• Title/Summary/Keyword: Data trend analysis

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Common Criteria of statistics using DEVS Modeling (DEVS 모델링을 이용한 보안제품 공동평가 통계)

  • Lee, Ki Sung;Kim, Tae Kyung;Seo, Hee Suk
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.2
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    • pp.71-80
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    • 2010
  • This thesis is purposed on developing security product co-evaluation statistics administrate program which is can administrate or analysis CC accreditation product using by DEVS modeling via portal site of member of CCRA. Via developing security product evaluation statistics administrate program, it can analysis the trend of all countries of the world in many ways, and noticed the ways of evaluation and accreditation of most countries via scheme analysis. Except this, it can analysis the situation of accreditation trend of any countries via data analysis of ICCC 2009. Also, For trend analysis to evaluation technique of CCRA member, it analyzed up to date technology and policy of the evaluation organization and the Certification Authority of most countries. And it peformed analysis the most trend of information security of evaluation authorization in CCRA member countries. In this program, It provide the function of trend statistics analysis which can statically analyzed the evaluation accreditation trends of most countries and automatical statistics by categorization ( by Product, Class and statistics in national) and report creation functions which can easily extraction and use the needed data. It has been updated the related informations until latest accredited product using by CC(Common Criteria) portal home page's data.

Suggestion of a Groundwater Quality Management Framework Using Threshold Values and Trend Analysis (문턱값과 추세분석을 이용한 지하수 수질관리체계 구축을 위한 연구)

  • An, Hyeonsil;Jee, Sung-Wook;Lee, Soo Jae;Hyun, Yunjung;Yoon, Heesung;Kim, Rak-Hyeon
    • Journal of Soil and Groundwater Environment
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    • v.20 no.7
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    • pp.112-120
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    • 2015
  • Statistical trend analysis using the data from the National Groundwater Quality Monitoring Network (NGQMN) of Korea was conducted to establish a new groundwater quality management framework. Sen’s test, a non-parametric statistical method for trend analysis, was used to determine the linear trend of the groundwater quality data. The analysis was conducted at different confidence levels (i.e., at 70, 80, 90, 95, and 99% confidence levels) for three of groundwater quality parameters, i.e., nitrate-nitrogen, chloride, and pH, which have sufficient time series of the NGQMN data between 2007 and 2013. The results showed that different trends can be determined for different depths even for the same monitoring site and the numbers of wells having significant trends vary with different confidence levels. The wells with increasing or decreasing trends were far less than the wells with no trend. Chloride had more wells with increasing trend than other parameters. On the other hand, nitrate-nitrogen had the most wells with increasing trend and concentration exceeding 75% of the threshold values (TVs). Based on the methodology used for this study, we suggest including groundwater TVs and trend analysis to evaluate groundwater quality and to establish an advanced groundwater quality management framework.

Item Trend Analysis Considering Social Network Data in Online Shopping Malls (온라인 쇼핑몰에서 소셜 네트워크 데이터를 고려한 상품 트렌드 분석)

  • Park, Soobin;Choi, Dojin;Yoo, Jaesoo;Bok, Kyoungsoo
    • The Journal of the Korea Contents Association
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    • v.20 no.2
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    • pp.96-104
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    • 2020
  • As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

The Study for Comparative Analysis of Software Failure Time Using EWMA Control Chart (지수 가중 이동 평균 관리도를 이용한 소프트웨어 고장 시간 비교분석에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.8 no.3
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    • pp.33-39
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    • 2008
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss exponentially weighted moving average chart, in measuring failure time. In control, exponentially weighted moving average chart's uses are efficiency case of analysis with knowing information, Using real software failure time, we are proposed to use exponentially weighted moving average chart and comparative analysis of software failure time.

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Comparative Analysis in Perception of Retro Fashion and New-tro Fashion Using Big Data (빅 데이터를 활용한 레트로 패션과 뉴트로 패션에 대한 인식 비교)

  • Kyung Ja Paek;Jeong-Mee Kim
    • Journal of the Korea Fashion and Costume Design Association
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    • v.25 no.1
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    • pp.83-96
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    • 2023
  • The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

Research on the New Consumer Market Trend by Social Big data Analysis -Focusing on the 'alone consumption' association- (소셜 빅데이터 분석에 의한 신 소비시장 트렌드 연구 - '나홀로 소비' 연관어를 중심으로 -)

