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Case study of AI art generator using artificial intelligence (인공지능을 활용한 AI 예술 창작도구 사례 연구)

  • Chung, Jiyun
    • Trans-
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    • v.13
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    • pp.117-140
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    • 2022
  • Recently, artificial intelligence technology is being used throughout the industry. Currently, Currently, AI art generators are used in the NFT industry, and works using them have been exhibited and sold. AI art generators in the art field include Gated Photos, Google Deep Dream, Sketch-RNN, and Auto Draw. AI art generators in the music field are Beat Blender, Google Doodle Bach, AIVA, Duet, and Neural Synth. The characteristics of AI art generators are as follows. First, AI art generator in the art field are being used to create new works based on existing work data. Second, it is possible to quickly and quickly derive creative results to provide ideas to creators, or to implement various creative materials. In the future, AI art generators are expected to have a great influence on content planning and production such as visual art, music composition, literature, and movie.

Development of cloud-based multiplication table practice application using data visualization (데이터 시각화를 적용한 클라우드 기반 곱셈구구 연습 애플리케이션 개발)

  • Kang, Seol-Joo;Park, Phanwoo;Bae, Youngkwon
    • Journal of The Korean Association of Information Education
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    • v.26 no.4
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    • pp.285-293
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    • 2022
  • The COVID-19 outbreak, which took longer than expected, caused considerable damage to students' basic academic ability in mathematics. In this paper, a multiplication table practice application that can help students improve their basic multiplication arithmetic skills has been developed based on a cloud-service. The performance of the application was improved by integrating the Flutter framework, Google Cloud, and Google Sheets. As a result of applying this application to 72 6th graders in elementary schools located in K Metropolitan City, for one week. students' spending time required for solving multiplication table problems was reduced by more than 28% compared to the initial period, while students' learning data was able to be accurately collected without errors. It is hoped that the development case conducted through the Flutter framework in this study can lead to the development of other educational learning applications.

Weblog Analysis of University Admissions Website using Google Analytics (구글 애널리틱스를 활용한 대학 입시 홈페이지 웹로그 분석)

  • Su-Hyun Ahn;Sang-Jun Lee
    • Journal of Practical Engineering Education
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    • v.16 no.1_spc
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    • pp.95-103
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    • 2024
  • With the rapid decline of the school-age population, the competition for admissions has increased and marketing through digital channels has become more important, so universities are investing more resources in online promotion and communication to recruit new students. This study uses Google Analytics, a web log analysis tool, to track the visitor behavior of a university admissions website and establish a digital marketing strategy based on it. The analysis period was set from July 1, 2023, when Google Analytics 4(GA4) was integrated, to January 10, 2024, when the college admissions process was completed. The analysis revealed interesting patterns such as geographical information based on visitors' access location, devices(operating systems) and browsers used by visitors, acquisition channels through visitors traffic, conversions on pages and screens that visitors engaged with and visitor flow. Based on this study, we expect universities to find ways to strengthen their admission promotion through digital marketing and effectively communicate with applicants to gain a competitive edge.

The Effects of Restrictions in Economic Activity on the Spread of COVID-19 in the Philippines: Insights from Apple and Google Mobility Indicators

  • CAMBA, Abraham C. Jr.;CAMBA, Aileen L.
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.115-121
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    • 2020
  • This study aims to investigate the effects of restrictions in economic activity on the spread of COVID-19 in the Philippines. This research employs daily time-series data of confirmed new COVID-19 cases, Apple mobility trends (i.e., use of public transport to destinations, volume of people driving, and amount of walking to destinations) and Google community mobility (i.e., visits to transit stations, visits to workplaces, and staying-at-home) indicators covering the period February 17 to September 11, 2020. The analysis starts by establishing the correlation pattern of new confirmed COVID-19 daily infections to each independent variable. The results show negative linear correlation of the number of new COVID-19 daily infections with less visit to transit station, increase stay-at-home, less use of public transport, and less amount of walking to destinations. Interestingly, the number of new COVID-19 daily infections indicates some form of positive linear correlation with visits to workplaces and volume of people driving. Moreover, employing robust least square regression via the method of MM-estimation, major findings reveal that across mobility measures, staying-at-home has the highest impact on reducing the spread of COVID-19, followed by visiting transit stations less, less use of public transport, less amount of walking, and less workplace visits.

Androfilter: Android Malware Filter using Valid Market Data (Androfilter: 유효마켓데이터를 이용한 안드로이드 악성코드 필터)

  • Yang, Wonwoo;Kim, Jihye
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.6
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    • pp.1341-1351
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    • 2015
  • As the popularization of smartphone increases the number of various applications, the number of malicious applications also grows rapidly through the third party App Market or black market. This paper suggests an investigation filter, Androfilter, that detects the fabrication of APK file effectively. Whereas the most of antivirus software uses a separate server to collect, analyze, and update malicious applications, Androfilter assumes Google Play as the trusted party and verifies integrity of an application through a simple query to Google Play. Experiment results show that Androfilter blocks brand new malicious applications that have not been reported yet as well as known malicious applications.

