• Title/Summary/Keyword: 과학기술 데이터

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Development for Worker Safety Management System on the EOS Blockchain (EOS 블록체인 기반의 작업자 안전관리 시스템 개발)

  • Jo, Yeon-Jeong;Eom, Hyun-Min;Sim, Chae-Lin;Koo, Hyeong-Seo;Lee, Myung-Joon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.10
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    • pp.797-808
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    • 2019
  • In a closed workplace, the management of the workplace is important because the environmental data at the workplace has a great influence on the safety of workers. Today's industrial sites are transformed into data-based factories that collect and analyze data through sensors in those sites, requiring a management system to ensure safety. In general, a safety management system stores and manages data on a central server associated with a database. Since such management system introduces high possibility of forgery and loss of data, workers often suspect the reliability of the information on the management system. In this paper, we present a worker safety management system based on the EOS blockchain which is considered as third-generation blockchain technology. The developed system consists of a set of smart contracts on the EOS blockchain and 3 decentralized applications associated with the blockchain. According to the roles of users, the worker and manager applications respectively perform the process of initiating or terminating tasks as blockchain transactions. The entire transaction history is distributed and stored in all nodes participating in the blockchain network, so forgery and loss of data is practically impossible. The system administrator application assigns the account rights of workers and managers appropriate for performing the functions, and specifies the safety standards of IoT data for ensuring workplace safety. The IoT data received from sensor platforms in workplaces and the information on initiation, termination or approval of tasks assigned to workers, are explicitly stored and managed in the EOS smart contracts.

Epistemic Level in Middle School Students' Small-Group Argumentation Using First-Hand or Second-Hand Data (데이터 출처 유형에 따른 중학생의 소집단 논변활동의 인식론적 수준)

  • Cho, Hyun-A;Chang, Ji-Eun;Kim, Heui-Baik
    • Journal of The Korean Association For Science Education
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    • v.33 no.2
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    • pp.486-500
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    • 2013
  • This study is conducted to examine how epistemic reasoning and argument structures of students vary according to data sources used in the process of argumentation implemented in the context of inquiry. To this end, three argument tasks using first-hand data and three argument tasks using second-hand data were developed and applied to the unit on 'Nutrition of Plants' for first year middle school students. According to the results of this study, epistemic reasoning of students manifested during the process of argumentation and varied according to data sources. While most students composed explanations with phenomenon-based or relation-based reasoning in argumentation using first-hand data, all the small groups composed explanations that included model-based reasoning in argumentation using second-hand data. In the case of arguments including phenomenon-based or relation-based reasoning, students described only observable characteristics, with warrants omitted from arguments in many cases. On the other hand, in the case of arguments that included model-based reasoning, explanations were composed by combining the results of observations with theoretical knowledge, with warrants more apparent in their arguments.

The Effects of Socioscientific Issue (SSI)-Based Instruction on Underachieving 9th-Grade Students: Achievement, Attitudes, and Scientific Participation and Lifelong Learning Competency (과학기술 관련 사회쟁점(SSI) 기반 수업이 중학교 3학년 과학 학습부진 학생의 기초 학업성취도, 과학학습에 대한 태도 및 과학적 참여와 평생학습 역량에 미치는 효과)

  • Jin-Kyong Hur;Nam-Hwa Kang
    • Journal of Science Education
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    • v.47 no.1
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    • pp.11-23
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    • 2023
  • In this study, we examined the effect of socioscientific issue (SSI) based science lessons on underachieving 9th-grade students. A total of seven lessons centered on two SSIs related to the national science curriculum were developed and implemented during the first semester of 2021. Data were collected from 185 9th-grade students in one middle school in a mid-sized city of South Korea. Among them, 37 were identified as achieving far below the standards (underachieving students hereafter). Quantitative data were collected from pre- and post-tests on basic science content and attitudes and competency measures. To supplement quantitative data, lesson observation notes were recorded, and student interviews with a selected number of students were conducted. The analysis of quantitative data was conducted through the Wilcoxon Signed Rank Test and paired t-tests. Qualitative data were analyzed to find reasons for changing attitudes. The findings showed that the SSI-based lessons were more effective on underachieving students than the others in enhancing basic academic achievement, while there was no significant effect on all in attitudes and competency. Lesson observation data showed that underachieving students were more engaged in SSI-based lessons than before. Student interviews demonstrated several reasons why they were engaged, suggesting the aspects of SSI-based lessons that facilitated underachieving students' learning. Further research topics are suggested.

