• Title/Summary/Keyword: Data trend analysis

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Assessing the Impacts of Errors in Coarse Scale Data on the Performance of Spatial Downscaling: An Experiment with Synthetic Satellite Precipitation Products

  • Kim, Yeseul;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.33 no.4
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    • pp.445-454
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    • 2017
  • The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

A Design of Air Compressor Remote Control System Using USN Technology (USN 기술을 이용한 공기압축기 원격관리 시스템 설계)

  • Hwang, Moon-Young
    • Korean Journal of Artificial Intelligence
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    • v.6 no.1
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    • pp.1-10
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    • 2018
  • Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

Trend Analysis of Earthquake Researches in the World (전세계의 지진 연구의 추세 분석)

  • Yun, Sul-Min;Hamm, Se-Yeong;Jeon, Hang-Tak;Cheong, Jae-Yeol
    • Journal of the Korean earth science society
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    • v.42 no.1
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    • pp.76-87
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    • 2021
  • In this study, temporal trend of researches in earthquake with groundwater level, water quality, radon, remote sensing, electrical resistivity, gravity, and geomagnetism was searched from 2001 to 2020, using the journals indexed in Web of Science, and the number of articles published in international journals was counted in relation to the occurrences of earthquakes (≥Mw 5.0, ≥Mw 6.0, ≥Mw 7.0, ≥Mw 8.0, and ≥Mw 9.0). The number of articles shows an increasing trend over the studied period. This is explained by that studies on earthquake precursor and seismic monitoring becomes active in various fields with integrated data analysis through the development of remote sensing technology, progress of measurement equipment, and big data. According to Mann-Kendall and Sen's tests, gravity-related articles exhibit an increasing trend of 1.30 articles/yr, radon-related articles (0.60 articles/yr), groundwater-related articles (0.70 articles/yr), electrical resistivity-related articles (0.25 articles/yr), and remote-sensing-related articles (0.67 articles/yr). By cross-correlation analysis of the number of articles in each field with removing trend effect and the number of earthquakes of ≥Mw 5.0, ≥Mw 6.0, ≥Mw 7.0, ≥Mw 8.0, and ≥Mw 9.0, radon and remote sensing fields exhibit a high cross-correlation with a delay time of one year. In addition, large-scale earthquakes such as the 2004 and 2005 Sumatra earthquake, the 2008 Sichuan earthquake, the 2010 Haiti earthquake, and the 2010 Chile earthquake are estimated to be related with the increase in the number of articles in the corresponding periods.

Detrending Crop Yield Data for Improving MODIS NDVI and Meteorological Data Based Rice Yield Estimation Model (벼 수량 자료의 추세분석을 통한 MODIS NDVI 및 기상자료 기반의 벼 수량 추정 모형 개선)

  • Na, Sang-il;Hong, Suk-young;Ahn, Ho-yong;Park, Chan-won;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.199-209
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    • 2021
  • By removing the increasing trend that long-term time series average of rice yield due to technological advancement of rice variety and cultivation management, we tried to improve the rice yield estimation model which developed earlier using MODIS NDVI and meteorological data. A multiple linear regression analysis was carried out by using the NDVI derived from MYD13Q1 and weather data from 2002 to 2019. The model was improved by analyzing the increasing trend of rime-series rice yield and removing it. After detrending, the accuracy of the model was evaluated through the correlation analysis between the estimated rice yield and the yield statistics using the improved model. It was found that the rice yield predicted by the improved model from which the trend was removed showed good agreement with the annual change of yield statistics. Compared with the model before the trend removal, the correlation coefficient and the coefficient of determination were also higher. It was indicated that the trend removal method effectively corrects the rice yield estimation model.

Status and Trend of Foreign Underground Data Centers (해외 지하 데이터센터의 현황과 동향 분석)

  • Lee, Chulho;Choi, Soon-Wook;Kang, Tae-Ho;Chang, Soo-Ho
    • Tunnel and Underground Space
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    • v.29 no.1
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    • pp.52-63
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    • 2019
  • It is highly in demand to establish a bunker-type underground data center to ensure the safety of national critical data, such as financial information and medical information, and prevent those outflow of national important data. In particular, the security of a data center which is a key national structure has become a social issue due to EMP weapon and earthquakes, but data centers in the nation have not been able to deal with it properly. Therefore, it is necessary to develop an underground data center that is safe from human-induced and natural disasters while reducing power costs by utilizing the benefits of underground spaces such as constant temperature and isolation. In this analysis, the status and trends of data centers around the world were analyzed and based on those trend analyses, the research strategy for underground data center were discussed.

