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Books on the topic 'Real time prediction'

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Published: 4 June 2021

Last updated: 26 January 2023

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1

Bell, M. G. H. Journey time prediction for real time bus monitoring and passenger information systems. Newcastle upon Tyne: University of Newcastle upon Tyne, Transport Operations Research Group, 1988.

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2

Amato, Jeffery D. The real-time predictive content of money for output. Basel, Switzerland: Bank for International Settlements, Monetary and Economic Dept., 2000.

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3

Rendine, John J. Real-time airborne ocean sampling and applications to naval operations. Monterey, Calif: Naval Postgraduate School, 1986.

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4

Marsteller, Gary E. Comparison of the Naval Operational Global Atmospheric Prediction System cloud analyses and forecasts with the Air Force Real Time nephanalyses cloud model. Monterey, Calif: Naval Postgraduate School, 1998.

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5

Clark, Todd E. Tests of equal predictive ability with real-time data. Kansas City [Mo.]: Research Division, Federal Reserve Bank of Kansas City, 2007.

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6

Harrington, Edward J. A real time sharpening of NOGAPS predictions of mid-latitude Central Pacific cyclones. Monterey, Calif: Naval Postgraduate School, 1992.

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7

Bauer, Jeffrey E. An impact-location estimation algorithm for subsonic uninhabited aircraft. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1997.

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8

Nihan, N. L. Predictive algorithm improvements for a real-time ramp control system: Final report, Research Project GC 8286, Task 16, Ramp Control Volume Forecast. [Olympia, Wash.]: Washington State Dept. of Transportation, Planning, Research and Public Transportation Division, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1991.

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9

Moshgbar, Mojgan. Prediction and real-time compensation of line wear in cone crushers. 1996.

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10

I, Cleveland Jeff, and Langley Research Center, eds. A study of workstation computational performance for real-time flight simulation. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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11

Fault and error latency under real workload: An experimental study. Urbana, Ill: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1986.

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12

United States. National Aeronautics and Space Administration., ed. Fault and error latency under real workload: An experimental study. Urbana, Ill: Coordinated Science Laboratory, College of Engineering, University of Illinois at Urbana-Champaign, 1986.

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13

Comparison of the Naval Operational Global Atmospheric Prediction SystemCloud Analyses and Forecasts With the Air Force Real Time Nephanalyses Cloud Model. Storming Media, 1998.

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14

van den Dool, Huug. Empirical Methods in Short-Term Climate Prediction. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780199202782.001.0001.

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This clear and accessible text describes the methods underlying short-term climate prediction at time scales of 2 weeks to a year. Although a difficult range to forecast accurately, there have been several important advances in the last ten years, most notably in understanding ocean-atmosphere interaction (El Nino for example), the release of global coverage data sets, and in prediction methods themselves. With an emphasis on the empirical approach, the text covers in detail empirical wave propagation, teleconnections, empirical orthogonal functions, and constructed analogue. It also provides a detailed description of nearly all methods used operationally in long-lead seasonal forecasts, with new examples and illustrations. The challenges of making a real time forecast are discussed, including protocol, format, and perceptions about users. Based where possible on global data sets, illustrations are not limited to the Northern Hemisphere, but include several examples from the Southern Hemisphere.

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15

National Aeronautics and Space Administration (NASA) Staff. Obtaining Reliable Predictions of Terrestrial Energy Coupling from Real-Time Solar Wind Measurements. Independently Published, 2018.

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16

Kumar, Swarn Avinash, Dac-Nhuong Le, Abhishek Kumar, Ashutosh Kumar Dubey, and Surbhi Bhatia. Evolving Predictive Analytics in Healthcare: New AI Techniques for Real-Time Interventions. Institution of Engineering & Technology, 2022.

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17

Kumar, Abhishek, Ashutosh Kumar Dubey, Surbhi Bhatia, Swarn Avinash Kumar, and Dac-Nhuong Le, eds. Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions. Institution of Engineering and Technology, 2022. http://dx.doi.org/10.1049/pbhe043e.

