• 제목/요약/키워드: temporal analysis

검색결과 2,414건 처리시간 0.03초

Telephone Speech Recognition with Data-Driven Selective Temporal Filtering based on Principal Component Analysis

  • Jung Sun Gyun;Son Jong Mok;Bae Keun Sung
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 학술대회지
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    • pp.764-767
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    • 2004
  • The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis.

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Temporal Structure on Discourse bevel within the Controlled Information Packaging Theory

  • Lee, Min-Haeng;Lee, Ik-Hwan
    • 한국언어정보학회지:언어와정보
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    • 제6권1호
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    • pp.91-103
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    • 2002
  • The temporal structure of events on the discourse level has long been of great interest in both theoretical and computational linguistics. In this paper, we offer a unified approach to the temporal relationships related to a hierarchical discourse structure. We apply the method of pronoun resolution to the interpretation of tense. It is based on an analysis within the framework of the controlled information packaging theory. A unique aspect of our account is that temporal interpretation across discourse segments in global discourse is subject to the same principles as the interpretation of global anaphora, and that there is thus no need to postulate independent principles to account for the discourse behaviour of tense. In this way, we can neatly explain the general view that tense parallels the anaphoric nature of pronouns.

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Temporal Classification Method for Forecasting Power Load Patterns From AMR Data

  • Lee, Heon-Gyu;Shin, Jin-Ho;Park, Hong-Kyu;Kim, Young-Il;Lee, Bong-Jae;Ryu, Keun-Ho
    • 대한원격탐사학회지
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    • 제23권5호
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    • pp.393-400
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    • 2007
  • We present in this paper a novel power load prediction method using temporal pattern mining from AMR(Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

거주인구의 시공간 변화 및 영향요인 분석: 전라북도 전주시 사례를 중심으로 (Exploring Spatio-temporal Patterns of Population and its Influential Factors in Jeonju)

  • 양지철;김주애;조국;이상완
    • 산업경영시스템학회지
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    • 제46권3호
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    • pp.251-258
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    • 2023
  • This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

Towards 4-dimensional Geographic Information Systems

  • Lee, Seong-Ho;Park, Jong-Hyun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.473-475
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    • 2003
  • To overcome the limitation that traditional GISs lose much information for the real world, 4-dimensional GIS has the additional reference systems including object's height and temporal dimension. This paper describes the 4-dimensional geometric object model and components. The prototype for 4-dimensional GIS consists of the data provider, manager, and renderer components. We show the virtual city that its database contains topographic maps, buildings, roads and temporal history data. This provides spatial, temporal operations and analysis functions.

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Application of Multi-periodic Harmonic Model for Classification of Multi-temporal Satellite Data: MODIS and GOCI Imagery

  • Jung, Myunghee;Lee, Sang-Hoon
    • 대한원격탐사학회지
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    • 제35권4호
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    • pp.573-587
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    • 2019
  • A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

A Systematic Review of Spatial and Spatio-temporal Analyses in Public Health Research in Korea

  • Byun, Han Geul;Lee, Naae;Hwang, Seung-sik
    • Journal of Preventive Medicine and Public Health
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    • 제54권5호
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    • pp.301-308
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    • 2021
  • Objectives: Despite its advantages, it is not yet common practice in Korea for researchers to investigate disease associations using spatio-temporal analyses. In this study, we aimed to review health-related epidemiological research using spatio-temporal analyses and to observe methodological trends. Methods: Health-related studies that applied spatial or spatio-temporal methods were identified using 2 international databases (PubMed and Embase) and 4 Korean academic databases (KoreaMed, NDSL, DBpia, and RISS). Two reviewers extracted data to review the included studies. A search for relevant keywords yielded 5919 studies. Results: Of the studies that were initially found, 150 were ultimately included based on the eligibility criteria. In terms of the research topic, 5 categories with 11 subcategories were identified: chronic diseases (n=31, 20.7%), infectious diseases (n=27, 18.0%), health-related topics (including service utilization, equity, and behavior) (n=47, 31.3%), mental health (n=15, 10.0%), and cancer (n=7, 4.7%). Compared to the period between 2000 and 2010, more studies published between 2011 and 2020 were found to use 2 or more spatial analysis techniques (35.6% of included studies), and the number of studies on mapping increased 6-fold. Conclusions: Further spatio-temporal analysis-related studies with point data are needed to provide insights and evidence to support policy decision-making for the prevention and control of infectious and chronic diseases using advances in spatial techniques.

