• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.473-480
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• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.922-934
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• 2020

The talent trading platform is a platform that brokers transactions such as program coding, media content production (video, music, presentation materials, etc.), design, learning, and repair. Existing talent trading platforms provide a server-client model-based service, which incurs server operating costs and arbitration labor costs for transactions, which has a disadvantage that users bear high service fees. This paper proposes a method to reduce server and database operation costs by uploading transaction information to blocks through the system as a distributed app (dApp) based on the Ethereum platform. In addition, it proposes a method to lower transaction fees by reducing the labor cost of transaction arbitrators through smart contracts. Compare and analyze the cost processing procedure and transaction fee size of the blockchain-based talent trading platform and the existing talent trading platform.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.281-286
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• 2014

Humanities knowledge makes the learners overcome the boundaries of study and can be applied variously by means of contents for study. This paper suggests application contents plans designed as the learning tools for blended learning, which can be sure of the possibility to the extension of other fields. Literary education with application contents has effects followings: First, smart device based on the web under the ubiquitous circumstances has the information system like the neuron's. So the application selects the necessary information and makes the contents for infusion into the education. Also it provides with more abundant and extended information system. With this approach, learners are able to get further literary knowledge and promote the ability for tapping them for new knowledge as well. Lastly, literature applied to the class with web contents is based on the foundation that creates new knowledge necessary for culture, arts, and so on. As a result, the education using web contents achieves the boundless of study, which is the final goal of the blended learning.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.511-516
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• 2024

The recently enacted detailed guidelines on the performance evaluation of track facilities presented the necessary requirements regarding the evaluation procedures and implementation methods of track performance evaluation. However, the grade of rail surface damage is determined by external inspection (visual inspection), and there is no choice but to rely only on qualitative evaluation based on the subjective judgment of the inspector. Therefore, in this study, we attempted to develop a diagnostic application that can diagnose rail internal defects using rail surface damage. In the field investigation, rail surface damage was investigated and patterns were analyzed. Additionally, in the indoor test, SEM testing was used to construct image data of rail internal damage, and crack length, depth, and angle were quantified. In this study, a deep learning model (Fast R-CNN) using image data constructed from field surveys and indoor tests was applied to the application. A rail surface damage diagnosis application (App) using a deep learning model that can be used on smart devices was developed. We developed a smart diagnosis system for rail surface damage that can be used in future track diagnosis and performance evaluation work.

• The Journal of Korean Association of Computer Education
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• v.14 no.5
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• pp.71-79
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• 2011

We designed and implemented a cooperative learning system using social network service which can be utilized on a smart phone for users to read each other's posting once they upload posting and to give feedback concerning the posting in real time without the need for accessing a relevant website, through the installation of a necessary application which makes it possible for learners to interact at any time in any place on a smart phone. The developed program is used as an intermediate tool for real-time communications so as to aid in solving the task of learners, and it was made to boost academic achievement as well as interest in learning through real-time interactions and feedback. Furthermore, the program was designed in such a way that an instructor actually helps learners by closely identifying their levels based on accumulated data.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.124-131
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• 2020

As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.11-18
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• 2015

A person with defects and the lack of hearing, has very difficult problems to listen to the sound of conversation or environment, and these problems cause wrong directions in the linguistic sense and character. We designed and implemented an application to practice and correct pronunciation of a hearing-impaired person specially. This is made as a mobile app without the limitation of time and space, and this provides practices with the level of difficulty in learning of pronunciation, taking into consideration of remedial status in pronunciation. The hearing-impaired person can train the basic pronunciation and the word pronunciation. He or she can practice basic skills in pronunciation and check the record on the practice rate and the success rate. Also, the person can improve pronunciation by self-correction function using the front camera of a smart phone.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.65-71
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• 2017

With advances in technology, many researchers have made an effort to find out educational methods with customized instruction. The purpose of the research is to investigate i) if flipped learning is beneficial for the students taking intermediate-level English grammar and writing class compared with the traditional class, ii) if the flipped learning class is advantageous for all the score level students in terms of student achievement and iii) if the students feel motivated with the flipped learning class. T-test was utilized to determine any differences between pretest and posttest in student achievement. The result in terms of the academic achievement revealed that the flipped classroom approach for the low score group was found to be the least effective among others. In the case of flipped learning teaching method, the instructor should develop contents according to the level of learners. The development of customized contents tailored to the level of learners will enhance learners' learning achievement.

• Smart Media Journal
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• v.11 no.4
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• pp.9-18
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• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.59-67
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• 2018

There are not that many m-health related services limited to the elderly. Many of the elderly who are at risk of dementia are unfamiliar to smart devices, so it is required to design an user-customized App. Therefore, I design and embody a mobile voice alert integrated app, which enables voice input to increase the accessibility of the elderly, so as to prevent diseases caused by declined cognitive function such as dementia. I conducted interviews and questionnaire after having the students use the app in Lifelong Education Center in H region of Gyeongbuk, and the analysis result has showed the high satisfaction. It is expected that it will be able to play a key role for M-Health service for the elderly since it is possible to prevent dementia through the voice health care alert app. I would like to learn deep learning in the future to predict the life patterns and the possibility of dementia of the elderly.