• Title/Summary/Keyword: 언어 분석

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Efficient use of artificial intelligence ChatGPT in educational ministry (인공지능 챗GPT의 교육목회에 효율적인 활용방안)

  • Jang Heum Ok
    • Journal of Christian Education in Korea
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    • v.78
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    • pp.57-85
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    • 2024
  • Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

A Study on the Development Trend of Artificial Intelligence Using Text Mining Technique: Focused on Open Source Software Projects on Github (텍스트 마이닝 기법을 활용한 인공지능 기술개발 동향 분석 연구: 깃허브 상의 오픈 소스 소프트웨어 프로젝트를 대상으로)

  • Chong, JiSeon;Kim, Dongsung;Lee, Hong Joo;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.1-19
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    • 2019
  • Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

An Efficient Array Algorithm for VLSI Implementation of Vector-radix 2-D Fast Discrete Cosine Transform (Vector-radix 2차원 고속 DCT의 VLSI 구현을 위한 효율적인 어레이 알고리듬)

  • 신경욱;전흥우;강용섬
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.12
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    • pp.1970-1982
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    • 1993
  • This paper describes an efficient array algorithm for parallel computation of vector-radix two-dimensional (2-D) fast discrete cosine transform (VR-FCT), and its VLSI implementation. By mapping the 2-D VR-FCT onto a 2-D array of processing elements (PEs), the butterfly structure of the VR-FCT can be efficiently importanted with high concurrency and local communication geometry. The proposed array algorithm features architectural modularity, regularity and locality, so that it is very suitable for VLSI realization. Also, no transposition memory is required, which is invitable in the conventional row-column decomposition approach. It has the time complexity of O(N+Nnzp-log2N) for (N*N) 2-D DCT, where Nnzd is the number of non-zero digits in canonic-signed digit(CSD) code, By adopting the CSD arithmetic in circuit desine, the number of addition is reduced by about 30%, as compared to the 2`s complement arithmetic. The computational accuracy analysis for finite wordlength processing is presented. From simulation result, it is estimated that (8*8) 2-D DCT (with Nnzp=4) can be computed in about 0.88 sec at 50 MHz clock frequency, resulting in the throughput rate of about 72 Mega pixels per second.

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Contents Conversion System for Mobile Devices using Light-Weight Web Document (웹 문서 경량화에 의한 모바일용 콘텐츠 변환 시스템)

  • Kim Jeong-Hee;Kwon Hoon;Kwak Ho-Young
    • Journal of Internet Computing and Services
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    • v.6 no.6
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    • pp.13-22
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    • 2005
  • This paper aims to develop a system for converting web contents to mobile contents that can be used on mobile devices. Since web contents generally consist of pop-up ad windows, a bunch of unnecessary images and useless links, it is difficult to efficiently display them on common mobile devices that have lower bandwidth and memory, as well as much smaller screen, than the online environment. It is also troublesome for mobile device users to directly access contents. Thus, there has been a great demand for a new method for extracting useful and adequate contents from web documents, and optimizing them for use on mobile phones, In the paper, a system based on WAP 2,0 and XHTML Basic, which is a content creation language adopted for WAP 2,0, has been suggested. The system is designed to convert web contents by using the conversion rules of the existing filtering method after making the size of web documents smaller. The adopted conversion rules use the XHTML Basic's module units so that modification and deletion can be carried out with ease. In addition, it has been defined in a XSL document written in XSLT to maintain the extensibility of conversion and the validity of documents, In order to allow it to efficiently work together with WAP l.X's legacy services, the system has been built in a way that can have modules, which analyze information about CC/PP profiles and mobile device headers.

