• Title/Summary/Keyword: temporal trend

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Trend Analysis Service using a Temporal Web Ontology Language in News Domains (시간 웹 온톨로지 언어를 이용한 뉴스 동향 분석 서비스)

  • Kim, Sang-Kyun;Lee, Kyu-Chul
    • The Journal of Society for e-Business Studies
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    • v.12 no.3
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    • pp.133-150
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    • 2007
  • In this paper we investigate a trend analysis service using Semantic Web technology in a news domain. The trend analysis service can provide more intelligent answers rather than the answer given In current news search engines since it can analyze the passage of time and the relation among news. In order to provide the trend analysis service, the capability of temporal reasoning is required, but the Semantic Web language such as OWL does not support the reasoning capability. Therefore, we propose a language TL-OWL(Temporal Web Ontology Language) extending OWL with the temporal reasoning.

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Trend Analysis of Monthly Water Quality Data in Nakdong River Based on Seasonal Mann-Kendall Test (계절 Mann-Kendall 검정을 이용한 낙동강 유역의 월별 수질 장기 경향성 분석)

  • Yun, Jung-hye;Hwang, Syewoon;Kim, Dong-Hyeon;Kim, Sang-Min
    • Journal of The Korean Society of Agricultural Engineers
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    • v.57 no.6
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    • pp.153-162
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    • 2015
  • In this study, we analyzed the trends of water quality along the main stream in Nakdong river basin using the recent data and seasonal Mann-Kendall test. Monthly averaged values of DO, BOD, SS, COD, TN, and TP from 1989 to 2014 for 14 stations (including 2 TMDLs stations) were used in the study. The trend analysis results showed that BOD and TP at most stations has decreasing temporal trend except a few stations while COD and SS showed increasing trend at most stations. Temporal trends in TN at 8 stations were found to be statistically significant and 5 of them showed increasing temporal trend. Temporally averaged BOD, COD, TN and TP were generally increasing as going downstream and the worst water quality were found at Goryeong and Hyunpung station. Overall, water quality of Nakdong river especially in COD, SS, and TN getting worse in time at most stations and as going downstream.

Long-Term Trend Analyses of Water Qualities in Mangyung Watershed (비모수 통계기법을 이용한 만경강 유역의 장기간 수질 경향 분석)

  • Lee, Hye Won;Park, Seoksoon
    • Journal of Korean Society on Water Environment
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    • v.24 no.4
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    • pp.480-487
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    • 2008
  • Spatial and temporal analyses of water qualities were performed for 11 monitoring stations located in Mangyung watershed in order to analyze the trends of monthly water quality data of Biochemical Oxygen Demand (BOD), Total Nitrogen (TN) and Total Phosphorus (TP) measured from 1995 to 2004. The long-term trends were analyzed utilizing Seasonal Mann-Kendall test, LOWESS and three-dimensional graphs were constructed with respect to distance and time. The graph can visualize spatial and temporal trend of the long-term water quality in a large river system. The results of trend analysis indicated that water quality of BOD and TN showed the downward trend. This quantitive and quantitative analysis is the useful tool to analyze and display the long-term trend of water quality in a large river system.

Homogeneity of Climate Aridity Index Trends Using Mann-Kendall Trend Test (Mann-Kendall 추세분석을 이용한 건조지수 추세의 동질성)

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.47 no.7
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    • pp.643-656
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    • 2014
  • The homogeneity analysis of temporal (monthly, seasonal and annual) climate aridity index trend was accomplished for 43 climate measurement stations in South Korea. Furthermore, 43 stations were grouped into 9 different regions and the temporal and regional homogeneity of climate aridity index trends in each region and entire 9 regions were analyzed. For analysis, monthly, seasonal and annual climate aridity indexes of 43 study stations were estimated using precipitation and potential evapotranspiration calculated from FAO Penman-Monteith equation. The Mann-Kendall statistical test for significant trend was accomplished using the estimated climate aridity indexes and the results of trend test (Z scores) were used to analyze the temporal and regional homogeneity of climate aridity index trends. The study results showed the temporal and regional homogeneity of climate aridity index trends for individual and entire 9 regions. However, the homogeneity and the extent of aridity index trend showed different patterns temporally and regionally.

