• Journal of Distribution Science
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• v.17 no.11
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• pp.93-101
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• 2019

Purpose: Blockchain technology suggests ways to solve the problems in the existing industry. Among them, Cryptocurrency system, which is an element of Blockchain technology, is a very important factor for operating Blockchain. While Blockchain cryptocurrency has attracted attention, studies on cryptocurrency prices have been mainly conducted, however previous studies mainly conducted on Bitcoin prices. On the other hand, in the context of the creation and trading of various cryptocurrencies based on the Blockchain system, little research has been done on cryptocurrencies other than Bitcoin. Hence, this study attempts to find variables related to the prices of Dash, Litecoin, and Monero cryptocurrencies using machine learning techniques. We also attempt to find differences in the variables related to the prices for each cryptocurrencies and to examine machine learning techniques that can provide better performance. Research design, data, and methodology: This study performed Dash, Litecoin, and Monero price prediction analysis of cryptocurrency using Blockchain information and machine learning techniques. We employed number of transactions in Blockchain, amount of generated cryptocurrency, transaction fees, number of activity accounts in Blockchain, Block creation difficulty, block size, umber of created blocks as independent variables. This study tried to ensure the reliability of the analysis results through 10-fold cross validation. Blockchain information was hierarchically added for price prediction, and the analysis result was measured as RMSE and MAPE. Results: The analysis shows that the prices of Dash, Litecoin and Monero cryptocurrency are related to Blockchain information. Also, we found that different Blockchain information improves the analysis results for each cryptocurrency. In addition, this study found that the neural network machine learning technique provides better analysis results than support-vector machine in predicting cryptocurrency prices. Conclusion: This study concludes that the information of Blockchain should be considered for the prediction of the price of Dash, Litecoin, and Monero cryptocurrency. It also suggests that Blockchain information related to the price of cryptocurrency differs depending on the type of cryptocurrency. We suggest that future research on various types of cryptocurrencies is needed. The findings of this study can provide a theoretical basis for future cryptocurrency research in distribution management.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.525-539
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• 2019

Much research has been conducted on user behavior by taking surveys and interviews to plan the green space effectively. However, there is a limitation in understanding detailed user characteristics such as personalities and values. This study applied the Persona-based Scenario Method (PSM) to Hongneung Experimental Forest to understand the detailed needs and behaviors of the users in the forest recreation area. The PSM is a user experience modeling technique, which tries to understand the users by describing the type of users as real people. This study 1) extracts the factors of visitor recreation activities in Hongneung Experimental Forest based on the results of the survey, 2) develops user personas based on the results of survey and comes up with activity factors, and 3) designs user scenarios. As a result of applying the PSM, 64 factors of visitor activities were derived from the observation survey in 14 sites of Hongneung Experimental Forest and 25 key factors of visitor activities were chosen through observer's brainstorming. Second, three types of personas were developed considering the key factors and the results of user characteristics with quantitative and qualitative analysis. Lastly, context scenarios were designed by applying the key factors of visitor recreation activities to the persona model. We identified the design problems of the space and design requirements through the scenarios. This study has significance in that it takes an approach from the user perspective and was applied to the forest recreation area, which was mainly used in product design. The developed personas could be used for deriving design elements and setting the direction for planning considering detailed needs, behaviors and characteristics of users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.801-810
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• 2015

With the international community's efforts to respond to climate changes progressing in the world, Green IT technologies have also developing rapidly. As green IT technologies against climate change has emerged as the agenda of social sciences, the concept of green IT has evolved into two types: greening of IT and greening by IT. In this context, this study reviewed in depth green IT research trends as well as concepts of greening of IT and greening by IT to respond to climate change. Furthermore, it proposed a life cycle assessment (LCA) as an indicator for assessing green IT. The results of this study are expected to contribute to solving political problems with green IT and continuing research in the climate change era. They are also expected to make a contribution to the development of IT industry in Korea by presenting the concepts of greening of IT and greening by IT.

• Journal of Educational Research in Mathematics
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• v.19 no.2
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• pp.321-340
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• 2009

The purpose of this study was to analyze how lower graders in elementary school might respond to 4 different problem types in the context of measuring length: unit-length comparison, units and unit counting, unit-length expectation, and length comparison. A total of 375 students(185 second graders and 190 third graders) were surveyed and analyzed. The results showed that students were good at 'unit-length comparison' and 'units and unit counting', whereas they were not as to 'length comparison', This paper includes detailed analysis of students' responses as to both correct answer and incorrect one in conjunction with their typical answers and reasoning behind the answers. This paper suggests that teachers be sensitive to the certain level of reasoning tied to each type of problems and attend to students' difficulties in comparing length.

