Relevant bibliographies by topics / Distributed data series index

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Distributed data series index'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Distributed data series index"

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Chatzakis, Manos, Panagiota Fatourou, Eleftherios Kosmas, Themis Palpanas, and Botao Peng. "Odyssey: A Journey in the Land of Distributed Data Series Similarity Search." Proceedings of the VLDB Endowment 16, no. 5 (2023): 1140–53. http://dx.doi.org/10.14778/3579075.3579087.

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This paper presents Odyssey, a novel distributed data-series processing framework that efficiently addresses the critical challenges of exhibiting good speedup and ensuring high scalability in data series processing by taking advantage of the full computational capacity of modern distributed systems comprised of multi-core servers. Odyssey addresses a number of challenges in designing efficient and highly-scalable distributed data series index, including efficient scheduling, and load-balancing without paying the prohibitive cost of moving data around. It also supports a flexible partial repli
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Liu, Feng-Chi, Cathy W. S. Chen, and Cheng-Ying Ho. "Bayesian Forecasting of Bounded Poisson Distributed Time Series." Entropy 26, no. 1 (2023): 16. http://dx.doi.org/10.3390/e26010016.

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This research models and forecasts bounded ordinal time series data that can appear in various contexts, such as air quality index (AQI) levels, economic situations, and credit ratings. This class of time series data is characterized by being bounded and exhibiting a concentration of large probabilities on a few categories, such as states 0 and 1. We propose using Bayesian methods for modeling and forecasting in zero-one-inflated bounded Poisson autoregressive (ZOBPAR) models, which are specifically designed to capture the dynamic changes in such ordinal time series data. We innovatively exten
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Triebel, Dagmar, Camila Uribe-Holguin, Stefan Seifert, Markus Weiss, and Peter Scholz. "Connecting IndExs Editors and exsiccata IDs with Wikidata for Disambiguation of People Names and Work in Botanical and Mycological Collections." Biodiversity Information Science and Standards 6 (August 23, 2022): e93585. https://doi.org/10.3897/biss.6.93585.

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"IndExs—Index of Exsiccatae" is an online database with bibliographic information on exsiccatae and exsiccata-like series launched in 2001 (Triebel and Scholz 2022). This type of series is a specific system in botany and mycology to create, publish and distribute well identified and documented reference material. In most cases the distributed specimens are numbered and each number consists of uniform material (herbarium duplicates) from a single collection event. Exsiccatal series are regularily published with small booklets containing the printed labels/ schedae of each numbered entity. The t
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Zhao, Qing, Chengkui Zhang, Hao Li, Tingting Zhao, Chenzhou Cui, and Dongwei Fan. "TT-HEALpix: A New Data Indexing Strategy for Efficient Cross-match of Large-scale Astronomical Catalogs." Publications of the Astronomical Society of the Pacific 136, no. 3 (2024): 034501. http://dx.doi.org/10.1088/1538-3873/ad2721.

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Abstract Cross-matching is an indispensable operation in the data preparation, analysis, and research processes of multi-band astronomy and time-domain astronomy. Multi-catalog time-series data reconstruction is an important part of time-domain astronomy. In the large-scale distributed reconstruction process, boundary problems have always affected the accuracy of time-series data. To optimize these boundary problems and improve data precision, this paper proposes a new hybrid astronomical data indexing method called Translated Transformation based HEALPix Dual Index (TT-HEALPix). Under the rea
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Allen, David E., and Michael McAleer. "A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index." Energies 13, no. 15 (2020): 4011. http://dx.doi.org/10.3390/en13154011.

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The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag nonlinear autoregressive distributed lag (NARDL) framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from Federal Reserve Bank of St Louis (FRE
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Lisdawami, Indi Masita. "PENGARUH KURS, INFLASI DAN INDEKS PRODUKSI INDUSTRI TERHADAP JAKARTA ISLAMIC INDEX PERIODE 2010-2019." Ulumuna: Jurnal Studi Keislaman 7, no. 1 (2021): 90–114. http://dx.doi.org/10.36420/ju.v7i1.4925.