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Reading "Money": Value and Signification of Money (화폐 읽기: 화폐의 의미작용과 가치)

  • Won, Yong-Jin;Hong, Sung-Il
    • Korean journal of communication and information
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    • v.41
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    • pp.75-107
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    • 2008
  • The paper aims to figure out the meaning of money in terms of communication in which we can find the specific communicative and cultural form of money. In the modern capitalist society, we cannot limit money within the economical terms - for example, store of value, medium of exchange, unit of account and means of payment - because money mediates all human activities beyond the economic boundary and conveys specific meaning in the social and the cultural area. Money can be the medium of the cultural and the communicational as well as the medium of the economic. In this respect, we've try to articulate money with linguistic or semiotic insight. Through this theoretical dialogue, we find two significations of money as a medium of communication. The first signification is meta-signification which drives the individual to the unlimited accumulation of the money. Meta-signification displace the second signification of the money that is the singular, over-determined and the mosaic significations. In this process money can be the signifier without signification. And then, money is the Master signifier which all sign should be identified imaginary. Finally, Money is not only the re-presense (Darstellung) of all sings but also the representative (Vertretung) of all signs. But this double position creates some tensions and makes master signifier of money unstable. Man's analysis of Bonapartism, which shares the linguistic or semiotic insight, shows the crack of the re-presence between the representative. Like Marx's analysis, the money has the tension between two signification which makes the room for the struggle to signify.

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Web Accessibility of Healthcare Websites of Korean Government and Public Agencies: Automated and Expert Evaluations (정부 및 공공기관의 보건 관련 웹 사이트의 웹 접근성 - 자동 및 전문가 평가 -)

  • Yi, Yong Jeong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.26 no.4
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    • pp.283-304
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    • 2015
  • The purpose of this study was to identify Web accessibility issues of healthcare websites of the Korean government and public agencies by evaluating these websites' accessibility in accordance with the Korean Web Contents Accessibility Guideline. This study conducted both automated and expert testing to assess the accessibility of a total of 27 health-related websites. The results of the assessment which was conducted in two stages indicated that institutions such as the National Hospital and National Rehabilitation Center demonstrated almost no Web accessibility error. In addition, the Korea Health Insurance Review and Assessment Service, the Ministry of Health and Welfare, the Health Services Agency, the Ministry of Food and Drug Safety, and the Korea Medical Dispute Mediation and Arbitration Agency attained very high web accessibility. However, the results of an expert evaluation highlighted that there were considerable errors in providing appropriate alternative text, which was not found in the automated test, and the color contrast of the text content did not comply with Web accessibility standard. Therefore, these websites did not support web accessibility for the sight-impaired. Furthermore, the present study found that it was difficult to deliver accurate information to users due to errors in the default language display and markup, and also, issues of skipping repeated content, content linearization, and compliance with keyboard use were considered as challenges that might arise for people with sight, cognitive and mobility impairments with respect to Web accessibility. It is the first study that evaluated accessibility of healthcare websites of the Korean government and public agencies based on the Korean Web Contents Accessibility Guideline. The present study made a contribution to research on Web accessibility by conducting expert testing, which provided a more complete assessment that identified the degree and specific issues of accessibility errors when compared to automated testing.

Optimization and Performance Analysis of Distributed Parallel Processing Platform for Terminology Recognition System (전문용어 인식 시스템을 위한 분산 병렬 처리 플랫폼 최적화 및 성능평가)

  • Choi, Yun-Soo;Lee, Won-Goo;Lee, Min-Ho;Choi, Dong-Hoon;Yoon, Hwa-Mook;Song, Sa-kwang;Jung, Han-Min
    • The Journal of the Korea Contents Association
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    • v.12 no.10
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    • pp.1-10
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    • 2012
  • Many statistical methods have been adapted for terminology recognition to improve its accuracy. However, since previous studies have been carried out in a single core or a single machine, they have difficulties in real-time analysing explosively increasing documents. In this study, the task where bottlenecks occur in the process of terminology recognition is classified into linguistic processing in the process of 'candidate terminology extraction' and collection of statistical information in the process of 'terminology weight assignment'. A terminology recognition system is implemented and experimented to address each task by means of the distributed parallel processing-based MapReduce. The experiments were performed in two ways; the first experiment result revealed that distributed parallel processing by means of 12 nodes improves processing speed by 11.27 times as compared to the case of using a single machine and the second experiment was carried out on 1) default environment, 2) multiple reducers, 3) combiner, and 4) the combination of 2)and 3), and the use of 3) showed the best performance. Our terminology recognition system contributes to speed up knowledge extraction of large scale science and technology documents.

