• Proceedings of the Korean Society of Computer Information Conference
• /
• 한국컴퓨터정보학회 2015년도 제51차 동계학술대회논문집 23권1호
• /
• pp.135-136
• /
• 2015

본 논문에서는 무선 랜(Wi-Fi)을 통하여 학습 환경 구축을 위해 LED 조명 색 온도를 제어하는 방법을 설명 하고, LED 조명을 위한 Android App 개발 과정을 설명한다. 스마트폰과 LED 조명은 Wi-Fi를 통해 통신하며, JAVA언어로 개발한 Android App을 이용하여 학습 주제에 따른 색온도(Color Tempeaure)로 제어하게 되면 LED 조명 색온도가 변경되어 학습 환경 구축이 완료되어, 집중력 향상으로 인한 학습 능률이 증가된다.

• Korean Journal of Artificial Intelligence
• /
• 제2권1호
• /
• pp.1-3
• /
• 2014

These days, interest and demand on smart learning has rapidly increased. Video English and mobile system based English speaking service have become popular. This study gave prototype of application to give and take voice message with world people and to give new concept of voice pen-pal beyond exchange of text messages. In modern society having rapidly increasing demand on smart learning, you can study foreign language by smart phone and communicate with foreigners by voice anytime and anywhere. The app allows global exchange to learn conversation. Recruitment of initial users and profit model have problems. We shall develop to improve problems and to solve difficulty.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 한국컴퓨터정보학회 2012년도 제46차 하계학술발표논문집 20권2호
• /
• pp.355-357
• /
• 2012

본 논문에서는 안드로이드 기반 스마트폰을 이용하여 모바일 게임개발을 위한 기초 학습용 앱의 구현 내용을 소개하였다. 이미 상용화 되어 있는 학습용 앱의 용도 외에 게임적 요소를 접목하여 학습의 효과와 흥미를 높일 수 있도록 하였다. 누구나 배우고 즐길 수 있는 학습용 앱으로 평가할 수 있다. 디자인적 요소와 게임 기능의 확대 후 안드로이드 마켓에 배포하여 서비스를 할 수 있으며 본 연구의 과정은 게임 앱 설계 관련 프로젝트의 수행이나 학습용 게임 앱 개발의 학습 모형을 제시한 사례로 활용할 수 있다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 한국컴퓨터정보학회 2011년도 제44차 하계학술발표논문집 19권2호
• /
• pp.419-420
• /
• 2011

스마트폰을 이용한 학습용 앱을 개발하기 위해 본 연구는 기초학습인 덧셈의 기능을 완료하였다. 덧셈문제를 계속해서 풀 수 있는 구조로 설계하였고, 정답과 오답에 대한 설명 이벤트를 배치하여 학습효과를 높였다. 본 과정은 수학공식 및 다양한 학습으로 확장 가능하며, 사용자별, 날짜별 점수 DB를 저장한다면 본인의 실력 향상을 체크해 볼 수 도 있을 것이다. 본 학습앱을 안드로이드기반 스마트폰에 배포한 결과 정상적으로 풀이 됨을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권6호
• /
• pp.1620-1634
• /
• 2023

This paper studies the task of embedding nodes with multiple graphs representing multiple information channels, which is useful in a large volume of network clustering tasks. By learning a node using multiple graphs, various characteristics of the node can be represented and embedded stably. Existing studies using multi-channel networks have been conducted by integrating heterogeneous graphs or limiting common nodes appearing in multiple graphs to have similar embeddings. Although these methods effectively represent nodes, it also has limitations by assuming that all networks provide the same amount of information. This paper proposes a method to overcome these limitations; The proposed method gives different weights according to the source graph when embedding nodes; the characteristics of the graph with more important information can be reflected more in the node. To this end, a novel method incorporating a multi-channel gate layer is proposed to weigh more important channels and ignore unnecessary data to embed a node with multiple graphs. Empirical experiments demonstrate the effectiveness of the proposed multi-channel-based embedding methods.

