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An Investigation on the Network Analysis Papers by Content Analysis and Bibliometric Analysis (네트워크 분석 논문의 고찰: 계량서지적 분석과 내용분석을 중심으로)

  • Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.38 no.1
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    • pp.169-190
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    • 2021
  • Research in various academic fields using network analysis techniques has been conducted and grown. This study performed bibliographical analysis and content analysis on a total of 2,187 network analysis papers published in journals from 2003 to 2021. The results showed that the fields of Pedagogy, Interdisciplinary Research, Computer Science, Library and Information Science, Public Administration, and Business Administration were higher in terms of the number of research papers. From the perspective of journal, mega-journals were indicated as the most productive journals. However, when looking at the impact based on the number of citations, the strength of Public Administration, Library and Information Science, and Pedagogy is clearly revealed. The results of the analysis by authors can also confirm the higher impact of Journalism, Public Administration Science, and Library and Information Science. Of the 1,537 authors identified, very few authors are active in research, confirming the need to expand the researcher base. The results of content analysis showed that the weighted and non-directional network was the most common network type with using the research papers as a data set. Generally nodes are expressed as words and links are expressed as relationship. For network analysis, the use of KrKwic, UCINET, NetMiner, and NetDraw is the most prominent.

The Perspective of Elementary School Teachers on Implementation of AI Education in relation to Software Training Experience (소프트웨어 학습경험에 따른 초등교사의 인공지능교육 도입에 대한 인식)

  • Lee, Yong-Bae
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.449-457
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    • 2021
  • Ministry of education recently announced to implement AI curriculum in elementary, middle school and highschool from 2025 which will include programing, basic AI principal and AI Ethics, and the media is releasing articles that have reservations on it. This study is focused on analyzing the perspective of elementary teachers - who are going to be in charge of AI education - on the implementation of AI education in elementary schools and the teachers are divided into two groups of 'software-experienced' and 'software-inexperienced' in relation to software training background. The results showed that 100% of the 'software-experienced' teachers agreed on implementing AI education and 80% of 'software-inexperienced' teachers also showed positive perspective on it. Among the reasons that 20% of 'software-inexperienced' teachers had negative perspective on AI education, it was highly rated that existing home economics subject covers fulfilling amount of software education. Both 'software-experienced' and 'software-inexperienced' teachers chose grade 5 and 6 as the most appropriate age for software education and considered one class per a week as the most appropriate amount of AI class. In terms of the subject format, 75% of the 'software-experienced' teachers chose the idea that software education has to be an independent school subject which will include AI education. Also, 54% of the 'software-inexperienced' teachers chose the ideas either AI education should be an independent subject or software education should be an independent subject which will include AI education. The preference of the content of AI education appeared in order of basic AI programing, principles of AI and AI Ethics.

A Deep Learning Method for Cost-Effective Feed Weight Prediction of Automatic Feeder for Companion Animals (반려동물용 자동 사료급식기의 비용효율적 사료 중량 예측을 위한 딥러닝 방법)

  • Kim, Hoejung;Jeon, Yejin;Yi, Seunghyun;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.263-278
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    • 2022
  • With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

Study on the Textile Design using Buttons on Western clothing in the 18th·19th Centuries (18·19세기 서양 복식의 단추를 활용한 텍스타일 디자인 연구)

  • Lee, Eui-Jung;Kang, Kyung-Ae
    • Journal of the Korea Fashion and Costume Design Association
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    • v.24 no.2
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    • pp.97-115
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    • 2022
  • The study aims to explore a new direction for research on buttons by understanding the functions and artistic features of buttons on Western clothing in the 18th and 19th centuries, and to use the findings to develop a textile design. In terms of the research method, the period was set in the 18th and 19th centuries, when decorative features and artistic values of buttons on Western clothing reached theirpeak, while theoretical analysis was made based on literature and previous research papers on Western clothing, websites of the Metropolitan Museum and French Museum of Decorative Arts and other website materials, as well as special exhibition materials of the National Museum of Modern and Contemporary Art. Textile designs were developed using computer programs, including Clip Studio Paint and Adobe Photoshop, by integrating the reinterpreted motif of buttons in the 18th and 19th centuries and the styles that prevailed at that time. The results are as follows. First, buttons on Western clothing had the following three functions: a practical function, a symbolic function representing the wearer's status, and a decorative function expressing individuality and beauty. Second, buttons in the 18th century were works of art made with various handicraft techniques and were an important medium that expressed the wearer's fashion sense. In addition, buttons in the 19th century were mass-produced as a result of industrialization and took a major step forward with the development of materials and dyeing. Buttons reflected themes of poetry, drama, biblical stories, music and art, lifestyle,, along with the political and social atmosphere that rapidly changed after the revolution and fashion trends. Third, the artistic features and shapes of buttons were reinterpreted to create a design motif, and the design was developed reflecting the characteristic elements of the rococo style of the 18th century and the art nouveau style of the 19th century that can conform to modern fashion, thereby rediscovering the artistic meaning and value implied in buttons. In the future, the research on creative buttons of 20th century artists is expected to be conducted from various perspectives.

