• 제목/요약/키워드: Big Data Trend Analysis

검색결과 327건 처리시간 0.03초

Thermoreflectance Microscopy for Thermal Analysis of Electronics (전자소자 열분석을 위한 열반사 현미경 기술)

  • Kim, Hyeon-Beom;Lee, Seunghwan;Jang, Hyejin
    • Journal of the Microelectronics and Packaging Society
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    • 제29권2호
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    • pp.19-31
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    • 2022
  • With the advent of technologies based on big data, the trend of electronics towards high performance and high integration density continues. However, this development of electronics suffers from overheating issues, which seriously threaten the reliability of the devices. To develop effective strategies for thermal management, it is crucial to accurately evaluate the temperature distribution and design the heat dissipation path within the device in the operating condition. This paper introduces thermoreflectance microscopy that can observe the temperature distribution of a device with high spatial and temporal resolutions in a non-contact way. Specifically, the working principle and various forms of thermoreflectance microscopy are presented along with the latest research trends to improve the temperature, space, and time resolutions. We further review several examples in which thermoreflectance microscopy is applied to investigate the temperature and thermal characteristics of electronic devices.

New Distribution Strategies of Korean SMEs in Post COVID-19 Pandemic Era: Focusing on the Innovation of Official Distribution Channels

  • Lee, Min-Jae;Jung, Jin-Sup
    • Journal of Korea Trade
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    • 제25권3호
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    • pp.153-168
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    • 2021
  • Purpose - In this study, we aim to explore new distribution strategies for sustainable growth in the era of the 4th industrial revolution, focusing on SMEs (small and medium-sized enterprises) in Korea, and suggest ways to upgrade the government's official distribution channel to the next level. Design/methodology - First of all, this paper explored the prior research, the current status of sales support for SMEs, and the changes in the distribution industry due to COVID-19 pandemic. Based on Moon (2016)'s ABCD strategic model - Agility, Benchmarking, Convergence, and Dedication, the study then derived directions in which official distribution channels should move and the new distribution strategy for Korean SMEs to secure competitive advantage. Findings - First, in terms of 'Agility', in order to upgrade official distribution channels, which are currently at some competitive disadvantages compared to private distribution companies, we must quickly introduce technologies for the 4th industrial revolution, such as AI, Big Data, etc., and establish precise strategies to strengthen the capabilities of SMEs. Second, in terms of 'Benchmarking', the use of "Chamelezones" has been increasing to enhance the competitiveness of offline stores in line with recent ontact trends. Therefore, official distribution channels should also benchmark such cases, strengthening their competitiveness by utilizing offline spaces more efficiently and effectively. Third, in terms of 'Convergence', in line with the rapidly changing trend of the times, official distribution channels should also promote active partnerships with media commerce, e-commerce and ICT platforms, as well as cooperation with private retailers, and focus on creating synergy effects through them. Finally, from the perspective of 'Dedication', digitalization should be promoted step by step, finding the sector that can accelerate digital among the value chains of official distribution channels, and continuing to discuss how to digitize it realistically. Originality/value - Based on this analysis, we have presented strategies and implications for innovating official distribution channels for SMEs, which will contribute to enhancing the competitive advantage of official distribution channels in the post COVID-19 pandemic era.

Trend Analysis of Intelligent Cyber Attacks on Power Systems (전력시스템 대상 지능형 사이버공격 동향 분석)

  • Soon-Min Hong;Jung-ho Eom;Jae-Kyung Lee
    • Convergence Security Journal
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    • 제23권3호
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    • pp.21-28
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    • 2023
  • The development of information and communication technology in the 21st century has increased operational efficiency by providing hyper-connectivity and hyper-intelligence in the control systems of major infrastructure, but is also increasing security vulnerabilities, exposing it to hacking threats. Among them, the electric power system that supplies electric power essential for daily life has become a major target of cyber-attacks as a national critical infrastructure system. Recently, in order to protect these power systems, various security systems have been developed and the stability of the power systems has been maintained through practical cyber battle training. However, as cyber-attacks are combined with advanced ICT technologies such as artificial intelligence and big data, it is not easy to defend cyber-attacks that are becoming more intelligent with existing security systems. In order to defend against such intelligent cyber-attacks, it is necessary to know the types and aspects of intelligent cyber-attacks in advance. In this study, we analyzed the evolution of cyber attacks combined with advanced ICT technology.

Occupational Therapy in Long-Term Care Insurance For the Elderly Using Text Mining (텍스트 마이닝을 활용한 노인장기요양보험에서의 작업치료: 2007-2018년)

  • Cho, Min Seok;Baek, Soon Hyung;Park, Eom-Ji;Park, Soo Hee
    • Journal of Society of Occupational Therapy for the Aged and Dementia
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    • 제12권2호
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    • pp.67-74
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    • 2018
  • Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.

