• Title/Summary/Keyword: 추이

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A Study on Follow-up Survey Methodology to Verify the Effectiveness of (<인생나눔교실> 사업의 효과 검증을 위한 추적 조사 방법론 연구 - 2017~2018년도 영상추적조사를 중심으로 -)

  • Lee, Dong Eun
    • Korean Association of Arts Management
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    • no.53
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    • pp.207-247
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    • 2020
  • is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

Social Network Analysis(SNA)-Based Korean Film Producer-Director-Actor Network Analysis : Focusing on Films Released Between 2013 and 2019 (한국영화 제작자·감독·배우 네트워크 분석: 2013~2019년 개봉작 중심으로)

  • Cho, Hee-Young
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.4
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    • pp.169-186
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    • 2020
  • This study selected 127 powerful Korean film producers, directors, and actors whose stable audience drawing power has been proven over the past seven years from 2013 to 2019, and viewed their network through social network analysis(SNA) to explain their power structure. It also explained the changes compared to the results of previous studies conducted on box office hits from 1998 to 2012. The producers who showed the highest audience drawing power over the past seven years were KANG Hae-jung, JANG Won-seok, LEE Eugene, HAN Jae-duk. BONG Joon-ho, KIM Yong-hwa, and RYOO Seung-wan as directors and SONG Kang-ho, HA Jung-woo, and HWANG Jung-min as actors were confirmed to exhibit the most stable audience drawing power. Meanwhile, the network formed by the 127 leading producers, filmmakers, and actors was analyzed based on closeness/ degree/eigenvector/betwenness centrality, and the result discovered a strong network involving JANG Won-seok, HAN Jae-duk, CHO Jin-woong, Don LEE, and HWANG Jung-min. This study is meaningful in that it included producers, the position which has never been discussed in previous local studies to analyze the network influencing star casting, and selected accurate box office hits by checking whether the concerned films actually reached break-even point rather than simply relying on the number of audiences or total revenue they garnered. Nonetheless, it left a hole to be filled in that it did not include the role of the management companies in the network. Therefore, a relevant follow-up discussion would be needed.

Analysis of the Present Status and Characteristics of Environmental Product Declaration of Ready-mixed Concrete (레디믹스트 콘크리트의 환경성적표지 현황 및 특성 분석)

  • Kim, Rak-Hyun;Kim, Gwang-Hyun;Park, Won-Jun;Roh, Seung-Jun
    • Journal of the Korea Institute of Building Construction
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    • v.22 no.2
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    • pp.137-148
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    • 2022
  • Recently, in the concrete industry, the development and commercialization of low-carbon products of ready-mixed concrete have emerged as part of the efforts to realize carbon neutrality. This study aims to investigate the current status of environmental product declaration(EPD) of ready-mixed concrete and to analyze the characteristics of carbon emissions by compressive strength, life cycle stage, and region. To this end, the related certification system requiring the calculation of carbon emissions in the concrete industry was analyzed. The target of analyzing the current status of carbon emissions was set as a product of ready-mixed concrete that acquired EPD certification based on the life cycle assessment method. In addition, the trend of carbon emissions according to each characteristic was reviewed by analyzing carbon emissions by the life cycle of ready-mixed concrete products, analyzing carbon emissions by standard, and analyzing carbon emissions by region. As a result, the carbon emissions in the pre-production stage were 99% compared to total carbon emissions., and as it increased from 18MPa to 40MPa, carbon emissions also increased. Even with the same specifications, the carbon emissions in the capital region were higher than in the southern region.

Prediction of KRW/USD exchange rate during the Covid-19 pandemic using SARIMA and ARDL models (SARIMA와 ARDL모형을 활용한 COVID-19 구간별 원/달러 환율 예측)

  • Oh, In-Jeong;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.28 no.4
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    • pp.191-209
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    • 2022
  • This paper is a review of studies that focus on the prediction of a won/dollar exchange rate before and after the covid 19 pandemic. The Korea economy has an unprecedent situation starting from 2021 up till 2022 where the won/dollar exchange rate has exceeded 1,400 KRW, a first time since the global financial crisis in 2008. The US Federal Reserve has raised the interest rate up to 2.5% (2022.7) called a 'Big Step' and the Korea central bank has also raised the interested rate up to 2.5% (2022.8) accordingly. In the unpredictable economic situation, the prediction of the won/dollar exchange rate has become more important than ever. The authors separated the period from 2015.Jan to 2022.Aug into three periods and built a best fitted ARIMA/ARDL prediction model using the period 1. Finally using the best the fitted prediction model, we predicted the won/dollar exchange rate for each period. The conclusions of the study were that during Period 3, when the usual relationship between exchange rates and economic factors appears, the ARDL model reflecting the variable relationship is a better predictive model, and in Period 2 of the transitional period, which deviates from the typical pattern of exchange rate and economic factors, the SARIMA model, which reflects only historical exchange rate trends, was validated as a model with a better predictive performance.

Outdoor Workers and Compensating Wage Differentials: A Comparison across Regions and Wage Levels (실외노동과 보상적 임금격차: 지역별·분위별 추이)

  • Jeong, Sangyun;Song, Changhyun;Kim, Yeonwoo;Lim, Up
    • Journal of the Korean Regional Science Association
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    • v.38 no.2
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    • pp.3-20
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    • 2022
  • The purpose of this study is to explore the heterogeneity of compensating wage differentials for outdoor workers, under the threat of climate change and heatwave, by region and by wage quantile. This study conducted Oaxaca-Blinder decomposition, multiple regression analysis by region, and unconditional quantile regression analysis using the Korean Working Conditions Survey, which provides individual-level information on the working environment and worker's characteristics. The implications derived from the results of the study are as follows: For most variables, the endowment effect and the price effect were greater for indoor workers, while experience and gender played a role in narrowing the wage gap; The compensating wage differentials for outdoor workers were confirmed to be 2.4% nationwide, depending on the region however, the compensating wage differentials varied from 5 times of national average to nothing statistically significant; The higher the wage quantile, the greater the compensating wage differentials for outdoor workers, and statistically significant monetary compensation was not identified for some low-level outdoor workers. This study is meaningful as an early study that revealed the heterogeneity of compensating wage differentials for outdoor workers and suggested further research on the topic.