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This study aims to analyze the effect of macroeconomic factors on the Jakarta Islamic Index (JII). The variables in this study are exchange rate, inflation, and Industrial Production Index (IPI). This study uses the Autoregressive Distributed (ARDL) model. The data used in this study is secondary data in the form of monthly time series (time series) from January 2010 to December 2019 taken from publications from the Central Statistics Agency, Bank Indonesia, related journals and references. The results of this study are the exchange rate and inflation variables have a negative and significant
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Wang, Nianyong, Muhammad Haroon Shah, Kishwar Ali, Shah Abbas, and Sami Ullah. "Financial Structure, Misery Index, and Economic Growth: Time Series Empirics from Pakistan." Journal of Risk and Financial Management 12, no. 2 (2019): 100. http://dx.doi.org/10.3390/jrfm12020100.

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This study empirically analyzes the impact of the financial structure and misery index on economic growth in Pakistan. We adopted Autoregressive-Distributed Lag (ARDL) for a co-integration approach to the data analysis and used time series data from 1989 to 2017. We used GDP as the dependent variable; the Financial Development index (FDI) and misery index as the explanatory variables; and remittances, real interest, and trade openness as the control variables. The empirical results indicate the existence of a long-term relationship among the included variables in the model and the FD index, mi
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Allen, David, and Michael McAleer. "A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes." Risks 9, no. 11 (2021): 195. http://dx.doi.org/10.3390/risks9110195.

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The paper features an examination of the link between the behaviour of the FTSE 100 and S&P500 Indexes in both an autoregressive distributed lag ARDL, plus a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a daily FTSE adjusted price series, commencing in April 2009 and terminating in March
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NASREEN, SAMIA, and SOFIA ANWAR. "FINANCIAL STABILITY AND THE ROLE OF ECONOMIC AND FINANCIAL INTEGRATION IN SOUTH ASIA: EVIDENCE FROM TIME-SERIES DATA." Singapore Economic Review 65, no. 02 (2017): 303–33. http://dx.doi.org/10.1142/s0217590817500011.

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Using the aggregate financial stability index (AFSI) which measures the gradual progression and changes in financial market stability, this paper empirically evaluates the impact of financial and economic integration on financial stability in South Asian countries using time-series data for the period 1980–2012. Auto-regressive distributed lag (ARDL) Bounds testing approach to cointegration is applied to ensure long-run relationship between variables. Bound F-test results confirm the long-run relationship between selected variables. The estimated results show that economic and financial integr
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Sagajoka, Estherlina. "Analisis Wilayah Kecamatan Potensial Melalui Pendekatan Tipologi Klassen di Kabupaten Ende." Analisis 19, no. 1 (2020): 39–49. http://dx.doi.org/10.37478/analisis.v19i1.322.

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This study aims to determine the comparison of the results of the inequality analysis of economic development between districts / cities in the province of East Nusa Tenggara for the period of 2013-2018. The method used in this research is quantitative descriptive analysis using the Williamson index, and Theil Entropy Index, using time data per capita PDRB series and population data for each district / city in 2013-2018.
 The Williamson Index analysis results show that the economic development sector inequality in 21 districts in NTT province is very evenly distributed (low inequality) ex
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Dissertations / Theses on the topic "Distributed data series index"

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Milton, Robert. "Time-series in distributed real-time databases." Thesis, University of Skövde, Department of Computer Science, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-827.

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<p>In a distributed real-time environment where it is imperative to make correct decisions it is important to have all facts available to make the most accurate decision in a certain situation. An example of such an environment is an Unmanned Aerial Vehicle (UAV) system where several UAVs cooperate to carry out a certain task and the data recorded is analyzed after the completion of the mission. This project aims to define and implement a time series architecture for use together with a distributed real-time database for the ability to store temporal data. The result from this project is a tim
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Charapko, Aleksey. "Time Series Similarity Search in Distributed Key-Value Data Stores Using R-Trees." UNF Digital Commons, 2015. http://digitalcommons.unf.edu/etd/565.