The Effectiveness of Fiscal Policies for R&D Investment (R&D 투자 촉진을 위한 재정지원정책의 효과분석)

  • Song, Jong-Guk;Kim, Hyuk-Joon
    • Journal of Technology Innovation
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    • v.17 no.1
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    • pp.1-48
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    • 2009
  • Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

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Rank Correlation Coefficient of Energy Data for Identification of Abnormal Sensors in Buildings (에너지 데이터의 순위상관계수 기반 건물 내 오작동 기기 탐지)

  • Kim, Naeon;Jeong, Sihyun;Jang, Boyeon;Kim, Chong-Kwon
    • Journal of KIISE
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    • v.44 no.4
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    • pp.417-422
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    • 2017
  • Anomaly detection is the identification of data that do not conform to a normal pattern or behavior model in a dataset. It can be utilized for detecting errors among data generated by devices or user behavior change in a social network data set. In this study, we proposed a new approach using rank correlation coefficient to efficiently detect abnormal data in devices of a building. With the increased push for energy conservation, many energy efficiency solutions have been proposed over the years. HVAC (Heating, Ventilating and Air Conditioning) system monitors and manages thousands of sensors such as thermostats, air conditioners, and lighting in large buildings. Currently, operators use the building's HVAC system for controlling efficient energy consumption. By using the proposed approach, it is possible to observe changes of ranking relationship between the devices in HVAC system and identify abnormal behavior in social network.

An Analysis System Using Big Data based Real Time Monitoring of Vital Sign: Focused on Measuring Baseball Defense Ability (빅데이터 기반의 실시간 생체 신호 모니터링을 이용한 분석시스템: 야구 수비능력 측정을 중심으로)

  • Oh, Young-Hwan
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.1
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    • pp.221-228
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    • 2018
  • Big data is an important keyword in World's Fourth Industrial Revolution in public and private division including IoT(Internet of Things), AI(Artificial Intelligence) and Cloud system in the fields of science, technology, industry and society. Big data based on services are available in various fields such as transportation, weather, medical care, and marketing. In particular, in the field of sports, various types of bio-signals can be collected and managed by the appearance of a wearable device that can measure vital signs in training or rehabilitation for daily life rather than a hospital or a rehabilitation center. However, research on big data with vital signs from wearable devices for training and rehabilitation for baseball players have not yet been stimulated. Therefore, in this paper, we propose a system for baseball infield and outfield players, especially which can store and analyze the momentum measurement vital signals based on big data.

Study on Design of Protest Song Metadata based on OAIS Reference Model (OAIS 참조모형 기반 민중가요 메타데이터 설계에 관한 연구)

  • Kang, Minjeong;Chang, Wookwon
    • Journal of Korean Society of Archives and Records Management
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    • v.21 no.1
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    • pp.211-230
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    • 2021
  • This study aims to design folk song metadata based on the OAIS reference model for the folk songs' preservation and permanent use. Thus, the folk songs' general characteristics were investigated by researching literature and related technical standards. The type of records, the methods and standards for long-term storage of records, OAIS reference models, and each package's metadata elements were identified through opinions from the popular songs' creators and researchers. The results awere that first, folk songs were created for social transformation, serving as a cultural heritage different from popular songs given their noncommercial quality. Second, the types of folk song records were identified, and the long-term preservation system suitable for the types of records was based on the OAIS reference model. Third, the metadata were edited, and the OIS reference model was applied such that respect was given to the folk songs' characteristics, context, and original order. Fourth and last, information package metadata elements matching the folk songs' records were derived and applied to the representative Korean folk song, "The March for Being."