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.19-30
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• 2016

This study examined pre-service teachers' pedagogical content knowledge of fraction division in a context where they were asked to write a story problem for a symbolic expression illustrating a whole number divided by a proper fraction. Problem-posing is an important instructional strategy with the potential to create meaningful contexts for learning mathematical concepts, especially when real-world applications are intended. In this study, story problems written by 135 elementary pre-service teachers were analyzed with respect to mathematical correctness. error types, and division models. Patterns and tendencies in elementary pre-service teachers' knowledge of fraction division were identified. Implicaitons for teaching and teacher education are discussed.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.241-246
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• 2001

Area of software measurement in software engineering is active more than thirty years. There is a huge collection of researches but still no a concrete software cost estimation model. If we want to measure the cost-effort of a software project, we need to estimate the size of the software. A number of software metrics are identified in the literature ; the most frequently cited measures are LOC(line of code) and FPA(function point analysis). The FPA approach has features that overcome the major problems with using LOC as a measure of system size. This paper presents an neural networks(NN) models that related software development effort to software size measured in FPs and function element types. The research describes appropriate NN modeling in the context of a case study for 24 software development projects. Also, this paper compared the NN model with a regression analysis model and found the NN model has better estimative accuracy.

• Journal of Science Education
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• v.46 no.1
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• pp.17-29
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• 2022

The purpose of this study is to look qualitatively into how efficiently and reasonably a computer can learn themes related to the Nature of Science (NOS). In this regard, a corpus has been constructed focusing on literature (920 abstracts) related to NOS, and factors of the optimized Word2Vec (CBOW, Skip-gram) were confirmed. According to the four dimensions (Inquiry, Thinking, Knowledge and STS) of NOS, the comparative evaluation on the word-level word embedding was conducted. As a result of the study, according to the previous studies and the pre-evaluation on performance, the CBOW model was determined to be 200 for the dimension, five for the number of threads, ten for the minimum frequency, 100 for the number of repetition and one for the context range. And the Skip-gram model was determined to be 200 for the number of dimension, five for the number of threads, ten for the minimum frequency, 200 for the number of repetition and three for the context range. The Skip-gram had better performance in the dimension of Inquiry in terms of types of words with high similarity by model, which was checked by applying it to the four dimensions of NOS. In the dimensions of Thinking and Knowledge, there was no difference in the embedding performance of both models, but in case of words with high similarity for each model, they are sharing the name of a reciprocal domain so it seems that it is required to apply other models additionally in order to learn properly. It was evaluated that the dimension of STS also had the embedding performance that was not sufficient to look into comprehensive STS elements, while listing words related to solution of problems excessively. It is expected that overall implications on models available for science education and utilization of artificial intelligence could be given by making a computer learn themes related to NOS through this study.

• Journal of the Korean Society for information Management
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• v.31 no.4
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• pp.7-28
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• 2014

This study analyses the questions addressed to the collaborative digital reference service run by the National Library of Korea. The data consist of 661 question entries to the 'Ask a Librarian' service during first 6 months in 2014. Each entry includes average 1.17 questions, and 77.82% of the total questions are real reference in nature. Questions are analyzed by classification division, context of the questioner, desired end product, activities of librarians, and the resources used to respond them. Each category is subdivided and analyzed in detail. Results revealed interesting findings and problems, and suggestions for further endeavor are provided.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.4
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• pp.25-48
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• 2013

The study aims at providing alternative strategies for the National Assembly's archival information services. In this context, it conducts a literature review and discusses current status of the National Assembly's archival information services. Furthermore, this study draws six critical problems of the National Assembly's archival information services, ranging from a lack of comprehensive archival information services to a deficiency of value-added contents. As a case study, it reviews legislative archival institutions in the US and the UK, and classifies their legislative records management services into 3 different types, including retrieval assistant services, contents services, and extensive services. Base on the case study, as a result, it provides 5 strategies for the development of the National Assembly's archival information services.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.223-240
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• 2013

RFID(Radio Frequency Identification) is use of an RFID tag applied to object for the purpose of identification and tracking using radio waves. Recently, it is being actively researched and introduced in logistics and manufacturing. RFID portals in supply chains are meant to identify all the tags within a given interrogation zone. Hence the hardware and software mechanisms for RFID tag identification mostly focus on successful read of multiple tags simultaneously. Such mechanisms, however, are inefficient for determining moving direction of tags, sequence of consecutive tags, and validity of the tag reads from the viewpoint of workflow. These types of problems usually cause many difficulties in RFID portal implementation in manufacturing environment, there by having RFID-system developers waste a considerable amount of time. In this research, we designated an RFID portal system with SDO(Sequence, Direction, and Object-flow)-perception capability by using fundamental data supplied by ordinary RFID readers. Using our work, RFID system developers can save a great amount of time building RFID data-capturing applications in manufacturing environment.