• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1551-1559
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• 2015

Recently, the performance of smart devices is almost similar to that of the existing PCs, thus the users of smart devices can perform similar works such as messengers, SNSs(Social Network Services), smart banking, etc. originally performed in PC environment using smart devices. Although the development of smart devices has led to positive impacts, it has caused negative changes such as an increase in security threat aimed at mobile environment. Specifically, the threats of mobile devices, such as leaking private information, generating unfair billing and performing DDoS(Distributed Denial of Service) attacks has continuously increased. Over 80% of the mobile devices use android platform, thus, the number of damage caused by mobile malware in android platform is also increasing. In this paper, we propose android based malware detection mechanism using time-series analysis, which is one of statistical-based detection methods.We use auto-regressive moving-average model which is extracting accurate predictive values based on existing data among time-series model. We also use fast and exact malware detection method by extracting possible malware data through Z-Score. We validate the proposed methods through the experiment results.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.65-72
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• 2016

Personal Health Record(PHR) service can be helpful to patients with diseases requiring strict everyday care and medical treatment, such as diabetes or cancer. In this paper, we propose a PHR system specialized in collecting and analyzing health record data of cancer patients, and present the process of how the system can improve the efficiency of cancer treatment process. Through the smart device application, cancer PHR system obtains daily PHR data which is highly related and critical to cancer therapy. The analysis report is provided to the medical staff with an available format suited for Electronic Medical Record used at medical institution. With the final result of PHR analysis which is easily merged with medical chart, most efficient Chemotherapy treatment can be provided for the patients. Also it is possible for the patients to give the information of side-effect and other pain experience during therapy to their doctors without loss of information. The proposed PHR system has the effect of improving the quality of patient care by allowing the medical staff to acquire the main objective data necessary for drug prescription and medical care benefits.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.47-56
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• 2012

Bicycle has a large amount of kinetic energy available for energy harvesting technology in its speedy and balanced riding movement. Systematic and realistic analysis of its dynamic property is essential to improve the efficiency of energy harvester. However, there has not been enough researches about precise measurement or analysis of bicycle dynamics on real roads. This study aims to investigate the characteristics of vibrational movement of bicycle using MEMS-based accelerometer and to develop a prototype of electromagnetic energy harvester with nonlinear behavior which is proper to the random vibrations accompanied in bicycle riding. The vibrational components have average magnitude of 1 g and turn out to be independent of riding speed. The developed prototype of energy harvester was installed on a front port of a bicycle to use this ambient vibration and generated an average electrical power of 1.5 mW which is enough to support power for most of portable sensors and short range radio-frequency communication. Further study about isolation of vibration from a rider and conversion efficiency is ongoing. The developed energy harvester is expected to be a platform technology for sustainable portable power supply for various smart IT devices and applications.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.60-74
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• 2020

Nursing education using virtual reality simulation (VRS) has emerged as a new teaching method for improving nursing student's knowledge as well as of competency for clinical nursing skill. The purpose of this study was to analyze the effects of nursing education using VRS through an integrative analysis on quantitative and qualitative research. Through quality assessment on the total 382 studies, 17studies (12 quantitative and 5 qualitative) were finally selected. Contents of the 17 studies were reviewed and those with respect to four aspects were gathered: the condition, knowledge, and attitude for effective education using VRS, and the effects of nursing education using VRS on the practice. Readiness of the use of virtual reality device, mastsering of the platform, and interesting scenario were required condition for effective education. The effects of nursing education adopting virtual reality convergence simulation oin terms of knowledge, attitude, and practice included enhancement of the knowledge and extension of the knowledge, improvement in memorizing the process and sequence of the practice through repetitive education, and development of empathy ability and formation of rapport. Hence, adopting virtual reality to convergence simulation of nursing education can maximize the effect of the education.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.68-78
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• 2020

Crop models have been used to predict vegetable crop yield, which would have a considerable economic impact on consumers as well as producers. A small number of models have been developed to estimate growth and yield of vegetables due to limited availability of growth observation data in high-quality. In this study, we aimed to analyze the protocols designed for collection of the observation data for major vegetable crops including cabbage, radish, garlic, onion and pepper. We also designed the protocols suitable for development and verification of a vegetable crop growth model. In particular, different measures were proposed to improve the existing protocol used by Statistics Korea (KOSTAT) and Rural Development Administration (RDA), which would enhance reliability of parameter estimation for the crop model. It would be advantageous to select sampling sites in areas where reliable weather observation data can be obtained because crop models quantify the response of crop growth to given weather conditions. It is recommended to choose multiple sampling sites where climate conditions would differ. It is crucial to collect time series data for comparison between observed and simulated crop growth and yield. A crop model can be developed to predict actual yield rather than attainable yield using data for crop damage caused by diseases and pests as well as weather anomalies. A bigdata platform where the observation data are to be shared would facilitate the development of crop models for vegetable crops.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.35-51
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• 2019

The two main goals of this study are to derive independent factors affecting the success rate of crowdfunding and to empirically analyze the variation of independent factors' effects on the success of crowdfunding by industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). To identify the success factors of crowdfunding for invigoration and strategic utilization, first, several variables were refined after interviews with experts and platform operators with investment experiences in numerous crowdfunding projects. Then, independent factors affecting project involvement were categorized as follows: a characteristic of project, participant activity, and enterprise. Also, the results derived from the influence of independent variables on crowdfunding after moderating effects were driven. Selected independent factors in this study are as follows: crowdfunding period, target amount, visual contents, minimum account money, number of comments, number of SNS followers, level of interest, financial Statement disclosure, investment attraction, venture company, intellectual property rights disclosure, and business operation period. Selected moderating factors in this study are as follows: industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). In conclusion, a discussion of the academical and practical implications and a suggestion of directions for further research are explained.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.139-149
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• 2022

The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.717-736
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• 2023

The purpose of this study is to develop a statistical program using data and artificial intelligence prediction models and apply it to one class in the sixth grade of elementary school to see if it is effective in improving students' statistical literacy. Based on the analysis of problems in today's elementary school statistical education, a total of 15 sessions of the program was developed to encourage elementary students to experience the entire process of statistical problem solving and to make correct predictions by incorporating data, the core in the era of the Fourth Industrial Revolution into AI education. The biggest features of this program are the recognition of the importance of data, which are the key elements of artificial intelligence education, and the collection and analysis activities that take into account context using real-life data provided by public data platforms. In addition, since it consists of activities to predict the future based on data by using engineering tools such as entry and easy statistics, and creating an artificial intelligence prediction model, it is composed of a program focused on the ability to develop communication skills, information processing capabilities, and critical thinking skills. As a result of applying this program, not only did the program positively affect the statistical literacy of elementary school students, but we also observed students' interest, critical inquiry, and mathematical communication in the entire process of statistical problem solving.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.