• Journal of the Institute of Convergence Signal Processing
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• 제24권1호
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• pp.42-50
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• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.

• Journal of Service Research and Studies
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• 제14권2호
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.

• The Transactions of the Korea Information Processing Society
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• 제13권5호
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Information Systems Review
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• 제22권1호
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• pp.17-31
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• 2020

With the start of the fourth industrial revolution era, technologies of various fields are merged and new types of technologies and products are being developed. In addition, the importance of the registration of intellectual property rights and patent registration to gain market dominance of them is increasing in oversea as well as in domestic. Accordingly, the number of patents to be processed per examiner is increasing every year, so time and cost for prior art research are increasing. Therefore, a number of researches have been carried out to reduce examination time and cost for patent-pending technology. This paper proposes a method to calculate the degree of similarity among patent documents of the same priority claim when a plurality of patent rights priority claims are filed and to provide them to the examiner and the patent applicant. To this end, we preprocessed the data of the existing irregular patent documents, used Word2vec to obtain similarity between patent documents, and then proposed recommendation model that recommends a similar patent document in descending order of score. This makes it possible to promptly refer to the examination history of patent documents judged to be similar at the time of examination by the examiner, thereby reducing the burden of work and enabling efficient search in the applicant's prior art research. We expect it will contribute greatly.

• The Korean Journal of Archival Studies
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• 제79호
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• pp.471-513
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• 2024

The monthly news and culture magazine, 'Sasanggye,' established by Jang Jun-ha from 1953 to 1970, served as a platform for government criticism and intellectual representation. The magazine created photographic-essays covering a variety of topics and utilized images as a visually impactful tool with news value. This paper aims to critically examine the photographic-essays within 'Sasanggye' as archival records, shedding light on their intrinsic value. Before delving into this assessment, the paper thoroughly explores the developmental process and characteristics of these photographic-essays. And based on the content divisions within the main text, the paper categorized the themes captured in the photographic essays into politics, economics, society, culture, and miscellaneous topics. It then introduced representative photographicessays. From an archival perspective, looking at photographs involves elucidating that photographs carry meanings beyond mere data. The photographic essays in 'Sasanggye' serve as photographic records providing evidence of 1960s Korean society and encapsulating crucial visual information. Furthermore, the photographic essays in 'Sasanggye' hold a historical significance in the aspect of Korean magazine documentary photography. The photo-essays in 'Sasanggye' carry worth in the history of photography and encompass evidential and informational values as photographic records.

• Journal of The Korean Association For Science Education
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• 제44권1호
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• pp.39-55
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• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.

• Journal of Navigation and Port Research
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• 제48권1호
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• pp.34-48
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• 2024

As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.

• Journal of the Korean Society for information Management
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• 제41권1호
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.540-543
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• 2007