Evaluation of Mobile Unified Search Contents of Naver and Google Korea (네이버와 구글의 모바일 통합 검색 컨텐츠 평가)

  • Park, So-Yeon
    • Journal of Korean Library and Information Science Society
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    • v.42 no.4
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    • pp.263-280
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    • 2011
  • This study aims to investigate current status of mobile search services of Korean search portals, and analyze mobile unified search contents of Naver and Google Korea. In particular, this study analyzed characteristics of mobile unified search such as number of retrieved documents, collection distribution, and yearly distribution. Also, documents were evaluated in terms of relevance, credibility, and currency. This study compared quality of Naver's unified Web best and unified Web, and Google's best Web documents and Web documents. The correlation between document's ranking and document's relevance was analyzed. The results of this study can be implemented to the portal's effective development of mobile search service.

Analyzing Learners' Activities in the Collaborative Learning Based Group Project Using the Wiki Environment: a Case of the Google Sites Use (위키 환경을 활용한 학습자의 협력학습 기반 그룹 프로젝트 활동 분석: 구글 사이트 활용 사례를 중심으로)

  • Jung, Young-Sook;Park, Ok-Nam
    • Journal of the Korean Society for information Management
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    • v.26 no.3
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    • pp.239-259
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    • 2009
  • The study aims at investigating students' behaviors and perceptions regarding the collaborative learning based group project using the wiki environment. The study utilized Google Sites as a case, and analyzed file unloads, the use of web pages, navigation bars, and comments as well as surveys. The study discusses main characteristics of students' activities in the collaborative learning group project, which are drawn from the analysis of students' behaviors and perceptions. The study also provides implications for improvement of wiki environment to support collaborative learning in education.

The Development of information sharing Application of Android based on the Google Map (구글맵 기반 안드로이드 정보 공유 애플리케이션 개발)

  • Kim, Byeong-Su;Kim, Jong-Hoon
    • 한국정보교육학회:학술대회논문집
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    • 2011.01a
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    • pp.153-158
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    • 2011
  • The idea that the mobile phone could be used in the education field recently comes from it's strengths. They have mobility, on-the-spot-study, portablity, immediacy and they are easy to connect to educational information. The application which I developed in this study is using Google-Map API and is based on GPS. It can share the information about the area where user is located like text data and pictures of geography, culture, and historical remains. This application makes the best use of the mobile phone's strengths. It's more effective and we can expect that users could manage resources of learning and do self-directed study in spite of being outside of the classroom or after regular classtime.

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A Verification about the Formation Process of Filter Bubble with Personalization Algorithm (개인화 알고리즘으로 필터 버블이 형성되는 과정에 대한 검증)

  • Jun, Junyong;Hwang, Soyoun;Yoon, Youngmi
    • Journal of Korea Multimedia Society
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    • v.21 no.3
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    • pp.369-381
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    • 2018
  • Nowadays a personalization algorithm is gaining huge attention. It gives users selective information which is helpful and interesting in a deluge of information based on their past behavior on the internet. However there is also a fatal side effect that the user can only get restricted information on restricted topics selected by the algorithm. Basically, the personalization algorithm makes users have a narrower perspective and even stronger bias because users have less chances to get views of opponent. Eli Pariser called this problem the 'filter bubble' in his book. It is important to understand exactly what a filter bubble is to solve the problem. Therefore, this paper shows how much Google's personalized search algorithm influences search result through an experiment with deep neural networks acting like users. At the beginning of the experiment, two Google accounts are newly created, not to be influenced by the Google's personalized search algorithm. Then the two pure accounts get politically biased by two methods. We periodically calculate the numerical score depending on the character of links and it shows how biased the account is. In conclusion, this paper shows the formation process of filter bubble by a personalization algorithm through the experiment.

The Study on the Ranking Algorithm of Web-based Sear ching Using Hyperlink Structure (하이퍼링크 구조를 이용한 웹 검색의 순위 알고리즘에 관한 연구)

  • Kim, Sung-Hee;O, Gun-Teak
    • Journal of Information Management
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    • v.37 no.2
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    • pp.33-50
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    • 2006
  • In this paper, after reviewing hyperlink based ranking methods, we saw various other parameters that effect ranking. Then, We analyzed the PageRank and HITS(Hypertext Induced Topic Search) algorithm, which are two popular methods that use eigenvector computations to rank results in terms of their characteristics. Finally, google and Ask.com search engines were examined as examples for applying those methods. The results showed that use of Hyperlink structure can be useful for efficiency of web site search.