Relevant bibliographies by topics / Statistical processing of real data

Contents

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

Academic literature on the topic 'Statistical processing of real data'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Statistical processing of real data"

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Parygin, D. S., V. P. Malikov, A. V. Golubev, N. P. Sadovnikova, T. M. Petrova, and A. G. Finogeev. "Categorical data processing for real estate objects valuation using statistical analysis." Journal of Physics: Conference Series 1015 (May 2018): 032102. http://dx.doi.org/10.1088/1742-6596/1015/3/032102.

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Anju Santosh Yedatkar. "Real-time data analytics in distributed systems." International Journal of Scientific Research in Modern Science and Technology 3, no. 6 (2024): 09–16. http://dx.doi.org/10.59828/ijsrmst.v3i6.215.

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Real-time data analytics involves the processing and analysis of data as it arrives, delivering immediate insights that are crucial for time-sensitive applications. This research explores the platforms and techniques necessary for supporting real-time analytics, extending beyond traditional Event Processing Systems (EPS) to include broader big data contexts that integrate both 'data at rest' and 'data in motion' solutions. A detailed case study is presented, showcasing the application of the Event Swarm complex event processing engine in addressing financial analytics challenges. The study ide
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Nikolov, Asen, Nadezhda Sertova, and Maya Ignatova. "Real and statistical processing of barley yield data naturally contaminated with fusariotoxin." Bulgarian Journal of Animal Husbandry 61, no. 2 (2024): 49–53. http://dx.doi.org/10.61308/tixe6954.

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Fumonisins are produced by fungi of the genus Fusarium spp., which are widely spread out in the nature. They are produced during grain growth, ripening and harvesting and are known as “field mycotoxins“. Fusarium species can produce compounds that are toxic to animals and humans. In this study, the development of Fusarium toxins was determined in healthy and mechanically damaged barley grains treated and untreated with fungicide, respectively, under natural contamination. It was found that healthy kernels treated with fungicide had the highest yield of 6700 kg.ha-1 followed by the yield of dam
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Bhargavi, Tanneru. "Application of Kafka Messaging in Microservices for Real-Time Data Processing." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 11, no. 5 (2023): 1–4. https://doi.org/10.5281/zenodo.14945204.

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The growing need for scalable and efficient data processing in distributed systems has led to the widespread adoption of microservices architectures. Kafka, a distributed streaming platform, has gained significant traction as a messaging system in microservices-based applications, enabling real-time data processing and seamless communication between services. This paper explores the application of Kafka messaging in microservices for real-time data processing, discussing its implementation's benefits, challenges, and impact. The paper further highlights use cases, solutions to common problems,
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Haoxuan Sun. "Statistical analysis of clinical trial data in cancer research." World Journal of Biology Pharmacy and Health Sciences 20, no. 3 (2024): 417–28. https://doi.org/10.30574/wjbphs.2024.20.3.0972.

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Statistical methods are fundamental to designing and executing cancer clinical trials, which present unique challenges such as patient diversity, incomplete data, and ethical considerations. This article underscores the pivotal role of advanced statistical techniques in ensuring reliable outcomes, with a focus on sample size estimation, randomization, and endpoint selection. Key methodologies discussed include Cox regression, Bayesian modeling, and machine learning applications for predictive analytics and real-time data processing. Practical solutions to challenges like treatment effect asses
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Sun, Hong Feng, Ying Li, and Hong Lv. "Statistical Analysis of the Massive Traffic Data Based on Cloud Platform." Advanced Materials Research 717 (July 2013): 662–66. http://dx.doi.org/10.4028/www.scientific.net/amr.717.662.

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Currently, with the rapid development of various geographic data acquisition technologies, the data-intensive geographic calculation is becoming more and more important. The urban motor vehicles loaded with GPS, namely the transport vehicles, can real-timely collect a large number of urban traffic information. If these massive transportation vehicle data can be real-timely collected and analyzed, the real-time and accurate basic information will be provided for monitoring the large area of traffic status as well as the intelligent traffic management. Based on the requirements of the organizati
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Nalisnik, E. V. "Methods of clinical data analysis: comparison of different methods of processing and interpretation of clinical data to improve the effectiveness of therapy." Glavvrač (Chief Medical Officer), no. 4 (March 22, 2025): 66–77. https://doi.org/10.33920/med-03-2504-13.