최근의 그리드 컴퓨팅 시스템 환경은 단일 환경에서 작게는 2~4CPU, 많게는 수백 CPU 이상의 시스템으로 구축되고 있고, 더욱이 지역적으로도 멀리 떨어져 있다. 따라서 이를 운용하는 기업에서는 시스템의 사용 현황을 신속하게 분석할 필요가 있다. 그러나 이렇게 혼재된 이 기종 및 컴퓨팅 환경하에서의 각 지역별 시스템 사용현황을 효과적으로 분석 한다는 것은 매우 어려운 일이다. 기존에 사용되어 온 그리드 컴퓨팅 시스템 환경에서의 사용율 관리 방법들은 Queueing 시스템이 가지고 있는 Accounting 분석 명령어로 text 형태의 Accounting raw data 의 결과를 추출하여 가공 처리하므로 데이터 증가 시 반응 속도가 현격하게 느려지는 상황이 발생한다. 또한 원격지 그리드 컴퓨팅 시스템 군의 사용율 분석은 데이터 분석 시 매번 원격지접근 절차를 사용하여 그리드 컴퓨팅 시스템 군에 접근한 후 해당 로컬 시스템 분석을 해야 하고 각 원격지시스템군별로 추출 된 데이터를 통합 관리해야 하는 문제점을 가지고 있다. 따라서 이러한 문제점을 해결하고자 하는 것이 본 논문에서 제안하는 3-tier 구조의 GSA(Grid System Account)이다. 제안한 GSA 는 각 원격지 별 데이터를 객체화하여 Database 에 저장 함으로써 데이터 분석 시 효과적으로 처리할 수 있으며, 다수의 원격지 그리드 컴퓨팅 시스템 군에 대한 복합적인 분석이 필요할 때 효율적으로 대처할 수 있다. 본 논문에서는 GSA 의 설계방법을 제안하고 구현하여 실 성능을 시험함으로써 보다 효율적인 그리드 컴퓨팅 시스템의 사용율 분석 관리가 가능함을 보였다.포는 감수성을 보이지 않았다. 따라서 위의 결과로부터 SLT-I에 감수성을 보이지 않은 Raw264.7세포를 대상으로 Gb3 발현 정도와 SLT-I의 세포독성의 관계를 규명하고자 Gb3의 발현을 증가시킨 후 SLT-I의 세포독성을 재차 평가하였다. 이 결과 $TNF-{\alpha}$의 처리에 의하여 6 hrs에 Gb3의 발현이 정점(43.5%)에 이르렀으며 36 hrs에 정상 수준(25.0%)으로 환원되었다. 그러나, Gb3의 발현이 증가함에도 불구하고 SLT-I의 세포독성에는 변화가 관찰되지 않았다. 따라서, SLT-I에 의한 세포독성은 세포의 종류에 따라서 다르며 또한, Gb3의 발현정도에만 의존적이지는 않을 것으로 생각된다. 이와 같은 결과는 E. coli 0157의 감염증 병인 연구에 있어 SLT-I과 Gb3의 발현의 상관관계에 대한 보다 심도 있는 연구가 필요함을 시사한다.만 분할률, 배반포 형성률 및 배반포의 세포수를 증가시키는 것으로 사료된다.수의 유출입 지점에 온도센서를 부착하여 냉각수의 온도를 측정하고 냉각수의 공급량과 대기의 온도 등을 측정하여 대사열의 발생을 추정할 수 있었다. 동시에 이를 이용하여 유가배양시 기질을 공급하는 공정변수로 사용하였다 [8]. 생물학적인 폐수처리장치인 활성 슬러지법에서 미생물의 활성을 측정하는 방법은 아직 그다지 개발되어있지 않다. 본 연구에서는 슬러지의 주 구성원이 미생물인 점에 착안하여 침전시 슬러지층과 상등액의 온도차를 측정하여 대사열량의 발생량을 측정하고 슬러지의 활성을 측정할 수 있는 방법을 개발하였다.enin과 Rhaponticin의 작용(作用)에 의(依)한 것이며, 이

• Journal of the Korean Society for information Management
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• 제30권1호
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• pp.7-32
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• 2013

The goal of the present study is to identify the topic trend in the field of library and information science in Korea. To this end, we collected titles and s of the papers published in four major journals such as Journal of the Korean Society for information Management, Journal of the Korean Society for Library and Information Science, Journal of Korean Library and Information Science Society, and Journal of the Korean BIBLIA Society for library and Information Science during 1970 and 2012. After that, we applied the well-received topic modeling technique, Latent Dirichlet Allocation(LDA), to the collected data sets. The research findings of the study are as follows: 1) Comparison of the extracted topics by LDA with the subject headings of library and information science shows that there are several distinct sub-research domains strongly tied with the field. Those include library and society in the domain of "introduction to library and information science," professionalism, library and information policy in the domain of "library system," library evaluation in the domain of "library management," collection development and management, information service in the domain of "library service," services by library type, user training/information literacy, service evaluation, classification/cataloging/meta-data in the domain of "document organization," bibliometrics/digital libraries/user study/internet/expert system/information retrieval/information system in the domain of "information science," antique documents in the domain of "bibliography," books/publications in the domain of "publication," and archival study. The results indicate that among these sub-domains, information science and library services are two most focused domains. Second, we observe that there is the growing trend in the research topics such as service and evaluation by library type, internet, and meta-data, but the research topics such as book, classification, and cataloging reveal the declining trend. Third, analysis by journal show that in Journal of the Korean Society for information Management, information science related topics appear more frequently than library science related topics whereas library science related topics are more popular in the other three journals studied in this paper.