• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• 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 the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1067-1073
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• 2021

Participants in the virtual environment will have an immersive and memorable perceived experience through interacting with virtual objects. Recently, commercial virtual reality technologies have released simple and cost-effective smartphone-based head-mounted displays (HMD) and high-quality wide field-of-view (FOV) HMDs. However, due to the vergence-accommodation conflict structure of HMD and the learned cognition mechanism in real, side effects such as dizziness and nausea remain challenging to overcome. This study focuses on consistent size perception among various cognitive difference factors, which are essential for interaction with virtual objects. We verified whether the visual angle, which affects the size perception of an object in real, is also the main factor in the virtual environment. Our experiments derived the relation between the visual angle and the environmental components, shadow, and grid, which help perceive a virtual object. As a result of the regression analysis, we presented that in the small FOV HMD environment, the visual angle affects size perception, and the relation between the shadow and the grid is statistically significant.

• The Journal of Bigdata
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• v.5 no.1
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• pp.209-225
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• 2020

This study tried to establish a base level for the form of ginseng in order to prevent fraud in which novice consumers, who have no information on ginseng and mountain ginseng, regard ginseng as mountain ginseng. To that end, researchers designed a service design in which when a consumer takes a picture of ginseng with an APP dedicated to a smartphone, the photo is sent remotely and the determined results are sent to the consumer based on machine learning data. In order to minimize the difference between the data set in the research process and the background color, location, size, illumination, and color temperature of the mountain ginseng when consumers took pictures through their smartphones, the filming box exclusively for consumers was designed. Accordingly, the collection of mountain ginseng samples was made under the same controlled environment and setting as the designed box. This resulted in a 100% predicted probability from the CNN(VGG16) model using a sample that was about one-tenth less than widley required in machine learning.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.175-187
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• 2011

Since insects play important roles in existence of plants and other animals in the natural environment, they are considered as necessary biological resources from the perspectives of those biodiversity conservation and national utilization strategy. For the conservation and utilization of insect species, an observational learning environment is needed for non-experts such as citizens and students to take interest in insects in the natural ecosystem. The insect identification is a main factor for the observational learning. A current time-consuming search method by insect classification is inefficient because it needs much time for the non-experts who lack insect knowledge to identify insect species. To solve this problem, we proposed an smart phone-based insect identification inference system that helps the non-experts identify insect species from observational characteristics in the natural environment. This system is based on the similarity between the observational information by an observer and the biological insect characteristics. For this system, we classified the observational characteristics of insects into 27 elements according to order, family, and species, and proposed similarity indexes to search similar insects. In addition, we developed an insect identification inference prototype system to show this study's viability and performed comparison experimentation between our system and a general insect classification search method. As the results, we showed that our system is more effective in identifying insect species and it can be more efficient in search time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.619-623
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• 2018

This paper aimed to design a computer course teaching-learning strategy for (m-learning?) to be used in a Problem Based Learning (PBL) environment. The research findings were as follows. Firstly, learning contents were provided as educational tools for mobile device usage. The educational contents provided were designed for effective usage on mobile devices, such as smartphones, thereby making mobile devices suitable for use as learning tools. Secondly, learning contents for PBL were provided. PBL problems (for computer engineering courses) were made with the principles of teaching plans. The learning objectives were achieved through the problem-solving progress of the learners and their self-directed and cooperative learnings. Thirdly, learning resources were provided that were easily accessible through smartphones, laptops and PDAs. This study is about the PBL instructional design of creative engineering design subjects, which aims to foster talent. The PBL model developed in this study consists of Analysis, Design, Development, Implementation, and Evaluation. We made a plan for creative engineering design subjects based on PBL, and focused on the process of PBL. This research was able to establish the basis for PBL usage in Engineering Schools and help achieve its ultimate goal of endowing professional intellectuals with creative problem-solving abilities.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.35-37
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• 2012

원격교육과 e-러닝의 차세대 형태로 모바일 교육에 대한 관심이 급증하고 있다. 이러한 모바일 교육은 스마트폰을 중심으로 전개되고 있으며 사이버 대학교뿐만 아니라 일반 오프라인 대학에서도 적극적인 움직임을 보이고 있다. 본 논문에서는 u-캠퍼스 환경기반에서의 모바일 교육 서비스 시스템을 설계하였다. 모바일 교육 서비스 시스템은 u-캠퍼스 환경기반에서 교육 수요자들인 학생들에게 시공간의 제약 및 디바이스에 제약이 없는 학습 환경 시스템을 제공하고 모바일 캠퍼스 플랫폼 기반의 m-러닝 시스템을 설계한 것이다.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.155-160
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• 2016

The education applications for English learning have been developing consistently by utilizing the smart-phone owing to the development of internet and ICT. Smart technology based study platform, the mobile learning which enables for the students to study beyond the time and space is expected to bring forth new paradigm of education in tune with the environment change and trends. But it is found that the current applications are mostly the contents patterned for English study institution information with single channel or made for thinking study concept with only the simple language learning once they were checked. Therefore, the understanding on the English study process shall be changed and the study on the platform service is required by accessing in the viewpoint of thinking exercise learning. This study is purposed to explore the scope and strategy of mobile learning UX platform development and suggest the service model via prototype for English study.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.64-69
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• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.45-53
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• 2012

The appearance of Intelligent mobile and home appliance increased the using of not only various multimedia contents but also educational contents. Especially the growth of smart device such as smart phone, smart pad and smart TV, provided the environment which everyone can use educational content anytime, anywhere, any device. However many smart devices are hard to reuse the various educational contents because the devices and mobile os policies are not unify. In this paper, we suggest the design of NeS(N-Screen e-learning system) in order to solve this problem. NeS is consisted of User Management, Educational Content Management, Content Convert System and Interactive Management System. In this system, we use the HTML5 language to assure interoperability in various Smart Device Environment. Through NeS, we can achieve Content OSMU(One Source Multi Use) in various device environment and assure the continuity of the contents for using the educational contents more easily.