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A Study on the Connective Validity of Technology Maturity and Industry for Core Technologies based on 4th Industrial Revolution (4차 산업혁명 기반 핵심기술에 대한 기술성숙도와 산업과 연계 타당성 연구)

  • Cho, Han-Jin;Jeong, Kyuman
    • Journal of the Korea Convergence Society
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    • v.10 no.3
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    • pp.49-57
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    • 2019
  • The core technology development of the Fourth Industrial Revolution is linked to the development of other core technologies, which will change the industrial structure in the future and create a new smart business model. In this paper, tried to analyze the technology maturity level and analyze the technology maturity. To do this, used technology trend information to investigate and integrate the market, policy, etc. Of core technology of the 4th Industrial Revolution to achieve a comprehensive maturity level. Because technology maturity measures are scored by technology developers, prejudices may be acted upon according to a person's tendency, which may be a subjective evaluation. It is also a measure of the maturity of individual technologies, and thus is not suitable for evaluating the overall system integration perspective. However, it is possible to evaluate the maturity before integrating the core element technologies constituting the whole system and to use it as a means to compare the effect of the whole system and its feasibility and play an important role in the planning of technology development.

Monetary policy synchronization of Korea and United States reflected in the statements (통화정책 결정문에 나타난 한미 통화정책 동조화 현상 분석)

  • Chang, Youngjae
    • The Korean Journal of Applied Statistics
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    • v.34 no.1
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    • pp.115-126
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    • 2021
  • Central banks communicate with the market through a statement on the direction of monetary policy while implementing monetary policy. The rapid contraction of the global economy due to the recent Covid-19 pandemic could be compared to the crisis situation during the 2008 global financial crisis. In this paper, we analyzed the text data from the monetary policy statements of the Bank of Korea and Fed reflecting monetary policy directions focusing on how they were affected in the face of a global crisis. For analysis, we collected the text data of the two countries' monetary policy direction reports published from October 1999 to September 2020. We examined the semantic features using word cloud and word embedding, and analyzed the trend of the similarity between two countries' documents through a piecewise regression tree model. The visualization result shows that both the Bank of Korea and the US Fed have published the statements with refined words of clear meaning for transparent and effective communication with the market. The analysis of the dissimilarity trend of documents in both countries also shows that there exists a sense of synchronization between them as the rapid changes in the global economic environment affect monetary policy.

Exploring Issues Related to the Metaverse from the Educational Perspective Using Text Mining Techniques - Focusing on News Big Data (텍스트마이닝 기법을 활용한 교육관점에서의 메타버스 관련 이슈 탐색 - 뉴스 빅데이터를 중심으로)

  • Park, Ju-Yeon;Jeong, Do-Heon
    • Journal of Industrial Convergence
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    • v.20 no.6
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    • pp.27-35
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    • 2022
  • The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

An Analysis of 3D Mesh Accuracy and Completeness of Combination of Drone and Smartphone Images for Building 3D Modeling (건물3D모델링을 위한 드론과 스마트폰영상 조합의 3D메쉬 정확도 및 완성도 분석)

  • Han, Seung-Hee;Yoo, Sang-Hyeon
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.1
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    • pp.69-80
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    • 2022
  • Drone photogrammetry generally acquires images vertically or obliquely from above, so when photographing for the purpose of three-dimensional modeling, image matching for the ground of a building and spatial accuracy of point cloud data are poor, resulting in poor 3D mesh completeness. Therefore, to overcome this, this study analyzed the spatial accuracy of each drone image by acquiring smartphone images from the ground, and evaluated the accuracy improvement and completeness of 3D mesh when the smartphone image is not combined with the drone image. As a result of the study, the horizontal (x,y) accuracy of drone photogrammetry was about 1/200,000, similar to that of traditional photogrammetry. In addition, it was analyzed that the accuracy according to the photographing method was more affected by the photographing angle of the object than the increase in the number of photos. In the case of the smartphone image combination, the accuracy was not significantly affected, but the completeness of the 3D mesh was able to obtain a 3D mesh of about LoD3 that satisfies the digital twin city standard. Therefore, it is judged that it can be sufficiently used to build a 3D model for digital twin city by combining drone images and smartphones or DSLR images taken on the ground.

The Process of Forming Ego and the Impact of Others on the Teaching Careers of Students Majoring in Science Education: A Lacanian Psychoanalytic Inquiry (사범대학 과학교육전공 재학생들의 교직에 대한 자아형성 과정과 타자의 영향 -Lacan의 정신분석학적 탐구-)

  • Hyojeong Hwang;Eunju Park;Jun-Ki Lee
    • Journal of The Korean Association For Science Education
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    • v.43 no.4
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    • pp.333-349
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    • 2023
  • This study employs Lacan's psychoanalytic approach to reinterpret the images of others and teachers that influence the process of self-formation within the teaching profession as students enter a university of education Seventy-four first- and second-year students majoring in science education at the College of Education from three regions across the country participated in this study, which was conducted using Lacan's L schematic as a representative theoretical framework. Through qualitative analysis and a word cloud analysis, it was confirmed that the students developed perceptions of the teaching profession based on somewhat fictitious and unrealistic teacher images, while others actively intervened in the process of career decision-making. In addition, although parents or teachers mainly occupied the realm of the Other, it was found that they failed to appropriately fulfill the role of the Other, in that they should have corrected the fictional image of teachers. Accordingly, it is necessary to recognize the limitations of ego-psychological career education that can deepen fixations on distorted self-images and, therefore, seek a new career education and counseling model through a psychoanalytic approach.