Classifying Temporal Topics with Similar Patterns on Twitter

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • 제9권3호
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    • pp.295-300
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    • 2011
  • Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

The Neovascularization Effect of Bone Marrow Stromal Cells in Temporal Muscle after Encephalomyosynangiosis in Chronic Cerebral Ischemic Rats

  • Kim, Hyung-Syup;Lee, Hyung-Jin;Yeu, In-Seung;Yi, Jin-Seok;Yang, Ji-Ho;Lee, Il-Woo
    • Journal of Korean Neurosurgical Society
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    • 제44권4호
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    • pp.249-255
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    • 2008
  • Objective : In Moyamoya disease, the primary goal of treatment is to improve collateral circulation through angiogenesis. In the present study, we obtained and sub-cultured bone marrow stromal cells (BMSCs) from rats without a cell-mediated immune response. Then, we injected the labeled BMSCs directly into adjacent temporal muscle during encephalomyosynangiosis (EMS). Three weeks after BMSC transplantation, we examined the survival of the cells and the extent of neovascularization. Methods : We divided 20 rats into a BMSC transplantation group (n=12) and a control group (n=8). Seven days after the induction of chronic cerebral ischemia, an EMS operation was performed, and labeled BMSCs ($1{\times}106^6/100\;{\mu}L$) were injected in the temporal muscle for the transplantation group, while an equivalent amount of culture solution was injected for the control group. Three weeks after the transplantation, temporal muscle and brain tissue were collected for histological examination and western blot analysis. Results : The capillary/muscle ratio in the temporal muscle was increased in the BMSC transplantation group compared to the control group, showing a greater increase of angiogenesis (p<0.05). In the brain tissue, angiogenesis was not significantly different between the two groups. The injected BMSCs in the temporal muscle were vascular endothelial growth factor (VEGF)-positive by immunofluorescence staining. In both temporal muscle and brain tissue, the expression of VEGF by western blot analysis was not much different between the two groups. Conclusion : During EMS in a chronic cerebral ischemia rat model, the injection of BMSCs resulted in accelerated angiogenesis in the temporal muscle compared to the control group.

극치강수량의 시공간적 특성 분석 및 지역화에 관한 연구 (Analysis on Spatio-Temporal Pattern and Regionalization of Extreme Rainfall Data)

  • 이정주;권현한
    • 대한토목학회논문집
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    • 제31권1B호
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    • pp.13-20
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    • 2011
  • 강수량은 시공간적으로 변화하는 수문변량으로서 강수량의 시간적인 특성 또한 강수량의 특성을 정의하는데 매우 중요한 요소이다. 본 연구에서는 극치강수량의 지역빈도해석을 위한 범주화 과정에서 기존의 강수량과 관측소 위치좌표만을 이용한 범주화를 통해 해결할 수 없는 강우 발생의 계절적 변화와 집중에 대한 고려를 반영하기 위하여, 기존의 양적 범주화 과정에 시간적인 영향을 고려할 수 있는 요소로서 극치강수량 발생 시기 통계치를 활용할 수 있는 범주화 과정을 제시하였다. 본 연구에서는 극치강수량의 발생 시기에 대한 정량적인 분석이 가능한 순환통계기법을 이용하여 관측 지점별 시간 통계량을 산정하고, 이를 극치강수량과 결합하여 시 공간적인 특성자료를 생성한 후 수정 K-means 방법을 이용하여 군집화 해석을 수행하였으며, 전국을 다섯 개의 군집으로 분류하였다. 기존의 양적 범주화 결과와의 비교를 통해 발생 시간 통계치를 결합한 범주화 결과가 지형 및 권역을 반영하는 결과를 보임을 확인하였다.