Implementation of WLAN Baseband Processor Based on Space-Frequency OFDM Transmit Diversity Scheme (공간-주파수 OFDM 전송 다이버시티 기법 기반 무선 LAN 기저대역 프로세서의 구현)

  • Jung Yunho;Noh Seungpyo;Yoon Hongil;Kim Jaeseok
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.5 s.335
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    • pp.55-62
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    • 2005
  • In this paper, we propose an efficient symbol detection algorithm for space-frequency OFDM (SF-OFDM) transmit diversity scheme and present the implementation results of the SF-OFDM WLAN baseband processor with the proposed algorithm. When the number of sub-carriers in SF-OFDM scheme is small, the interference between adjacent sub-carriers may be generated. The proposed algorithm eliminates this interference in a parallel manner and obtains a considerable performance improvement over the conventional detection algorithm. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In the case of 2 transmit and 2 receive antennas, at $BER=10^{-4}$ the proposed algorithm obtains about 3 dB gain over the conventional detection algorithm. The packet error rate (PER), link throughput, and coverage performance of the SF-OFDM WLAN with the proposed detection algorithm are also estimated. For the target throughput at $80\%$ of the peak data rate, the SF-OFDM WLAN achieves the average SNR gain of about 5.95 dB and the average coverage gain of 3.98 meter. The SF-OFDM WLAN baseband processor with the proposed algorithm was designed in a hardware description language and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. With the division-free architecture, the total logic gate count for the processor is 945K. The real-time operation is verified and evaluated using a FPGA test system.

WellnessWordNet: A Word Net for Unconstrained Subjective Well-Being Monitor ing Based on Unstructured Data and Contextual Polarity (웰니스워드넷: 비정형데이터와 상황적 긍부정성에 기반하여 주관적 웰빙 상태를 무구속적으로 모니터링하기 위한 워드넷 개발)

  • Song, Yeongeun;Nam, Suhyun;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.22 no.3
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    • pp.1-21
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    • 2016
  • IT-based subjective well-being (SWB) services, a main part of wellness IT, should measure the SWB state of individuals in an unrestrained, cost-effective manner. The dictionaries for sentiment analysis available in the market may be useful for this purpose, but obtaining proper sentiment values using only words from the sentiment lexicon is impossible; therefore, a new dictionary including wellness vocabulary is needed. The existing sentiment dictionaries link only a single sentiment value to a single sentiment word, although sentiment values may vary depending on personal traits. In this study, we develop an extended version of the SenticNet sentiment dictionary dubbed WellnessWordNet. SenticNet is considered the best and most expressive among the already existing sentiment dictionaries. Using the information provided by SenticNet, we created a database including the wellness states (estimated values) of stress, depression, and anger to develop the WellnessWordNet system. The accuracy of the system was validated through actual tests with live subjects. This study is unique and unprecedented in that i) an extended sentiment dictionary, WellnessWordNet, is developed; ii) values for wellness state language are offered; and iii) different sentiment values, namely contextual polarity, for people of the same gender or age group are suggested.

Crepe Search System Design using Web Crawling (웹 크롤링 이용한 크레페 검색 시스템 설계)

  • Kim, Hyo-Jong;Han, Kun-Hee;Shin, Seung-Soo
    • Journal of Digital Convergence
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    • v.15 no.11
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    • pp.261-269
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    • 2017
  • The purpose of this paper is to provide a search system using a method of accessing the web in real time without using a database server in order to guarantee the up-to-date information in a single network, rather than using a plurality of bots connected by a wide area network Design. The method of the research is to design and analyze the system which can search the person and keyword quickly and accurately in crepe system. In the crepe server, when the user registers information, the body tag matching conversion process stores all the information as it is, since various styles are applied to each user, such as a font, a font size, and a color. The crepe server does not cause a problem of body tag matching. However, when executing the crepe retrieval system, the style and characteristics of users can not be formalized. This problem can be solved by using the html_img_parser function and the Go language html parser package. By applying queues and multiple threads to a general-purpose web crawler, rather than a web crawler design that targets a specific site, it is possible to utilize a multiplier that quickly and efficiently searches and collects various web sites in various applications.