Analyzing the Variability of Spring Precipitation and Rainfall Effectiveness According to the Regional Characteristics (봄철 강수량 및 강수효율의 지역적 특성별 변화분석)

  • Kim, Gwang-Seob;Kim, Jong-Pil;Lee, Gi-Chun
    • Journal of The Korean Society of Agricultural Engineers
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    • v.53 no.3
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    • pp.1-11
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    • 2011
  • The temporal variability of spring (March, April, May) monthly precipitation, precipitation effectiveness, monthly maximum precipitation, monthly precipitation of different durations, and the precipitation days over several threshold (i.e. 0, 10, 20, 30, 40, and 50 mm/day) of 59 weather stations between 1973 and 2009 were analyzed. Also to analyze the regional characteristics of temporal variability, 59 weather stations were classified by elevations, latitudes, longitudes, river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization. Results demonstrated that trends of variables increase in April and decrease in May except precipitation day. Overall trend of precipitation amount and precipitation effectiveness is same but precipitation effectiveness of several sites decrease despite the trend of precipitation amount increases which may be caused by the air temperature increase. Therefore more effective water supply strategy is essential for Spring season. Regional characteristics of Spring precipitation variability can be summarized that increase trend during May become stronger with the increase of latitude and elevation which is similar to that of Summer season. The temporal variability of variables showed different behaviors according to river basins, inland or shore (east sea, south sea, west sea) area and the level of urbanization.

A Real-Time Integrated Hierarchical Temporal Memory Network for the Real-Time Continuous Multi-Interval Prediction of Data Streams

  • Kang, Hyun-Syug
    • Journal of Information Processing Systems
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    • v.11 no.1
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    • pp.39-56
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    • 2015
  • Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

Temporal Analysis of Trends in Dissolved Organic Matter in Han River Water

  • Lee, Hye-Won;Choi, Jung-Hyun
    • Environmental Engineering Research
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    • v.14 no.4
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    • pp.256-260
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    • 2009
  • This study used the extensive monitoring datasets of the Korea Ministry of Environment to examine trends in dissolved organic carbon (DOC) in Han River raw water. To estimate the organic contents of water, we adopted allied parameters such as biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as substitutes for DOC. Spatial and temporal analyses were performed on monthly BOD and COD data from 36 monitoring stations (14 for Main Han River, 7 for North Han River and 15 for South Han River) measured from 1989 to 2007. The results of trend analysis indicated that, on the whole, water quality according to BOD showed a downward trend at more than 67% of monitoring stations (9 for Main Han River, 6 for North Han River and 9 for South Han River). However, the water quality of COD showed an upward trend at more than 78% of monitoring stations (8 for Main Han River, 7 for North Han River and 13 for South Han River). The upward trend of COD contrary to the BOD trend indicates that there has been an increase in recalcitrant organic matter in Han River water that is not detectable by means of BOD.

Adaptive Reconstruction Of AVHRR NVI Sequential Imagery off Korean Peninsula

  • Lee, Sang-Hoon;Kim, Kyung-Sook
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.63-82
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    • 1994
  • Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. A reconstruction system was developed to increase the discrimination capability for imagery that has been modified by residual dffects resulting from imperfect sensing of the target and by atmospheric attenuation of the signal. Utilizing temporal information based on an adaptive timporal filter, it recovers missing measurements resulting from cloud cover and sensor noise and enhances the imagery. The temporal filter effectively tracks a systematic trend in remote sensing data by using a polynomial model. The reconstruction system were applied to the AVHRR data collected over Korean Peninsula. The results show that missing measurements are typically recovered successfully and the temporal trend in vegetation change is exposed clearly in the reconstructed series.

Comparison of Domestic and International Research Trend on Information Security (정보보안에 대한 국내외 연구 트렌드 비교)

  • Kim, Won-pil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.8
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    • pp.1811-1817
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    • 2015
  • This paper analyzes domestic research trend on information security, compares its results with international trends, and studies future directions we should have on national level. This research is a successor of the work for analysis of global research trend on information security. Therefore we select the same analysis method to compare domestic and international research trends exactly. To do this, we use domestic papers presented or published from 2001 to 2014, measure temporal relationship between technologies related to information security, analyze domestic research trends, and compare the results. Finally we will suggest our future direction through considering international future markets of technologies.

Outlook for Temporal Variation of Trend Embedded in Extreme Rainfall Time Series (극치강우자료의 경향성에 대한 시간적 변동 전망)

  • Seo, Lynn;Choi, Min-Ha;Kim, Tae-Woong
    • Journal of Wetlands Research
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    • v.12 no.2
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    • pp.13-23
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    • 2010
  • According to recent researches on climate change, the global warming is obvious to increase rainfall intensity. Damage caused by extreme hydrologic events due to global change is steadily getting bigger and bigger. Recently, frequently occurring heavy rainfalls surely affect the trend of rainfall observations. Probability precipitation estimation method used in designing and planning hydrological resources assumes that rainfall data is stationary. The stationary probability precipitation estimation method could be very weak to abnormal rainfalls occurred by climate change, because stationary probability precipitation estimation method cannot reflect increasing trend of rainfall intensity. This study analyzed temporal variation of trend in rainfall time series at 51 stations which are not significant for statistical trend tests. After modeling rainfall time series with maintaining observed statistical characteristics, this study also estimated whether rainfall data is significant for the statistical trend test in near future. It was found that 13 stations among sample stations will have trend within 10 years. The results indicate that non-stationary probability precipitation estimation method must be applied to sufficiently consider increase trend of rainfall.