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Clinical data analysis is a cornerstone of evidence-based medicine and a key to improving the effectiveness of therapy. This article reviews various methods of statistical processing of clinical data - from classical statistical tests to modern machine learning methods - and their comparative effectiveness in interpreting results to improve therapeutic outcomes. We will discuss examples of real-life studies demonstrating the application of these methods, as well as approaches to summarizing data (meta-analysis, analysis of real-world data) to make better informed treatment recommendations.
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Kulakova, Irina, Ol'ga Lebedeva, and Ermak Erofeev. "PROCESSING AND ANALYSIS OF BUS FLEET DATA IN A TABLE PROCESSOR." Bulletin of the Angarsk State Technical University 1, no. 18 (2024): 213–17. https://doi.org/10.36629/2686-777x-2024-1-18-213-217.

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The article discusses the methodology of preliminary processing of statistical data of the bus fleet using Microsoft Excel. This study is conducted on the basis of real data of a transport company. The analysis is performed using such tools as functions for working with data, including pivot tables, graphs and builtin formulas
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Liu, Hua, and Nan Zhang. "Data Processing in the Key Factors Affecting China's Endowment Real Estate Enterprises Financing." Applied Mechanics and Materials 730 (January 2015): 349–52. http://dx.doi.org/10.4028/www.scientific.net/amm.730.349.

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Financing problem is one of the main reasons for restricting the development of endowment real estate enterprises in China. By analyzing the present situation of endowment real estate enterprises financing and researching relevant literatures, we sum up 20 general influence factors. Using the data processing model of the principal component analysis method to analyze the 20 general influence factors under the help of SPSS 19.0 statistical analysis software, we can find out the key influence factors which affect endowment real estate enterprises financing. Aiming at the key influence factors, w
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Sun, Jun, Feng Ye, Nadia Nedjah, Ming Zhang, and Dong Xu. "A Practical Yet Accurate Real-Time Statistical Analysis Library for Hydrologic Time-Series Big Data." Water 15, no. 4 (2023): 708. http://dx.doi.org/10.3390/w15040708.

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Using different statistical analysis methods to examine hydrologic time-series data is the basis of accurate hydrologic status analysis. With the wide application of the Internet of Things and sensor technologies, traditional statistical analysis methods are unable to meet the demand for real-time and accurate hydrologic data analysis. The existing mainstream big-data analysis platforms lack analysis methods oriented to hydrologic data. In this context, a real-time statistical analysis library based on the new generation of big data processing engine Flink, called HydroStreamingLib, was propos
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Dissertations / Theses on the topic "Statistical processing of real data"

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Ha, Jin-cheol. "Real-time visual tracking using image processing and filtering methods." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28177.

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Thesis (M. S.)--Aerospace Engineering, Georgia Institute of Technology, 2008.<br>Committee Chair: Eric N. Johnson; Committee Co-Chair: Allen R. Tannenbaum; Committee Member: Anthony J. Calise; Committee Member: Eric Feron; Committee Member: Patricio A. Vela.
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Park, Chang Yun. "Predicting deterministic execution times of real-time programs /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/6978.

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Zamazal, Petr. "Statistická analýza rozsáhlých dat z průmyslu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-445466.

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This thesis deals with processing of real data regarding waste collection. It describes select parts of the fields of statistical tests, identification of outliers, correlation analysis and linear regression. This theoretical basis is applied through the programming language Python to process the data into a form suitable for creating linear models. Final models explain between 70 \% and 85 \% variability. Finally, the information obtained through this analysis is used to specify recommendations for the waste management company.
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Fernandez, Noemi. "Statistical information processing for data classification." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/3297.

