance level was .05. The results of the research were as followed; First, the respondent was composed of mainly man(77.9%), and monthly income group was mainly 2,000,000 or 3,000,000 won(24%), bachelor degree(48%), fifty or forty age group was shared to 75%, and their job was changed after learning(12.2%). So major respondents' job was not changed. Their major was not mainly agriculture. Learners' learning style were composed of two or more types as concrete-sequential, mixing, abstract-random, so e-learning course should be developed for the students' type. Second, it was attended at 3.2 days a week, 53.53 minutes a class, totally 172.63 minutes a week. They were very eager or generally eager to study, and attended two or more subjects. The cyber education motives was for farming knowledge, personal competency development, job performance enlarging. They selected subjects along with their interest. A subject person couldn't choose more subjects for little time, others, non interesting subject, but more subject persons were for job performance benefits and previous subjects effectiveness. Most learner was finished their subject, but a fourth was not finished for busy (26.7%). And their entrying behavior was not enough to learn e-course and computer or internet using ability was middle level as software using. And they thought RDA cyber course was comfort in non time or space limit, knowledge acquisition, and personal competency development. Cyber learning group was composed of open course only (12.5%), certificate only(25.7%), both(36.3%). Third, satisfaction and academic achievement of e-learning learners were good, and educational service offering for doing job in learning application category was good, but effect of cyber education was not good, especially, agricultural income increasing was not good because major learner group was not farmer, so they couldn't apply their knowledge to farming. And content structure and design, content comprehension, content amount were good. The more learning subject group responded to good in effects, and both open course and certificate course group satisfied more than open course only group. Based on the results, recommendation was offered as cyber course specialization before main course in RDA training system, support staff and faculty enlargement, building blended learning system with local RDA office, introducing cyber tutor system.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.100-107
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• 2013

As the eBook market grows fast recently, various eBook viewer solutions such as hardware viewers and software readers came out to the market. We can, however, hardly find mobile eBook interfaces for the reading disabled people who have difficulties in reading for their visual impairment or learning disabilities, or dyslexia. An eBook viewer interfaces for the reading disabled people should be carefully and distinctively designed because the reading disabled people cannot use normal versions of eBook viewer. In this paper, we suggest a eBook viewer interface model to make the reading disabled people read eBooks easily. Depending on the type of the reading disabled people: the full blind, the almost blind, the just learning disabled, our model provides an adaptive interface to make them read eBooks effectively. In addition, unlike the existing simple audio books, we also support annotation systems to make the reading disabled people interact with eBook viewer. To show the effectiveness of our model, we implemented an eBook viewer prototype on an android-based mobile device. We are sure that our model and implementation can make the reading disabled people, who is 10% of all the domestic people, read eBooks effectively.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.139-150
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• 2021

Object orientation has become the predominant paradigm for conceptual modeling (e.g., UML), where the notions of class and object form the primitive building blocks of thought. Classes act as templates for objects that have attributes and methods (actions). The modeled systems are not even necessarily software systems: They can be human and artificial systems of many different kinds (e.g., teaching and learning systems). The UML class diagram is described as a central component of model-driven software development. It is the most common diagram in object-oriented models and used to model the static design view of a system. Objects both carry data and execute actions. According to some authorities in modeling, a certain degree of difficulty exists in understanding the semantics of these notions in UML class diagrams. Some researchers claim class diagrams have limited use for conceptual analysis and that they are best used for logical design. Performing conceptual analysis should not concern the ways facts are grouped into structures. Whether a fact will end up in the design as an attribute is not a conceptual issue. UML leads to drilling down into physical design details (e.g., private/public attributes, encapsulated operations, and navigating direction of an association). This paper is a venture to further the understanding of object-orientated concepts as exemplified in UML with the aim of developing a broad comprehension of conceptual modeling fundamentals. Thinging machine (TM) modeling is a new modeling language employed in such an undertaking. TM modeling interlaces structure (components) and actionality where actions infiltrate the attributes as much as the classes. Although space limitations affect some aspects of the class diagram, the concluding assessment of this study reveals the class description is a kind of shorthand for a richer sematic TM construct.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.173-178
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• 2023

As Korean literature spreads around the world, its position in the overseas publishing market has become important. As demand in the overseas publishing market continues to grow, it is essential to predict future book sales and analyze the characteristics of books that have been highly favored by overseas readers in the past. In this study, we proposed ensemble learning based prediction model and analyzed characteristics of the cumulative sales of more than 5,000 copies classified as good sellers published overseas over the past 5 years. We applied the five ensemble learning models, i.e., XGBoost, Gradient Boosting, Adaboost, LightGBM, and Random Forest, and compared them with other machine learning algorithms, i.e., Support Vector Machine, Logistic Regression, and Deep Learning. Our experimental results showed that the ensemble algorithm outperforms other approaches in troubleshooting imbalanced data. In particular, the LightGBM model obtained an AUC value of 99.86% which is the best prediction performance. Among the features used for prediction, the most important feature is the author's number of overseas publications, and the second important feature is publication in countries with the largest publication market size. The number of evaluation participants is also an important feature. In addition, text mining was performed on the four book reviews that sold the most among good-selling books. Many reviews were interested in stories, characters, and writers and it seems that support for translation is needed as many of the keywords of "translation" appear in low-rated reviews.

• The Journal of Korean Association of Computer Education
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• v.20 no.4
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• pp.47-57
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• 2017

The purpose of this study is to verify the effectiveness of a CT-CPS(Computational Thinking-based Creative Problem Solving) instructional model on the cognitive and the affective area of middle school students' software class. To achieve our goal, we explored theoretical background and designed a lesson plan based on CT-CPS instructional model. Then we analyzed our experimental results after applying the lesson plan to middle school students. We performed our experiment to an experimental group by using our CT-CPS instructional model-based lesson plans, and we carried out three pre and post tests about cognitive and affective area, i.e. creative problem solving ability, meta cognition and motivation of learning. As a result, most of the test factors were statistically improved, so the effectiveness of the CT-CPS instructional model on the cognitive and the affective area of middle school students' software class was verified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3820-3841
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• 2018

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver's head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver's distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver's distraction, i.e., driver's head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver's head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.43-65
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• 2021

With the advancement of information and communications technology, a means to recruit IT professional has fundamentally changed. Nowadays recruiters search for candidate information from the Web as well as traditional information sources such as résumés or interviews. Particularly, open-source software development (OSSD) platforms have become an opportunity for developers to demonstrate their IT capabilities, making it a way for recruiters to find the right candidates, whom they need. Therefore, this study aims to investigate the impact developers' profiles in an OSSD platform on their finding a job. This study examined four antecedents of developer information that can accelerate their job search: job-seeking status, personal-information posting, learning activities and knowledge contribution activities. For the empirical analysis, we developed a Web crawler and gathered a dataset on 4,005 developers from GitHub, which is a well-known OSSD platform. Proportional hazards regression was used for data analysis because shorter job-seeking period implies more successful result of job change. Our results indicate that developers, who explicitly posted their job-seeking status, had shorter job-seeking periods than those who did not. The other antecedents (i.e., personal-information posting, learning, and knowledge contribution activities) also contributed in reducing the job-seeking period. These findings imply values of OSSD platforms for recruiters to find proper candidates and for developers to successfully find a job.