  • Choo, Jin-Ki
    • Journal of Digital Convergence
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    • v.18 no.2
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    • pp.367-376
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    • 2020
  • According to recent statistics on new consumer market trends, 'alone consumption' is at the center. This study focuses on the social big data that attracts the public's opinions in that it is important for a certain social trend to comprehensively understand the various fields such as society, locality, culture, marketing, economics, and psychology that form the background for it. Therefore, we set up the linkage of 'solo consumption' and conducted research on new consumer market trends using Opinion Analisys. As a result of this trend analysis, representative keywords such as 'honbab', 'honsul' and 'honyoeng' were derived and analyzed the trend of new consumer market using this data. Alone consumption is an inevitable new consumption trend caused by demographic change after the global economic crisis. The importance as a trend reflecting this will be further strengthened. Trend analysis by social big data will help scientific and systematic business distribution strategies and planning to help make new and valuable decisions and decisions about new consumer markets.

Power Test of Trend Analysis using Simulation Experiment (모의실험을 이용한 경향성 분석기법의 검정력 평가)

  • Ryu, Yongjun;Shin, Hongjoon;Kim, Sooyoung;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.46 no.3
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    • pp.219-227
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    • 2013
  • Time series data including change, jump, trend and periodicity generally have nonstationarity. Especially, various methods have been proposed to identify the trend about hydrological time series data. However, among various methods, evaluation about capability of each trend test has not been done a lot. Even for the same data, each method may show the different result. In this study, the simulation was performed for identification about the changes in trend analysis according to the statistical characteristics and the capability in the trend analysis. For this purpose, power test for the trend analysis is conducted using Men-Kendall test, Hotelling-Pabst test, t test and Sen test according to the slope, sample size, standard deviation and significance level. As a result, t test has higher statistical power than the others, while Mann-Kendall, Hotelling-Pabst, and Sen tests were similar results.

An Analysis of the Characteristics in Design Rainfall According to the Data Periods (자료기간에 따른 확률 강우량 변화 특성 분석)

  • Oh, Tae-Suk;Kim, Min-Seok;Moon, Young-Il;Ahn, Jae-Hyun
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.4
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    • pp.115-127
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    • 2009
  • Recently, Natural disasters are increasing the damage according to the influence of the abnormal climate and climate change. This study analyzed change characteristic of Design Rainfall according to the different data periods. First, 14 observatories were selected at Meteorological Administration. Second, frequency analysis carried out 5 cases by different data periods. At the results of the frequency analysis, the design rainfall could confirm the increase in most areas of Korea. Also, the change and trend analysis carried out for characteristic analysis by design rainfall and observed rainfall. The change and trend analysis of observed annual maximum rainfall did not appeared, but the change and trend analysis of design rainfall significantly appeared using statistic methods. The result of the change and trend analysis, design rainfall increased in most areas of Korea. Although, it could be the necessity for reestimating defense ability of flood, existing river systems, and new establishment of structure about the change characteristic.

Analysis for Air Temperature Trend and Elasticity of Air-water Temperature according to Climate Changes in Nakdong River Basin (기후변화에 따른 낙동강 유역의 기온 경향성 및 수온과의 탄성도 분석)

  • Shon, Tae Seok;Lim, Yong Gyun;Baek, Meung Ki;Shin, Hyun Suk
    • Journal of Korean Society on Water Environment
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    • v.26 no.5
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    • pp.822-833
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    • 2010
  • Temperature increase due to climate changes causes change of water temperature in rivers which results in change of water quality etc. and the change of river ecosystem has a great impact on human life. Analyzing the impact of current climate changes on air and water temperature is an important thing in adapting to the climate changes. This study examined the effect of climate changes through analyzing air temperature trend for Nakdong river basin and analyzed the elasticity of air-water temperature to understand the effect of climate changes on water temperature. For analysis air temperature trend, collecting air temperature data from the National Weather Service on main points in Nakdong river basin, and resampling them at the units of year, season and month, used as data for air temperature trend analysis. Analyzing for elasticity of air-water temperature, the data were collected by the Water Environment Information system for water temperature, while air temperature data were collected at the National Weather Service point nearest in the water temperature point. And using the results of trend analysis and elasticity analysis, the effect of climate changes on water temperature was examined estimating future water temperature in 20 years and 50 years after. It is judged that analysis on mutual impact between factors such as heat budget, precipitation and evapotranspiration on river water temperature affected by climate changes and river water temperature is necessary.