Spectogram analysis of active power of appliances and LSTM-based Energy Disaggregation (다수 가전기기 유효전력의 스팩토그램 분석 및 LSTM기반의 전력 분해 알고리즘)

  • Kim, Imgyu;Kim, Hyuncheol;Kim, Seung Yun;Shin, Sangyong
    • Journal of the Korea Convergence Society
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    • v.12 no.2
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    • pp.21-28
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    • 2021
  • In this study, we propose a deep learning-based NILM technique using actual measured power data for 5 kinds of home appliances and verify its effectiveness. For about 3 weeks, the active power of the central power measuring device and five kinds of home appliances (refrigerator, induction, TV, washing machine, air cleaner) was individually measured. The preprocessing method of the measured data was introduced, and characteristics of each household appliance were analyzed through spectogram analysis. The characteristics of each household appliance are organized into a learning data set. All the power data measured by the central power measuring device and 5 kinds of home appliances were time-series mapping, and training was performed using a LSTM neural network, which is excellent for time series data prediction. An algorithm that can disaggregate five types of energies using only the power data of the main central power measuring device is proposed.

Comparative Study of US-China Discourse on Cross-border Data Regulation and Cybersecurity: Focusing on ASEAN Development Assistance Cases (미·중 초국경 데이터 규제와 사이버안보 담론 비교: 아세안 개발원조 사례를 중심으로)

  • Kayeon Lee
    • Informatization Policy
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    • v.30 no.1
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    • pp.89-108
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    • 2023
  • Science, technology and innovation (STI) has expanded the activity of actors from the traditional physical territory to the cyberspace. Data-driven platform services and markets advance new discussions on cross-border cooperation and cyber security, as well as discourse on sovereignty in cyberspace. These changes are also affecting the hegemony competition between the US and China. In particular, competition for aid to developing countries that are located along major resource transportation routes, such as natural gas and deep sea resources, is fierce. ASEAN is not only a geopolitical military and security point where the US and China powers collide, but its population of 600 million has great potential for the development of the digital economy due to its data resources. In this regard, this article aims to connect the discourse of liberalism and authoritarianism with data regulation and cybersecurity in international development cooperation, and derive implications for ASEAN integration through this. This study has significance as a convergence study that links international political issues related to big data in terms of global governance.

Patterns of Student Evaluation on Media Information Regarding Socioscientific Issues (과학기술관련 사회쟁점 미디어 정보에 대한 중학생들의 평가 양상 탐색)

  • Jo, Serin;Ko, Yeonjoo;Lee, Hyunju
    • Journal of The Korean Association For Science Education
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    • v.41 no.1
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    • pp.59-70
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    • 2021
  • Ability to make informed decisions by critically evaluating media information on socioscientific issues (SSI) is one of the crucial elements of scientific literacy that citizens should obtain. This study aims to investigate how middle school students evaluated media information about socioscientific issues (SSI) when they faced two different types of information (i.e., numerical and empathic information). To achieve the aim, 96 middle school students responded to the questionnaires asking them to evaluate reliability and persuasiveness of SSI media information. The questionnaires consisted of two sets of newspaper articles on each SSI (pro-numerical/empathic, against-numerical/empathic). After reading the articles, the students evaluated reliability and persuasiveness of each article and wrote the reasons for their evaluation. The results were as follows: First, the students believed that news articles with numerical information were more reliable than the ones with empathic information in all SSI contexts. They tended to trust scientific evidence and data from numerical information, and real cases, societal problems, expressions, and values from empathic information. In addition, they evaluated their reliability based on the logic of information, accuracy of information, breadth and depth of data, and quantity and quality of sources both numerical and empathic information. Second, in case of evaluating persuasiveness of the articles, they focused more on the values that information contained, richness and logicality of the information, rather than the types of information, regardless of the type of information.