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Time series data are sequences of data points collected at certain time intervals. The advance in mobile and sensor technologies has led to rapid growth in the available amount of time series data. The ability to search large time series data sets can be extremely useful in many applications. In healthcare, a system monitoring vital signals can perform a search against the past data and identify possible health threatening conditions. In engineering, a system can analyze performances of complicated equipment and identify possible failure situations or needs of maintenance based on historical d
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Hwang, Suk Hyun. "Optimization of the Photovoltaic Time-series Analysis Process Through Hybrid Distributed Computing." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1587128073434884.

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Dias, Filipa de Carvalho. "Cluster analysis of financial time series data : evidence for portuguese and spanish stock markets." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14923.

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Mestrado em Mathematical Finance<br>Esta dissertação utilizando a distância de Caiado & Crato (2010) baseada nas autocorrelações, pretende efectuar o agrupamento de séries financeiras temporais. A métrica tenta avaliar o nível de interdependência, tendo por base a previsibilidade dos retornos. A análise de $clusters$ é feita tendo em conta a estrutura hierárquica (dendrograma) e as coordenadas principais calculadas (mapa multidimensional) das séries financeiras. Estas técnicas foram utilizadas para investigar as semelhanças e diferenças entre as empresas dos dois índices ibéricos de mercado de
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Wang, Chiying. "Contributions to Collective Dynamical Clustering-Modeling of Discrete Time Series." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-dissertations/198.

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The analysis of sequential data is important in business, science, and engineering, for tasks such as signal processing, user behavior mining, and commercial transactions analysis. In this dissertation, we build upon the Collective Dynamical Modeling and Clustering (CDMC) framework for discrete time series modeling, by making contributions to clustering initialization, dynamical modeling, and scaling. We first propose a modified Dynamic Time Warping (DTW) approach for clustering initialization within CDMC. The proposed approach provides DTW metrics that penalize deviations of the warping path
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Larsson, Klara, and Freja Ling. "Time Series forecasting of the SP Global Clean Energy Index using a Multivariate LSTM." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301904.

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Clean energy and machine learning are subjects that play significant roles in shaping our future. The current climate crisis has forced the world to take action towards more sustainable solutions. Arrangements such as the UN’s Sustainable Development Goals and the Paris Agreement are causing an increased interest in renewable energy solutions. Further, the EU Taxonomy Regulation, applied in 2020, aims to scale up sustainable investments and to direct cash flows toward sustainable projects and activities. These measures create interest in investing in renewable energy alternatives and predictin
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Lowry, Matthew C. "A new approach to the train algorithm for distributed garbage collection." Title page, table of contents and abstract only, 2004. http://hdl.handle.net/2440/37710.

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This thesis describes a new approach to achieving high quality distributed garbage collection using the Train Algorithm. This algorithm has been investigated for its ability to provide high quality collection in a variety of contexts, including persistent object systems and distributed object systems. Prior literature on the distributed Train Algorithm suggests that safe, complete, asynchronous, and scalable collection can be attained, however an approach that achieves this combination of behaviour has yet to emerge. The mechanisms and policies described in this thesis are unique in their abil
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Drougas, Ioannis. "Rate allocation in distributed stream processing systems." Diss., [Riverside, Calif.] : University of California, Riverside, 2008. http://proquest.umi.com/pqdweb?index=0&did=1663077971&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268240766&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2008.<br>Includes abstract. Title from first page of PDF file (viewed March 10, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 93-98). Also issued in print.
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Beasley, Ben. "Assessing Blackmouth Shiner (Notropis melanostomus) habitat in the Pascagoula River using a habitat inundation index based on time series Landsat data." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/honors_theses/73.