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This thesis introduces new algorithms for analysis and classification of multivariate data. Statistical approaches are devised for the objectives of data clustering, data classification and object recognition. An initial investigation begins with the application of fundamental pattern recognition principles. Where such fundamental principles meet their limitations, statistical and neural algorithms are integrated to augment the overall approach for an enhanced solution. This thesis provides a new dimension to the problem of classification of data as a result of the following developments: (1
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Ostroumov, Ivan Victorovich. "Real time sensors data processing." Thesis, Polit. Challenges of science today: XIV International Scientific and Practical Conference of Young Researchers and Students, April 2–3, 2014 : theses. – К., 2014. – 35p, 2014. http://er.nau.edu.ua/handle/NAU/26582.

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Sensor it is the most powerful part of any system. Aviation industry is the plase where milions of sensors is be used for difetrent purpuses. Othe wery important task of avionics equipment is data transfer between sensors to processing equipment. Why it is so important to transmit data online into MatLab? Nowadays rapidly are developing unmanned aerial vehicles. If we can transmit data from UAV sensors into MatLab, then we can process it and get the desired information about UAV. Of course we have to use the most chipiest way to data transfer. Today everyone in the world has mobile phone
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Macias, Filiberto. "Real Time Telemetry Data Processing and Data Display." International Foundation for Telemetering, 1996. http://hdl.handle.net/10150/611405.

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International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California<br>The Telemetry Data Center (TDC) at White Sands Missile Range (WSMR) is now beginning to modernize its existing telemetry data processing system. Modern networking and interactive graphical displays are now being introduced. This infusion of modern technology will allow the TDC to provide our customers with enhanced data processing and display capability. The intent of this project is to outline this undertaking.
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White, Allan P., and Richard K. Dean. "Real-Time Test Data Processing System." International Foundation for Telemetering, 1989. http://hdl.handle.net/10150/614650.

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International Telemetering Conference Proceedings / October 30-November 02, 1989 / Town & Country Hotel & Convention Center, San Diego, California<br>The U.S. Army Aviation Development Test Activity at Fort Rucker, Alabama needed a real-time test data collection and processing capability for helicopter flight testing. The system had to be capable of collecting and processing both FM and PCM data streams from analog tape and/or a telemetry receiver. The hardware and software was to be off the shelf whenever possible. The integration was to result in a stand alone telemetry collection and proces
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Clapp, T. C. "Statistical methods for the processing of communications data." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597697.

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This thesis describes the use of methods derived from Bayesian statistics on the problem of blind equalisation of communications channels, although much of this work is applicable to the more general problem of blind deconvolution. In order to allow general models to be incorporated, numerical methods are used; the focus is on <I>Markov chain Monte Carlo </I>(MCMC) methods for processing of blocks of data and the use of <I>particle filters </I>for sequential processing. In order to obtain the best performance using MCMC, the choice of the Markov chain needs tailoring to the application in hand
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Dowling, Jason, John Welling, Loral Aerosys, Kathy Nanzetta, Toby Bennett, and Jeff Shi. "ACCELERATING REAL-TIME SPACE DATA PACKET PROCESSING." International Foundation for Telemetering, 1995. http://hdl.handle.net/10150/608429.

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International Telemetering Conference Proceedings / October 30-November 02, 1995 / Riviera Hotel, Las Vegas, Nevada<br>NASA’s use of high bandwidth packetized Consultative Committee for Space Data Systems (CCSDS) telemetry in future missions presents a great challenge to ground data system developers. These missions, including the Earth Observing System (EOS), call for high data rate interfaces and small packet sizes. Because each packet requires a similar amount of protocol processing, high data rates and small packet sizes dramatically increase the real-time workload on ground packet pr
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Khondoker, Md Mizanur Rahman. "Statistical methods for pre-processing microarray gene expression data." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/12367.

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A novel method is developed for combining multiple laser scans of microarrays to correct for “signal saturation” and “signal deterioration” effects in the gene expression measurement. A multivariate nonlinear functional regression model with Cauchy distributed errors having additive plus multiplicative scale is proposed as a model for combining multiple scan data. The model has been found to flexibly describe the nonlinear relationship in multiple scan data. The heavy tailed Cauchy distribution with additive plus multiplicative scale provides a basis for objective and robust estimation of gene
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Books on the topic "Statistical processing of real data"

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Berthold, M. Guide to intelligent data analysis: How to intelligently make sense of real data. Springer, 2010.