Analysis and Prediction Methods of Marine Accident Patterns related to Vessel Traffic using Long Short-Term Memory Networks (장단기 기억 신경망을 활용한 선박교통 해양사고 패턴 분석 및 예측)

  • Jang, Da-Un;Kim, Joo-Sung
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.5
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    • pp.780-790
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    • 2022
  • Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

Rice Seedling Establishment for Machine Transplanting V. Effect on Endosperm Weight Change on the Seedling Growth and Regrowth After Transplanting (수도기계이앙 육묘에 관한 연구 -제5보 상자육묘시 배유양분의 소모가 묘생육 및 활착에 미치는 영향-)

  • Yun, Yong-Dae;Park, Seok-Hong
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.29 no.1
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    • pp.25-30
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    • 1984
  • Rice seedlings were raised in seedling box for rice transplanter at the temperatures of 32$^{\circ}C$ (day/1$0^{\circ}C$(night) and $25^{\circ}C$/1$0^{\circ}C$ in a phytotron. The endosperm materials were consumed more rapidly at the high temperature (32/1$0^{\circ}C$) than at the low temperature (25/1$0^{\circ}C$) and thus the leaf development was proloted at the high temperature for 15 days from the sowing. But at 35 days after sowing more leaves were developed at the low temperature than the high temperature. The short cotyledon length(5mm) before sowing was more available for the leaf development than the long cotyledon(20mm) because the endosperm materials of the former were consumed slowly. The residual of 10% endsoperm materials, when seedling age was of 2.0 to 2.1, promoted the regrowth of seedlings after machine transplanting.

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A Study on Public Awareness of Landslide and Check Dam Using the Big Data Platform 'Hyean' (공공 빅데이터 플랫폼 '혜안'을 통한 산사태 및 사방댐 인식 분석)

  • Sohee Park;Min Jeng Kang;Song Eu
    • Journal of the Society of Disaster Information
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    • v.18 no.4
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    • pp.687-698
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    • 2022
  • Purpose: This study was conducted to understand the public awareness of landslide and check dams in 2015-2020 using the big data platform 'Hyean' and to confirm the utilization of this platform in disaster prevention areas. Method: The total amount, number of detection by period by media, and affirmative and negative trends of a search for 'landslide' and 'check dam' in 2015-2020 were analyzed using a keyword search of 'Hyean.' Result: There is significant lack of public awareness of check dam compared to landslide, and the trend is more noticeable in the conspicuous gap of data amount between the news and SNS media. The number and the timing of the search for 'landslide' coincided with the actual occurrence of landslide, while the detection of 'check dam' was less related to it. Relatively affirmative preception for the check dam is inferred, but it was difficult to confirm accurate statistical affirmative and negative trends in the disaster prevention field using 'Hyean.' Conclusion: Unlike the experts who expect positive public awareness of check dam, the statistic results show that the public awareness of the check dam as an effective countermeasure against landslide was extremely low. Active promotion of erosion control projects should be carried out first, and a balanced sample survey should accompany online and periodic field surveys. Since there is a limit to grasping the effective perception in the field of disaster prevention area using 'Hyean', it should be very cautious to establish local/governmental policies using it.

A Study on the Mid- to Long-term Public Library Expansion Plan in Daegu City (대구시 중장기 공공도서관 확충방안 연구)

  • Hee-Yoon Yoon;Seon-Kyung Oh
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.3
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    • pp.97-117
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    • 2023
  • The purpose of this study is to suggest a mid- to long-term expansion plan to resolve the blind spot and alleviate the imbalance of public library services in Daegu City. The research methods for this purpose included literature review, related laws and statistical data analysis, case study, and opinion survey. As a result, the first service area was set as a total of 14 areas based on administrative districts(Jung-gu, Seo-gu, Nam-gu, and Dalseong-gun each have one, Dong-gu and Buk-gu each have two, and Suseong-gu and Dalseo-gu have three each). Second, the expansion scenario for public libraries in Daegu City was proposed to add 26 libraries by the final target year (2032) based on the trend of national library growth over the past 13 years (2008-2020) and the forecast for the next 10 years (2023-2032). Third, the construction scenarios for each basic local government, excluding the Daegu representative library, are as follows: One library each in Jung-gu, Seo-gu, and Nam-gu; two libraries in Suseong-gu; three libraries in Dalseong-gun; four libraries in Dong-gu; and seven libraries each in Buk-gu and Dalseo-gu. In terms of floor area, it is proposed to add a total of 17 branch libraries with a minimum legal standard of 330-2,499㎡, four central libraries with 2,500-4,999㎡ each, and four central libraries with 5,000-9,999㎡ each. On the premise of these conditions, Daegu City and public libraries should focus on creating an inclusive and open community space, creating a digital platform, strengthening the library operation and cooperation system centered on Daegu representative library, developing collections and specializing services for local hub libraries, enhancing various knowledge information and program services, managing key library indicators and improving social contribution.

Analysis of Research Trends in New Drug Development with Artificial Intelligence Using Text Mining (텍스트 마이닝을 이용한 인공지능 활용 신약 개발 연구 동향 분석)

  • Jae Woo Nam;Young Jun Kim
    • Journal of Life Science
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    • v.33 no.8
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    • pp.663-679
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    • 2023
  • This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.