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The Blackmouth Shiner (Notropis melanostomus) is a small North American cyprinid that is listed as a Species of Concern due its relatively small range, occurring at only a few sites in Mississippi, Alabama, and Florida. Due to limited data and the small number of actual samples of N. melanostomus, the true characteristics of viable habitat and distribution remain unknown. The objective of my research was to utilize remote sensing data to gain a better understanding of the habitat characteristics where the N. melanostomus has been collected and use this information to identify other areas were
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Toups, Matthew A. "A study of three paradigms for storing geospatial data: distributed-cloud model, relational database, and indexed flat file." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/td/2196.

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Geographic Information Systems (GIS) and related applications of geospatial data were once a small software niche; today nearly all Internet and mobile users utilize some sort of mapping or location-aware software. This widespread use reaches beyond mere consumption of geodata; projects like OpenStreetMap (OSM) represent a new source of geodata production, sometimes dubbed “Volunteered Geographic Information.” The volume of geodata produced and the user demand for geodata will surely continue to grow, so the storage and query techniques for geospatial data must evolve accordingly. This thesis
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Books on the topic "Distributed data series index"

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Leslie, Young Colin, ed. Solubility data series cumulative index: Volumes 1-18. Pergamon, 1985.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Deployment guide series. International Technical Support Organization, 2008.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Certification guide series. International Technical Support Organization, 2008.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Certification guide series. International Technical Support Organization, 2008.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Certification guide series. International Technical Support Organization, 2008.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Certification guide series. International Technical Support Organization, 2008.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Certification study guide series: IBM Tivoli monitoring V6.2. International Technical Support Organization, 2008.

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International Business Machines Corporation. International Technical Support Organization, ed. Certification guide series: IBM Tivoli provisioning manager express for software distribution V4.1. IBM International Technical Support Organization, 2006.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Deployment guide series. IBM Corp., International Technical Support Organization, 2006.

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Vasfi, Gucer, and International Business Machines Corporation. International Technical Support Organization., eds. Deployment guide series. IBM International Technical Support Organization, 2006.

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Book chapters on the topic "Distributed data series index"

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Lee, Hyunjo, Hyeonguk Ma, Youngho Song, and Jae-Woo Chang. "Secure Query Processing over Encrypted Data Using a Distributed Index Structure for Outsourcing Sensitive Data." In Economics of Grids, Clouds, Systems, and Services. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13342-9_16.

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Horváth, Lajos, and Piotr Kokoszka. "Spatially distributed functional data." In Springer Series in Statistics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3655-3_17.

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Dong, Hai tao, Qing Sun, Lu lu Shan, Xi Meng, Ru-nan Li, and Yi-he Fang. "Risk Analysis of Blueberry Gale Disaster in Liaodong Green Economic Zone Based on Machine Learning." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8401-1_7.

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AbstractBased on the long time series gale data of 9 national meteorological stations in Liaoning province and the data of blueberry growth period, the optimal machine learning model is chosen to extend the time series of maximum wind speed, using the maximum wind speed and disaster information data of the corresponding stations, considering the frequency and duration comprehensively, the meteorological index thresholds of different grades of high wind disaster risk during the ripening period of blueberry were determined, the risk grades of mild, moderate and severe gale disasters were established, and the spatial and temporal distribution characteristics of blueberry gale disaster risk were analyzed by the frequency of disasters and the ratio of stations. The results showed that the stochastic forest model had a high simulation precision and could extend the maximum wind speed time series, and the maximum wind disaster risk threshold was ≥ 13.9 ms−1 in the mature period of blueberry, the results were verified to be in accordance with the actual situation. During the whole mature period of blueberry in 30 years, the impact of Gale Disaster Risk tended to be mitigated, and the frequency of occurrence showed a non-significant decreasing trend, the Xiuyan area showed the most significant decrease, while the Kuandian Manchu Autonomous County area showed a significant increase trend. The probability of occurrence of gale hazard over the whole mature period of 30 years is 83.3%, and the probability of occurrence of gale hazard over two years (≥ 50%), among which the Fushun region has the highest risk degree, the middle risk probability is 17.8%, the Qingyuan region has the highest risk degree, and the severe risk degree is 5.2%, mainly in Fushun and Benxi. In general, the northwest part of the Green Economic Zone is a high risk area for gale disasters, which are widespread, frequent and severe, mainly distributed in Fushun, Benxi, Qingyuan Manchu Autonomous County and Xifeng County.
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Schill, Kerstin. "Distributed Reasoning With Uncertain Data." In International Series in Intelligent Technologies. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5473-8_23.