A Study on the System for AI Service Production (인공지능 서비스 운영을 위한 시스템 측면에서의 연구)

  • Hong, Yong-Geun
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.10
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    • pp.323-332
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    • 2022
  • As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

A Case Study on Utilizing Open-Source Software SDL in C Programming Language Learning (C 프로그래밍 언어 학습에 공개 소스 소프트웨어 SDL 활용 사례 연구)

  • Kim, Sung Deuk
    • Journal of Practical Engineering Education
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    • v.14 no.1
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    • pp.1-10
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    • 2022
  • Learning C programming language in electronics education is an important basic education course for understanding computer programming and acquiring the ability to use microprocessors in embedded systems. In order to focus on understanding basic grammar and algorithms, it is a common teaching method to write programs based on C standard library functions in the console window and learn theory and practice in parallel. However, if a student wants to start a project activity or go to a deeper stage after acquiring some basic knowledge of the C language, using only the C standard library function in the console window limits what a student can express or control with the C program. For the purpose of making it easier for a student to use graphics or multimedia resources and increase educational value, this paper studies a case of applying Simple DirectMedia Layer (SDL), an open source software, into the C programming language learning process. The SDL-based programming course applied after completing the basic programming curriculum performed in the console window is introduced, and the educational value is evaluated through a survey. As a result, more than 56% of the respondents expressed positive opinions in terms of improved application ability, stimulating interest, and overall usefulness, and less than 4% of them had negative opinions.

Dynamic Channel Management Scheme for Device-to-device Communication in Next Generation Downlink Cellular Networks (차세대 하향링크 셀룰러 네트워크에서 단말 간 직접 통신을 위한 유동적 채널관리 방법)

  • Se-Jin Kim
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.1-7
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    • 2023
  • Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

A Hybrid Blockchain-Based E-Voting System with BaaS (BaaS를 이용한 하이브리드 블록체인 기반 전자투표 시스템)

  • Kang Myung Joe;Kim Mi Hui
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.8
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    • pp.253-262
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    • 2023
  • E-voting is a concept that includes actions such as kiosk voting at a designated place and internet voting at an unspecified place, and has emerged to alleviate the problem of consuming a lot of resources and costs when conducting offline voting. Using E-voting has many advantages over existing voting systems, such as increased efficiency in voting and ballot counting, reduced costs, increased voting rate, and reduced errors. However, centralized E-voting has not received attention in public elections and voting on corporate agendas because the results of voting cannot be trusted due to concerns about data forgery and modulation and hacking by others. In order to solve this problem, recently, by designing an E-voting system using blockchain, research has been actively conducted to supplement concepts lacking in existing E-voting, such as increasing the reliability of voting information and securing transparency. In this paper, we proposed an electronic voting system that introduced hybrid blockchain that uses public and private blockchains in convergence. A hybrid blockchain can solve the problem of slow transaction processing speed, expensive fee by using a private blockchain, and can supplement for the lack of transparency and data integrity of transactions through a public blockchain. In addition, the proposed system is implemented as BaaS to ensure the ease of type conversion and scalability of blockchain and to provide powerful computing power. BaaS is an abbreviation of Blockchain as a Service, which is one of the cloud computing technologies and means a service that provides a blockchain platform ans software through the internet. In this paper, in order to evaluate the feasibility, the proposed system and domestic and foreign electronic voting-related studies are compared and analyzed in terms of blockchain type, anonymity, verification process, smart contract, performance, and scalability.

A Study on the Improvement of Computing Thinking Education through the Analysis of the Perception of SW Education Learners (SW 교육 학습자의 인식 분석을 통한 컴퓨팅 사고력 교육 개선 방안에 관한 연구)

  • ChwaCheol Shin;YoungTae Kim
    • Journal of Industrial Convergence
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    • v.21 no.3
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    • pp.195-202
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    • 2023
  • This study analyzes the results of a survey based on classes conducted in the field to understand the educational needs of learners, and reflects the elements necessary for SW education. In this study, various experimental elements according to learning motivation and learning achievement were constructed and designed through previous studies. As a survey applied to this study, experimental elements in three categories: Faculty Competences(FC), Learner Competences(LC), and Educational Conditions(EC) were analyzed by primary area and secondary major, respectively. As a result of analyzing CT-based SW education by area, the development of educational materials, understanding of lectures, and teaching methods showed high satisfaction, while communication with students, difficulty of lectures, and the number of students were relatively low. The results of the analysis by major were found to be more difficult and less interesting in the humanities than in the engineering field. In this study, Based on these statistical results proposes the need for non-major SW education to improve into an interesting curriculum for effective liberal arts education in the future in terms of enhancing learners' problem-solving skills.

Log Collection Method for Efficient Management of Systems using Heterogeneous Network Devices (이기종 네트워크 장치를 사용하는 시스템의 효율적인 관리를 위한 로그 수집 방법)

  • Jea-Ho Yang;Younggon Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.119-125
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    • 2023
  • IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.