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Hailperin, Max. Load balancing using time series analysis for soft real time systems with statistically periodic loads. Dept. of Computer Science, Stanford University, 1993.

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Orlova, Ekaterina. Research and Development (R&D): data analysis and cost-effectiveness. INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/1959274.

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The textbook outlines the methodological foundations of statistical analysis, modeling and forecasting of data characterizing research and development (R&amp;D) both at the level of individual organizations and at the level of industries and regional systems. Examples of the analysis of empirical data on R&amp;D are given, which allow us to get an idea of the scope of statistical data processing methods in the analysis of real economic processes. A set of methods for the economic justification of R&amp;D projects, depending on their type and stage of the life cycle, is presented. Examples of e
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Hale, Robert L. MYSTAT: Statistical applications. Course Technology, 1992.

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Kiselev, I︠U︡. V. (I︠U︡riĭ Vasilʹevich), ed. Statistical methods of geophysical data processing. World Scientific, 2010.

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McCuen, Richard H. Microcomputer applications in statistical hydrology. Prentice Hall, 1993.

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A, Aitkin Murray, ed. Statistical modelling in GLIM. Clarendon Press, 1989.

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Nazarov, Dmitriy, and Anton Kopnin. Information technologies in professional activity: data mining and business analytics. INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2110964.

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The textbook offers a comprehensive look covering a wide range of topics related to the role of information technology in the modern world. Starting with an overview of the history of information technology and its evolution, the book introduces the reader to professions in the field of information and digital technologies, emphasizing them in various professional fields. The content of the textbook includes a detailed analysis of key concepts such as Data Science, Data Mining and Machine Learning, and their role in healthcare, law, education, science and business. The textbook provides a deta
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Thisted, Ronald A. Elements of statistical computing. Chapman and Hall, 1988.

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Froeschl, Karl. Metadata management in statistical information processing: A unified framework for metadata-based processing of statistical data aggregates. Springer, 1997.

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Book chapters on the topic "Statistical processing of real data"

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Kundu, Debasis, and Swagata Nandi. "Real Data Example." In Statistical Signal Processing. Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0628-6_6.

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Nandi, Swagata, and Debasis Kundu. "Real Data Example Using Sinusoidal-Like Models." In Statistical Signal Processing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8_7.

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Tavazzi, Erica, Camille L. Gerard, Olivier Michielin, Alexandre Wicky, Roberto Gatta, and Michel A. Cuendet. "A Process Mining Approach to Statistical Analysis: Application to a Real-World Advanced Melanoma Dataset." In Lecture Notes in Business Information Processing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72693-5_22.

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AbstractThanks to its ability to offer a time-oriented perspective on the clinical events that define the patient’s path of care, Process Mining (PM) is assuming an emerging role in clinical data analytics. PM’s ability to exploit time-series data and to build processes without any a priori knowledge suggests interesting synergies with the most common statistical analyses in healthcare, in particular survival analysis. In this work we demonstrate contributions of our process-oriented approach in analyzing a real-world retrospective dataset of patients treated for advanced melanoma at the Lausa
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Baumeister, Jan, Bernd Finkbeiner, Stefan Gumhold, and Malte Schledjewski. "Real-Time Visualization of Stream-Based Monitoring Data." In Runtime Verification. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17196-3_21.

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AbstractStream-based runtime monitors are used in safety-critical applications such as Unmanned Aerial Systems (UAS) to compute comprehensive statistics and logical assessments of system health that provide the human operator with critical information in hand-over situations. In such applications, a visual display of the monitoring data can be much more helpful than the textual alerts provided by a more traditional user interface. This visualization requires extensive real-time data processing, which includes the synchronization of data from different streams, filtering and aggregation, and pr
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Nigmatullin, Raoul R., Paolo Lino, and Guido Maione. "The Statistics of Fractional Moments and its Application for Quantitative Reading of Real Data." In New Digital Signal Processing Methods. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45359-6_3.

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Bingham, John. "On-Line and Real Time Systems." In Data Processing. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-19938-9_18.