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Zomaya, Albert Y. "Wiley Series on Parallel and Distributed Computing." In The DATA Bonanza. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118540343.scard.

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Krüger, N., and M. Völschow. "Solar System Object Detection in Time Series Data Using Synthetically Trained Neural Networks." In Intelligent Distributed Computing XVI. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60023-4_10.

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Sarker, Biplab Kumer, Takaki Mori, Toshiya Hirata, and Kuniai Uehara. "Parallel Algorithms for Mining Association Rules in Time Series Data." In Parallel and Distributed Processing and Applications. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-37619-4_28.

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Palpanas, Themis. "Evolution of a Data Series Index." In Communications in Computer and Information Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44900-1_5.

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Hoang, Dinh-Quang, Dang-Khoa Tran, Viet-Thang Le, The-Manh Nguyen, and Trong-Hop Do. "Distributed Deep Learning for Big Data Time Series Analysis." In Intelligence of Things: Technologies and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15063-0_31.

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Mendoza-Granada, Fabricio, and Marcos Villagra. "A Distributed Algorithm for Spectral Sparsification of Graphs with Applications to Data Clustering." In AIRO Springer Series. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63072-0_31.

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Conference papers on the topic "Distributed data series index"

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Cai, Tao, Tianle Lei, Dejiao Niu, Jianfei Dai, Zeyu Huang, and Qiangqiang Ni. "A Hierarchical Heterogeneous IoT Time Series Data Index for NVM." In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2024. https://doi.org/10.1109/smc54092.2024.10831234.

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Li, Bo, Zhan Shi, Xiaozhi Deng, Zhentian Wu, and Zhihua Yang. "Distributed Photovoltaic Data Compression Method Based on Time Series Prediction Model." In 2024 4th International Conference on New Energy and Power Engineering (ICNEPE). IEEE, 2024. https://doi.org/10.1109/icnepe64067.2024.10860549.

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Fuchs, Marco. "Structural Breakpoint Detection in Noisy Time Series Using an Augmented Matrix Profile Index." In 2024 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2024. https://doi.org/10.1109/icdmw65004.2024.00119.

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Zhang, Wei, Houjun Tang, and Suren Byna. "IDIOMS: Index-powered Distributed Object-centric Metadata Search for Scientific Data Management." In 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid). IEEE, 2024. http://dx.doi.org/10.1109/ccgrid59990.2024.00072.

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Adelfio, Andrea, Riccardo Crupi, Sara Cutini, et al. "Anomaly Detection with Machine Learning on Time Series: Unveiling Lost Transients Data." In 2025 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP). IEEE, 2025. https://doi.org/10.1109/pdp66500.2025.00062.

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Fatourou, Panagiota, Eleftherios Kosmas, Themis Palpanas, and George Paterakis. "FreSh: A Lock-Free Data Series Index." In 2023 42nd International Symposium on Reliable Distributed Systems (SRDS). IEEE, 2023. http://dx.doi.org/10.1109/srds60354.2023.00029.

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Khan, Ashraf, and Dariusz Ceglarek. "Distributed Sensor Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-1042.