An Improvement of Kubernetes Auto-Scaling Based on Multivariate Time Series Analysis (다변량 시계열 분석에 기반한 쿠버네티스 오토-스케일링 개선)

  • Kim, Yong Hae;Kim, Young Han
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.3
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    • pp.73-82
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    • 2022
  • Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

The Research Features Analysis of Leisure and Recreation based on Co-authors Network and Topic Model (공저자 네트워크 및 토픽 모델링 기반 여가레크리에이션 학술 연구 특징 분석)

  • Park, SungGeon;Park, Kwang-Won;Kang, Hyun-Wook
    • 한국체육학회지인문사회과학편
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    • v.57 no.2
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    • pp.279-289
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    • 2018
  • The purpose of this study is to investigate features of leisure and recreation scholarship study in The Korean Journal of physical education based on co-authors network and topic modeling through using Word Cloud and LDA Topic Modeling(Latent Dirichlet Allocation). The data collected for this study are 2,697 papers published online from January 2008 to March 2017 on the Korean journal of physical education. Respectively ordered analysis targets are the major author, author of correspondence, co-author 1, co-author 2, co-author n in related document to explore studies' trends using the 369 documents. As a result, the co-author network analysis result found that 451 were linked to the research network, on average researchers had 1.52 relationships and the average distance between researchers was 2.33. The Representative author's concentration of connection was ranked high in the order of the following, Lee. K. M., Hwang. S. H., H., Lee. C. S., and proximity centers were shown in Seo K. B., Han. J. H., Kim. K. J. Finally, parameter-centric features appeared in order of Lee. C. W. and Seo. K. B. was most actively connected between the researchers of the leisure-related academic papers. Future research needs discussions among scholars regarding the trend and direction of future leisure research.

Mixing Characteristics of Nonconservative Pollutants in Paldang Lake (팔당호에 유입된 비보존성 오염물질의 혼합거동)

  • Seo, Il Won;Choi, Nam Jeong;Jun, In Ok;Song, Chang Geun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.3B
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    • pp.221-230
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    • 2009
  • In Korea, many water intake plants are easily affected by effluents of sewage treatment plants because sewage treatment plants are usually located upstream or nearby the plants of the same riverine area. Furthermore, the inflow of harmful contaminants owing to pollutant spills or transportation accidents of vehicles using the roads and bridges intersecting the river causes significant impact on the management of water intake plants. Paldang lake, the main water intake plants in Korea, is especially exposed to various water pollution accidents, because the drainage basin area is significantly large compared to the water surface area of the lake. Therefore it is necessary to predict the possible pollutant spill in advance and consider measurements in case of water pollution. In this study, water quality prediction was performed in Paldang Lake in Korea durig the dry season using two-dimensional numerical models. In order to represent the cases of pollutant accidents, the difference of pollutant transport patterns with varying injection points was analyzed. Numerical simulations for hydrodynamics of water flow and water quality predictions were performed using RMA-2 and RAM4 respectively. As a result of simulation, the difference of pollutant transport with the injection points was analyzed. As a countermeasure against the pollutant accident, the augmentation of the flow rate is proposed. In comparison with the present state, the rapid dilution and flushing effects on the pollutant cloud could be expected with increase of flow rate. Thus, increase of flow rate can be used for operation of water intake plants in case of pollutant spill accidents.

A Study on Intelligent Self-Recovery Technologies for Cyber Assets to Actively Respond to Cyberattacks (사이버 공격에 능동대응하기 위한 사이버 자산의 지능형 자가복구기술 연구)

  • Se-ho Choi;Hang-sup Lim;Jung-young Choi;Oh-jin Kwon;Dong-kyoo Shin
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.137-144
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    • 2023
  • Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

Retrieval of High Resolution Surface Net Radiation for Urban Area Using Satellite and CFD Model Data Fusion (위성 및 CFD모델 자료의 융합을 통한 도시지역에서의 고해상도 지표 순복사 산출)

  • Kim, Honghee;Lee, Darae;Choi, Sungwon;Jin, Donghyun;Her, Morang;Kim, Jajin;Hong, Jinkyu;Hong, Je-Woo;Lee, Keunmin;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.34 no.2_1
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    • pp.295-300
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    • 2018
  • Net radiation is the total amount of radiation energy used as a heat flux for the Earth's energy cycle, and net radiation from the surface is an important factor in areas such as hydrology, climate, meteorological studies and agriculture. It is very important to monitoring the net radiation through remote sensing to be able to understand the trend of heat island and urbanization phenomenon. However, net radiation estimation using only remote sensing data is generally causes difference in accuracy depending on cloud. Therefore, in this paper, we retrieved and monitored high resolution surface net radiation at 1 hour interval in Eunpyeong New Town where urbanization using Communication, Ocean and Meteorological Satellite (COMS), Landsat-8 satellite and Computational Fluid Dynamics (CFD) model data reflecting the difference in building height. We compared the observed and estimated net radiation at the flux tower. As a result, estimated net radiation was similar trend to the observed net radiation as a whole and it had the accuracy of RMSE $54.29Wm^{-2}$ and Bias $27.42Wm^{-2}$. In addition, the calculated net radiation showed well the meteorological conditions such as precipitation, and showed the characteristics of net radiation for the vegetation and artificial area in the spatial distribution.