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Orazi, Gilles, Marianne Marot, Iheb Khelifi, Franck Le Gall, Amara Richard, and Yvan Martzluff. "Edge-Cloud Solution Based on FIWARE and Context Augmentation to Monitor Usages of Carpooling Car Parks." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78572-6_9.

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Abstract Monitoring the usage and carbon impact of infrastructures such as carpooling car parks may be a challenge for local authorities. In this study, we address this issue by proposing an IoT solution that integrates both Edge processing and Cloud computing. Real-time continuous video AI processing automatically detects and stores information of car entries and exits. Then Cloud computing stores the anonymized data into a FIWARE information broker using ETSI’s NGSI-LD specification and employs query language to process and display useful statistics about carpark usage. To understand the car
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Weik, Martin H. "real-time data processing." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_15596.

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Fournier, Fabiana, and Inna Skarbovsky. "Real-Time Data Processing." In Big Data in Bioeconomy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_11.

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AbstractTo remain competitive, organizations are increasingly taking advantage of the high volumes of data produced in real time for actionable insights and operational decision-making. In this chapter, we present basic concepts in real-time analytics, their importance in today’s organizations, and their applicability to the bioeconomy domains investigated in the DataBio project. We begin by introducing key terminology for event processing, and motivation for the growing use of event processing systems, followed by a market analysis synopsis. Thereafter, we provide a high-level overview of eve
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Ratkó, István. "Statistical Data Processing by Microcomputer." In Medical Informatics Europe 85. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-93295-3_159.

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Conference papers on the topic "Statistical processing of real data"

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Bell, Graham E. C., Laury M. Rosenthal, and Kevin Lawson. "Electrochemical Noise Corrosion Monitoring Field Trial at Cahn 3 Water Treatment Plant Lost Hills, California." In CORROSION 2000. NACE International, 2000. https://doi.org/10.5006/c2000-00412.

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Abstract A real time electrochemical noise corrosion monitoring field trial was conducted at the Cahn 3 Water Treatment Plant in Lost Hills, California in late 1995. Five corrosion-monitoring probes were installed at different locations in the plant that had a history of weight loss corrosion between 0.5 to 450 mils per year (mpy). The five-element probes simultaneously performed Linear Polarization Resistance (LPR) and Electrochemical Noise (EN) measurements. Instantaneous and time averaged corrosion rates were calculated and recorded along with various other statistically relevant parameters
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Sarnaglia, A. J. Q., V. A. Reisen, P. Bondou, and C. Levy-Leduc. "A robust estimation approach for fitting a PARMA model to real data." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551740.

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Höper, Lukas, Susanne Podworny, Carsten Schulte, and Daniel Frischemeier. "Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network." In IASE 2021 Satellite Conference: Statistics Education in the Era of Data Science. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.nkppy.

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Students are not aware and have little understanding of collecting and processing personal data in their everyday contexts of interaction with data-driven digital artifacts. To be aware of where, how and why data are collected and processed is important to be self-determined. Therefore, we develop and evaluate a teaching sequence to provide reasoning about data as a fundamental aspect of statistical literacy. This teaching sequences deals with the context of interaction with a cellular network where location data are collected. Students get real location data from an unknown person which can b
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Babrauckas, Theresa L., and Dale J. Arpasi. "Integrated CFD and Experiments Real-Time Data Acquisition Development." In ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-097.

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The Computational Technologies Branch of NASA Lewis Research Center is developing an Integrated CFD and Experiments (ICE) system as part of the Multistage Compressor Flow Physics program. The ICE operating environment software is general and can be configured for different applications where CFD and experimental information must be managed. ICE currently consists of three powerful subsystems. The experiment support subsystem acquires data and uses parallel processing to generate statistical information and on-line graphical displays for flow physics experiments. The simulation subsystem allows
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Dalton, L. A., and E. R. Dougherty. "Bayesian MMSE estimation of classification error and performance on real genomic data." In 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2010. http://dx.doi.org/10.1109/gensips.2010.5719674.

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Platonova, M. V., and E. G. Klimova. "Determining the likely localization of methane sources using forecast time series and satellite data." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.70.91.039.