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Abstract Sensing for the system-wide diagnosis of dimensional faults in multi-fixture sheet metal assembly presents significant issues of complexity due to the number of levels of assembly and the number of possible faults at each level. The traditional allocation of sensing at a single measurement station is no longer sufficient to guarantee adequate fault diagnostic information for the increased parts and levels of a complex assembly system architecture. This creates a need for an efficient distribution of limited sensing resources to multiple measurement locations in assembly. The proposed
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Supekar, N., S. Peddada, and J. Reid. "Analysis of Clustering Machine Learning Algorithms and Generative Artificial Intelligence Tool for Visualization and Interpretation of Seismic Data." In ADIPEC. SPE, 2024. http://dx.doi.org/10.2118/221999-ms.

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Abstract Seismic attribute analysis is often confounded by the complexity of the subsurface. Clustering machine learning algorithms reduce complexity and bring the most salient features of the seismic datasets to the fore. By conducting a comparative study of clustering algorithms applied to 2D seismic data, we can determine a set of optimal methods for visualizing particular seismic attributes. This paper presents an analysis of clustering algorithms, and a generative artificial intelligence-based large language model (LLM) customized for interrogating seismic data. Based on data partitioning
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Shahcheraghi, Maryam, Trevor Cappon, Samet Oymak, et al. "Matrix Profile Index Approximation for Streaming Time Series." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671484.

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Chen, Huang, Yuanchao Li, David Tan, and Joseph Katz. "Visualizations of Flow Structures in the Rotor Passage of an Axial Compressor at the Onset of Stall." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-57054.

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Flow visualizations and stereoscopic PIV (SPIV) measurements are carried out to study the flow phenomena developing in the rotor passage of an axial compressor at the onset of stall. Experiments have been performed in the JHU optically index-matched facility, using acrylic blades and liquid that have the same optical refractive index. The blade geometries are based on the first one and a half stages of the Low Speed Axial Compressor (LSAC) facility at NASA Glenn. The SPIV measurements provide detailed snapshots and ensemble statistics on the flow in a series of meridional planes. Data recorded
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Reports on the topic "Distributed data series index"

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Marzouk, Youssef, P. Fast, M. Kraus, and J. P. Ray. A Bayesian method for characterizing distributed micro-releases: II. inference under model uncertainty with short time-series data. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/902883.

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Martínez-Rivera, Wilmer, Eliana R. González-Molano, and Edgar Caicedo-García. Forecasting Inflation from Disaggregated Data: The Colombian case. Banco de la República, 2023. http://dx.doi.org/10.32468/be.1251.

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Based on monthly disaggregated Consumer Price Index (CPI) item series and macroeconomic series, we explore the advantages of forecast inflation from a disaggregated to an aggregated level by aggregating the forecasts. We compare the performance of this approach with the forecast obtained modeling aggregated inflation directly. For the aggregate level, we implement some of the techniques and models, helpful to work with many predictors, such as dimension reduction, shrinkage methods, and machine learning models. Also, we implement traditional time-series models. For the disaggregated data, we u
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Kennedy, Mary Lee, and Cynthia Hudson Vitale. Identifying Collaboration Priorities for US-Based Research Data Organizations: Questionnaire Results. Association of Research Libraries, 2022. http://dx.doi.org/10.29242/report.researchdataorgscollab2022.

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The Association of Research Libraries (ARL) has released the results of a questionnaire, developed with the US National Committee for CODATA, intended to identify potential areas of synergy and interests among US-based research data organizations. This report is a first step in building community among US-based research data organizations. The report will inform the US National Committee for CODATA’s plans for a series of virtual convenings to discuss shared interests among cross-sector research data organizations, culminating in an in-person US Research Data Summit. The aim is to create a sha
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Lasko, Kristofer, Francis O’Neill, and Elena Sava. Automated mapping of land cover type within international heterogenous landscapes using Sentinel-2 imagery with ancillary geospatial data. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49367.

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A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover m
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Bekri, Mahmoud. Inflation Dependence Structure in a post-COVID-19 World. Islamic Development Bank Institute, 2022. http://dx.doi.org/10.55780/re24025.

