• Korean Management Science Review
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• v.23 no.2
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Convergence Security Journal
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• v.11 no.6
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• pp.73-80
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The delayed software S-shaped reliability model applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1329-1337
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• 2008

The project of Education information is promoted to maximize the efficiency of Teaching-Learning at schools. So Ministry of Education & Human Resources Development develops and spreads the Computer Assisted Instruction(CAI) and outstanding Educational Software to help learners who can utilize this software and make learning environment to form their own recognition. As the number of this software is increased, the necessity of management of Educational Software is required. This study divides Educational Software into three kinds, teaching-learning software, business management software, and system management software, and suggests how to use these softwares effectively according to this division. After the users log into the system through joining members, they are divided into manager module, teachers module, and students module. The manager manages all software like registration, revision, reference of date and so on. The teacher accesses properly. The student accesses teaching-learning software and prepares and reviews his lessons at any time.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.245-254
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• 2019

In the 2015 revision curriculum, software education must be conducted for 17 hours in elementary school fifth or sixth grade. Pre_service elementary teachers should be able to teach software. In this study, learning factors according to the achievement criteria for software education will be defined for pre-service elementary teachers. Pre-service teachers were taught by learning elements. As a result, the pre_service teachers were able to create teaching and evaluation materials for each learning element. It was also found that the pre-service teachers improved their ability to teach software education in elementary school based on these materials.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.1-10
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• 2022

Since 2019, elementary schools have been teaching software to students, so pre-service teachers should have the ability to teach software. Also, in the COVID-19 situation, pre-service teachers need the ability to teach software online. The purpose of this study is to investigate the effectiveness of online software education for preservice teachers. After providing online software education to preservice teachers, we analyse the results and examines whether online software education is effective. In this study, we define 55 learning elements by analyzing the achievement standards that can evaluate the software education ability of preservice teachers. We figure out whether pre-service teachers have acquired the ability to provide online software education to elementary school students. As a result of the study, we concluded that pre-service teachers who received this online education could conduct software education online in elementary school.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.159-167
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• 2018

In this study, we have developed an online learning community site using Humhub social network software and promote social constructive learning through the questions and answers in subject specific learning groups. By accumulating learning contents which consist of questions and answers about specific topics, learners can acquire knowledge by searching relevant topics and questions and can create and reconstruct knowledge as well as consuming knowledge by participating in self-regulated learning community. We have developed a mathematical editor feature which enables users to enter mathematical expression such as equations and greek characters. Online learning community sites can be used for inquiry based information education.

• Journal of Software Assessment and Valuation
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• v.14 no.2
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• pp.1-9
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• 2018

The proportion of users and companies using open source continues to grow. The size of open source software market is growing rapidly not only in foreign countries but also in Korea. However, compared to the continuous development of open source software, there is little research on open source software subject classification, and the classification system of software is not specified either. At present, the user uses a method of directly inputting or tagging the subject, and there is a misclassification and hassle as a result. Research on open source software classification can also be used as a basis for open source software evaluation, recommendation, and filtering. Therefore, in this study, we propose a method to classify open source software by using machine learning model and propose performance comparison by machine learning model.

• Journal of The Korean Association of Information Education
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• v.8 no.4
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• pp.501-510
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• 2004

The activation of the latest ICT(Information and Communication Technology)education has been putting more importance on the education of the application SW(software). By the way, the geometric progression of knowledge and the fast development of computer technology have continuously created new SW. Accordingly, the previous traditional SW learning paradigm runs into various problems. This study starts from the recognition of such problems. In this study, the SW adaptability is defined as the ability that learners can efficiently find and apply the suitable functions of SW to those problems in the problematic circumstances as well as promote retention and metastasis. With these premises, this paper makes an inquiry into the teaching-learning method. Besides, This paper explores the SW usability and the principles of UI(User Interface) design and deduces the SW learning strategy. Furthermore, it probes problems of the SW teaching-learning of the demonstration practice method and proposes the inquiring master for SW adaptability teaching-learning model.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.729-736
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. Until recent days, the model using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software cost using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying genetic algorithm. The proposed GA-SVR model outperform some recent results reported in the literature.