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The paper is devoted to the topical problem of determining the sources of methane from observational data. An algorithm based on the statistical optimization method used to estimate a time constant parameter is considered. To implement the algorithm, a variant of ensemble smoothing is used, which is an optimal estimate of the desired parameter based on observational data and forecast for a given time interval. This paper presents the implementation of the algorithm for real observational and forecast data, the results of a three-dimensional transport and diffusion model are taken as a mathemat
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Hartman, Daniel A. "Real-Time Detection of Processing Flaws During Inertia Friction Welding of Critical Components." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68014.

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Outside of statistical process control, current manufacturing quality control is founded upon a “make-then-inspect” mindset [1]. While this approach is an important part of the quality control process, post-process inspection is labor intensive, a bottleneck to continuous production throughput, costly, subject to human interpretation, and susceptible to missing subtle defects. This paper presents the application of in-process quality control (IPQC) during inertia friction welding of critical components. This paper is a follow-on to a preliminary investigation into a new sensing technique for r
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Atluru, Sri, and Amit Deshpande. "Statistical Process Monitoring With MTConnect." In ASME 2012 International Manufacturing Science and Engineering Conference collocated with the 40th North American Manufacturing Research Conference and in participation with the International Conference on Tribology Materials and Processing. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/msec2012-7344.

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Statistical Process Control (SPC) techniques are used widely in the manufacturing industry. However, it is sometimes observed that a deviation that is within the acceptable range of inherent process variation does not necessarily conform to specifications. This is especially true in the case of low volume; high precision manufacturing that is customary in aerospace and defense industries. In order to study the limitations posed by conventional SPC techniques in such manufacturing environments, a study was undertaken at TechSolve Inc., Cincinnati to develop a standalone SPC tool. The SPC tool s
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Li, Hongfei, and Hendrik F. Hamann. "A Statistical Approach to Thermal Zone Mapping." In ASME 2011 Pacific Rim Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/ipack2011-52192.

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Although in most buildings the spatial allocation of cooling resources can be managed using multiple air handling units and an air ducting system, it can be challenging for an operator to leverage this capability, partially because of the complex interdependencies between the different control options. This is in particular important for data centers, where cooling is a major cost while the sufficient allocation of cooling resources has to ensure the reliable operation of mission-critical information processing equipment. It has been shown that thermal zones can provide valuable decision suppo
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Banerjee, Sauvik, Fabrizio Ricci, and Ajit Mal. "A Vibration and Wave Propagation Based Methodology for Near Real-Time Damage Monitoring of Composite Structures." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-42095.

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This paper presents a novel approach to achieve near real-time damage monitoring whereby ultrasonic wave propagation and vibration data are analyzed to determine the location and degree of damage, requiring minimal operator intervention. An improved test setup, consisting of high fidelity sensor arrays, laser scanning vibrometer, data acquisition boards, signal conditioning and dedicated software has been implemented. The collected data are analyzed using a statistical damage index approach to determine the degree of damage to the structure as a function of time with a high confidence level. T
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Reports on the topic "Statistical processing of real data"

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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real tim
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Fiori, R. A. D., K. Reiter, D. Galeschuk, T. Ghosal, and N. Olfert. Near real-time processing of NRCan riometer data. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/332078.

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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Owechko, Yuri, and Bernard Soffer. Real-Time Implementation of Nonlinear Optical Data Processing Functions. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada233521.

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Beer, Randall D. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada251567.

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Beer, Randall D. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada259120.

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Anumukonda, Bharath Chandr. Real World Scalable Big Data Processing for Smart Transportation Performance Assessment. Iowa State University, 2022. http://dx.doi.org/10.31274/cc-20240624-1189.

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Ranjan, Niloo, Jibonananda Sanyal, and Joshua Ryan New. In-Situ Statistical Analysis of Autotune Simulation Data using Graphical Processing Units. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1093099.

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Koopman, D. STATISTICAL EVALUATION OF PROCESSING DATA FROM THE RH RU HG MATRIX STUDY. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/952445.

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Roth, Christopher J., Nelson A. Bonito, Maurice F. Tautz, and Eugene C. Courtney. CHAWS Data Processing and Analysis Tools in Real-Time and Postflight Environments. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada381118.

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