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Inflation may be defined as the decline of purchasing power of a determined currency over time. It also determines the erosion of living standards. Inflation may be measured by the Consumer Price Index (CPI), a quantitative estimate of the inflation that may be captured in the rise of an average price level of a basket of determined goods and services, which are typically purchased by specific groups of households in an economy over a specific period. We use the inflation data provided by OECD, measured in terms of the monthly growth rate, where the CPI index is estimated as a series of summar
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Slattery, Kevin T. Unsettled Aspects of the Digital Thread in Additive Manufacturing. SAE International, 2021. http://dx.doi.org/10.4271/epr2021026.

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In the past years, additive manufacturing (AM), also known as “3D printing,” has transitioned from rapid prototyping to making parts with potentially long service lives. Now AM provides the ability to have an almost fully digital chain from part design through manufacture and service. Web searches will reveal many statements that AM can help an organization in its pursuit of a “digital thread.” Equally, it is often stated that a digital thread may bring great benefits in improving designs, processes, materials, operations, and the ability to predict failure in a way that maximizes safety and m
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Hertel, Thomas, David Hummels, Maros Ivanic, and Roman Keeney. How Confident Can We Be in CGE-Based Assessments of Free Trade Agreements? GTAP Working Paper, 2003. http://dx.doi.org/10.21642/gtap.wp26.

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With the proliferation of Free Trade Agreements (FTAs) over the past decade, demand for quantitative analysis of their likely impacts has surged. The main quantitative tool for performing such analysis is Computable General Equilibrium (CGE) modeling. Yet these models have been widely criticized for performing poorly (Kehoe, 2002) and having weak econometric foundations (McKitrick, 1998; Jorgenson, 1984). FTA results have been shown to be particularly sensitive to the trade elasticities, with small trade elasticities generating large terms of trade effects and relatively modest efficiency gain
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Sarker, Abdur Razzaque, and Kashfi Rayan. Trends And Inequalities Of Childhood Underweight In Bangladesh: A Decomposition Approach. Bangladesh Institute of Development Studies, 2024. https://doi.org/10.57138/ezzy1359.

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Childhood underweight is a consistent public health problem globally. About 12.6 per cent of the total under-five children (85.4 million) were underweight in 2020, while half of the underweight burden (42 million) belonged to the Southeast Asian Region. Being underweight is one of the major risk factors for early neonatal mortality and morbidity in many developing countries. Although the global trend of underweight children has decreased over time, such progress is not uniformly distributed among resource-poor settings. This study investigates the nationwide trend of the prevalence of childhoo
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Goshu, Degye, and Mezid Nasir. DEVELOPMENT AND GOVERNANCE IMPACTS OF DIGITAL PUBLIC INFRASTRUCTURE IN ETHIOPIA (DPI ETHIOPIA). Global Development Network (GDN), 2025. https://doi.org/10.69814/wp/202595.

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Digital Public Infrastructure (DPI) is the foundation for digital transformation of economies. The goal of digital transformation in government is to create a more transparent, efficient, and responsive public sector that meets the evolving needs of citizens. Ethiopian government has developed legal and regulatory frameworks and launched several initiatives over the last decade to enhance DPI and digitalization. Accordingly, the strategy for digitalization was launched in July 2020 with four cross-sectoral areas: infrastructure, supporting systems, digital interaction, and digital ecosystem. T
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Kingston, A. W., A. Mort, C. Deblonde, and O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329797.

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The Montney Formation is a highly productive hydrocarbon reservoir with significant reserves of hydrocarbon gases and liquids making it of great economic importance to Canada. However, high concentrations of hydrogen sulfide (H2S) have been encountered during exploration and development that have detrimental effects on environmental, health, and economics of production. H2S is a highly toxic and corrosive gas and therefore it is essential to understand the distribution of H2S within the basin in order to enhance identification of areas with a high risk of encountering elevated H2S concentratio
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