• Journal of Korean Elementary Science Education
• /
• 제40권3호
• /
• pp.390-406
• /
• 2021

This study investigated how elementary students with different spatial ability constructed spatial thinking process about on volcanoes and earthquakes with GeoMapApp-based materials. Students' spatial thinking process was analyzed in terms of spatial concept recognized, tools of spatial representation, and their spatial reasoning to construct topographic structure. The student group with high-scored spatial ability showed the spatial reasoning based on internal representation of building mental images through sectional division of horizontal distance, directly connected with spatial concept, or distorting spatial concept. The student group with low-scored spatial ability built the spatial reasoning directly connected with spatial concept instead of transforming into internal representation, and partially recognized spatial concept on either distance or depth. Based on the results, we argued identifying spatial concepts such as distance, height, or depth from the GeoMapApp data would be funda- mental for the better spatial thinking.

• Journal of KIISE
• /
• 제42권12호
• /
• pp.1611-1622
• /
• 2015

Although Android systems provide a permission-based access control mechanism and demand a user to decide whether to install an app based on its permission list, many users tend to ignore this phase. Thus, an improved method is necessary for users to intuitively make informed decisions when installing a new app. In this paper, with regard to the permission-based access control system, we present a novel approach based on a machine-learning technique in order to support a user decision-making on the fly. We apply the K-NN (K-Nearest Neighbors) classification algorithm with necessary weighted modifications for malicious app classification, and use 152 Android permissions as features. Our experiment shows a superior classification result (93.5% accuracy) compared to other previous work. We expect that our method can help users make informed decisions at the installation step.

• Journal of the Korea Convergence Society
• /
• 제7권4호
• /
• pp.133-140
• /
• 2016

This paper suggests designing how to acquire English vocabularies on the smart devices based on the research that a ground-breaking English Vocabulary Learning Contents needs developing. The method makes it possible to develop the contents which helps the learners to master English vocabularies effectively on the smart phone. The core idea of this paper is as in the following: 1) English learners learn 30 vocabularies for three minutes 10 times (one is for a new learning and the other nine ones are for reviews about the first learning) a day. 2) Considering Ebbinghaus Forgetting Curve, the reflection study proposes to provide the learners with three times' reviews: one day, 10days, and 30days later from which they learn the first 30 vocabularies. This contents is mainly made up of 5 developing sections (1)to generate App ID, (2)to access App, (3)to set up Alarm, (4)to process Word learning, and (5)to monitor the result of learning. This proposed idea is optimized to enhance the memory by Ebbinghaus Periodic Repetitive Method, which makes the learners satisfied with their English vocabulary learning.

• Journal of Industrial Convergence
• /
• 제19권4호
• /
• pp.1-8
• /
• 2021

This study was conducted with the aim of developing a mobile app so that parents and children can provide questions and conversation-based Home Humanity Education. App development was developed in four stages: analysis, design, development, and evaluation by modifying the ADDIE model. In the analysis stage, education goals were set and seven core competencies were extracted for the app. In the design stage, 15 menus, including character to implement seven core competencies, were selected for learning contents. In the development stage, questions were asked based on 1,000 photos, and parents and children naturally talked to strengthen their core competencies. In the evaluation stage, the user's evaluation interview was followed by a reflux process that produced and reflected improvements. Based on research results, it is going to suggest follow-up research on developing apps for home humanity education. First, it is necessary to verify the learning experiences and changes that occur when parents and children use apps for a long time through longitudinal research. Second, a follow-up study is needed on how to use the home humanity education app by age and how to improve it accordingly. Third, as the number of cases in which grandparents raise their grandchildren increases, it is necessary to study the process and learning effects of grandparents and grandchildren using the app.

• Journal of Industrial Convergence
• /
• 제20권12호
• /
• pp.195-202
• /
• 2022

Underground Geospatial Information Map Management System(UGIMMS) integrates various underground facilities in the underground space into 3D mesh data, and supports to check the 3D image and location of the underground facilities in the mobile app. However, there is a problem that it takes a long time to run in the app because various underground facilities can exist in some areas executed by the app and can be seen layer by layer. In this paper, we propose a deep learning-based K-means vertex clustering algorithm as a method to reduce the execution time in the app by reducing the size of the data by reducing the number of vertices in the 3D mesh data within the range that does not cause a problem in visibility. First, our proposed method obtains refined vertex feature information through a deep learning encoder-decoder based model. And second, the method was simplified by grouping similar vertices through K-means vertex clustering using feature information. As a result of the experiment, when the vertices of various underground facilities were reduced by 30% with the proposed method, the 3D image model was slightly deformed, but there was no missing part, so there was no problem in checking it in the app.