Case Analysis on High Concentration of SO2 and Review on Its Reduction Policy in the Ulsan Metropolitan Area since 2001 (울산 지역에서 2001년 이후 이산화황(SO2)의 고농도 사례 분석과 저감 정책 방안의 검토)

  • Moon, Yun-Seob
    • Journal of Environmental Science International
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    • 제17권4호
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    • pp.423-437
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    • 2008
  • Until comparatively lately, the annual time series of the $SO_2$ concentration had been shown in a decreasing trend in Ulsan as well as other Korean cities. However, the high concentration of $SO_2$ was frequently found in the specific countermeasure region including the national industrial complex such as Mipo and Onsan in the Ulsan city for the period of $2001{\sim}2004$. There are many conditions that can influence the high concentration of $SO_2$ at monitoring sites in Ulsan, such as: First, annual usage of the fuel including sulfur increased in comparison with the year before in spite of the fuel conversion policy which wants to use low sulfur oil less than 3% and LNG. Second, point source, such as the power plants and the petroleum and chemistry stacks, was the biggest contributor in $SO_2$ emission, as a analyzed result of both the air quality modeling and the stack tole-monitoring system (TMS) data. And third, the air pollutants that occurred in processes of homing and manufacturing of the fuel including sulfur were transported slow into a special monitoring site by accumulating along the frontal area of see-breeze. It was concluded that Ulsan's current environmental policy together with control methods should be changed into the regulation on total amount of emission, including a market-based emission trading with calculating of atmospheric environmental critical loads, for the $SO_2$ reduction like the specific countermeasure for the $O_3$ and PM10 reduction in the Seoul metropolitan area. And this change should be started in the big point sources of $1{\sim}3$ species because they are big contributors of Ulsan's $SO_2$ pollution. Especially it is necessary to revitalize of the self-regulation environmental management. Other control methods for sustaining the $SO_2$ reduction are as follows: maintenance of the fuel conversion policy, reinforcement of the regional stationary source emission standard, and enlargement of the stack TMS.

A Study on Smart Ground Resistance Measurement Technology Based on Aduino (아두이노 기반 IT융합 스마트 대지저항 측정 기술 연구)

  • Kim, Hong Yong
    • Journal of the Society of Disaster Information
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    • 제17권4호
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    • pp.684-693
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    • 2021
  • Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

An Investigation on Digital Humanities Research Trend by Analyzing the Papers of Digital Humanities Conferences (디지털 인문학 연구 동향 분석 - Digital Humanities 학술대회 논문을 중심으로 -)

  • Chung, EunKyung
    • Journal of the Korean Society for Library and Information Science
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    • 제55권1호
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    • pp.393-413
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    • 2021
  • Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.

Utilization of Smart Farms in Open-field Agriculture Based on Digital Twin (디지털 트윈 기반 노지스마트팜 활용방안)

  • Kim, Sukgu
    • Proceedings of the Korean Society of Crop Science Conference
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    • 한국작물학회 2023년도 춘계학술대회
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    • pp.7-7
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    • 2023
  • Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

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Investigating Dynamic Mutation Process of Issues Using Unstructured Text Analysis (비정형 텍스트 분석을 활용한 이슈의 동적 변이과정 고찰)

  • Lim, Myungsu;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • 제22권1호
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    • pp.1-18
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    • 2016
  • Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

A Study on the Research Trends in Fintech using Topic Modeling (토픽 모델링을 이용한 핀테크 기술 동향 분석)

  • Kim, TaeKyung;Choi, HoeRyeon;Lee, HongChul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제17권11호
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    • pp.670-681
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    • 2016
  • Recently, based on Internet and mobile environments, the Fintech industry that fuses finance and IT together has been rapidly growing and Fintech services armed with simplicity and convenience have been leading the conversion of all financial services into online and mobile services. However, despite the rapid growth of the Fintech industry, few studies have classified Fintech technologies into detailed technologies, analyzed the technology development trends of major market countries, and supported technology planning. In this respect, using Fintech technological data in the form of unstructured data, the present study extracts and defines detailed Fintech technologies through the topic modeling technique. Thereafter, hot and cold topics of the derived detailed Fintech technologies are identified to determine the trend of Fintech technologies. In addition, the trends of technology development in the USA, South Korea, and China, which are major market countries for major Fintech industrial technologies, are analyzed. Finally, through the analyses of networks between detailed Fintech technologies, linkages between the technologies are examined. The trends of Fintech industrial technologies identified in the present study are expected to be effectively utilized for the establishment of policies in the area of the Fintech industry and Fintech related enterprises' establishment of technology strategies.