Odoo Data Mining Module Using Market Basket Analysis

  • Yulia, Yulia;Budhi, Gregorius Satia;Hendratha, Stefani Natalia
    • Journal of information and communication convergence engineering
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    • v.16 no.1
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    • pp.52-59
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    • 2018
  • Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.

A study on changes in domestic tourism trends using social big data analysis - Comparison before and after COVID19 -

  • Yoo, Kyoung-mi;Choi, Youn-hee
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.2
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    • pp.98-108
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    • 2022
  • In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.

Scenarios for Manufacturing Process Data Analysis using Data Mining (데이터 마이닝을 이용한 생산공정 데이터 분석 시나리오)

  • Lee, Hyoung-wook;Bae, Sung-min
    • Journal of Institute of Convergence Technology
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    • v.3 no.1
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    • pp.41-44
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    • 2013
  • Process and manufacturing data are numerously accumulated to the enterprise database in industries but little of those data are utilized. Data mining can support a decision to manager in process from the data. However, it is not easy to field managers because a proper adoption of various schemes is very difficult. In this paper, six scenarios are conducted using data mining schemes for the various situations of field claims such as yield problem, trend analysis and prediction of yield according to changes of operating conditions, etc. Scenarios, like templates, of various analysis situations are helpful to users.

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Technology Convergence & Trend Analysis of Biohealth Industry in 5 Countries : Using patent co-classification analysis and text mining (5개국 바이오헬스 산업의 기술융합과 트렌드 분석 : 특허 동시분류분석과 텍스트마이닝을 활용하여)

  • Park, Soo-Hyun;Yun, Young-Mi;Kim, Ho-Yong;Kim, Jae-Soo
    • Journal of the Korea Convergence Society
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    • v.12 no.4
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    • pp.9-21
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    • 2021
  • The study aims to identify convergence and trends in technology-based patent data for the biohealth sector in IP5 countries (KR, EP, JP, US, CN) and present the direction of development in that industry. We used patent co-classification analysis-based network analysis and TF-IDF-based text mining as the principal methodology to understand the current state of technology convergence. As a result, the technology convergence cluster in the biohealth industry was derived in three forms: (A) Medical device for treatment, (B) Medical data processing, and (C) Medical device for biometrics. Besides, as a result of trend analysis based on technology convergence results, it is analyzed that Korea is likely to dominate the market with patents with high commercial value in the future as it is derived as a market leader in (B) medical data processing. In particular, the field is expected to require technology convergence activation policies and R&D support strategies for the technology as the possibility of medical data utilization by domestic bio-health companies expands, along with the policy conversion of the "Data 3 Act" passed by the National Assembly in January 2019.

Research Trend Analysis of Research Published in the Journal of Dental Hygiene Science from 2011 to 2020

  • Lee, Sun-Mi;Seong, Mi-Gyung;Moon, Hee-Jung;Son, Jung-Hui
    • Journal of dental hygiene science
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    • v.22 no.3
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    • pp.131-138
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    • 2022
  • Background: The purpose of this study was to analyze research trends in articles published in the Journal of Dental Hygiene Science over the past decade. Methods: From 2011 to 2020, 653 studies were reviewed using a keyword analysis. Contents such as academic classification, research type, research method, research topic, data collection method, data analysis method, and financial support were analyzed. Results: Analysis by school type showed 34.2% of clinical dental hygiene studies, 23.3% of educational dental hygiene studies, 22.8% of basic dental hygiene studies, 10.0% of other field studies, and 9.8% of social dental hygiene studies. By type of study, quantitative studies were the most common at 69.5%. Regarding data collection methods, 45.8% of the studies that used surveys were the most common. The subjects of the study were 20.1% experimental studies, 15.6% general adults, and 15.0% dental hygienists. Regarding the data analysis method, 49.3% of the studies that conducted frequency analysis were the most common. The total number of keywords was 2,390, with 107 (4.48%) being 'dental hygienists.' Next, oral health was the most common with 67 (2.80%) articles, followed by 31 for the elderly (1.30%), 25 for dental hygiene students (1.05%), and 24 for stress (1.00%). Conclusion: For academic development of dental hygiene, it is necessary to explore the diversity of academic topics based on the results of this study. It is necessary to find a way to spread the research results so that the published research can be used for the academic development of dental hygiene.