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18

Kumar, Swarn Avinash, Dac-Nhuong Le, Abhishek Kumar, Ashutosh Kumar Dubey, and Surbhi Bhatia. Evolving Predictive Analytics in Healthcare: New AI Techniques for Real-Time Interventions. Institution of Engineering & Technology, 2022.

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19

Jefferson, Offutt A., Harris F. C, Clemson University, and Langley Research Center, eds. Towards conservative reliability predictions for real-time software: Final report NASA research grant, NAG-1-1024. Clemson, S.C: Clemson University, 1991.

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20

Neural Generalized Predictive Control: A Newton-Raphson implementation. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1997.

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21

Jappelli, Tullio, and Luigi Pistaferri. The Age Profile of Consumption and Wealth. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199383146.003.0002.

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The life-cycle model yields a number of important empirical predictions about consumption and saving behavior. First, the growth rate of consumption depends on the difference between the expected real interest rate and the rate of time preference and varies with the elasticity of intertemporal substitution. Second, individuals seek to smooth the marginal utility of consumption over time. Third, young consumers should be accumulating resources for retirement, and hence have an adequate level of wealth at retirement. Finally, the elderly should be decumulating resources. To test these predictions, one can draw on a vast array of data on interest rates, consumption, income, and wealth. Some come from time series and national accounts, others from cross-sectional or longitudinal surveys of households. This chapter introduces stylized facts that emerge from a first examination of such data, pointing out the merits but also the drawbacks of the available sources.

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22

A, Bejczy, and United States. National Aeronautics and Space Administration., eds. Demonstration of a high-fidelity predictive/preview display technique for telerobotic servicing in space. [Washington, DC: National Aeronautics and Space Administration, 1997.

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23

A, Bejczy, and United States. National Aeronautics and Space Administration., eds. Demonstration of a high-fidelity predictive/preview display technique for telerobotic servicing in space. [Washington, DC: National Aeronautics and Space Administration, 1997.

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24

A, Bejczy, and United States. National Aeronautics and Space Administration., eds. Demonstration of a high-fidelity predictive/preview display technique for telerobotic servicing in space. [Washington, DC: National Aeronautics and Space Administration, 1997.

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25

A, Bejczy, and United States. National Aeronautics and Space Administration., eds. Demonstration of a high-fidelity predictive/preview display technique for telerobotic servicing in space. [Washington, DC: National Aeronautics and Space Administration, 1997.

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26

Edward, Teets, and NASA Dryden Flight Research Center., eds. An impact-location estimation algorithm for subsonic uninhabited aircraft. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1997.

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27

Edward, Teets, and NASA Dryden Flight Research Center., eds. An impact-location estimation algorithm for subsonic uninhabited aircraft. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1997.

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28

Edward, Teets, and NASA Dryden Flight Research Center., eds. An impact-location estimation algorithm for subsonic uninhabited aircraft. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1997.

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29

An impact-location estimation algorithm for subsonic uninhabited aircraft. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1997.

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30

Ali, Syed A., Leonard Kalfayan, and Carl T. Montgomery. Acid Stimulation. Society of Petroleum Engineers, 2016. http://dx.doi.org/10.2118/9781613994269.

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Stimulation of oil, gas, and injection wells with acid is almost as old as the petroleum engineering industry itself. Acid Stimulation, ensures a comprehensive and up-to-the-minute presentation by 19 subject matter experts, all at the forefront of the development of acidizing technology. Each chapter delivers an authoritative presentation of the key areas of Acid Stimulation, providing an important resource for anyone who designs, analyzes, and/or improves acidizing treatments. Acid Stimulation includesA concise review of the tremendous amount of information that has been gathered on the subject since the introduction of the first patents 100 years ago.A summary of the mechanisms that cause formation damage and how to quantify that damage.A summary of the chemistry, reaction kinetics, and methods of measurement of reactive fluids.The latest design information and philosophies for both carbonate and sandstone acidizing.Coverage of diversion, acid additives, and acid corrosion control included.Includes guidelines for treatment evaluation and real-time diagnostics.The latest models and measurement techniques for the prediction of acid fracture conductivity, rock dissolution, worm-holing fluid loss, and acid transport.Current practices in acid treatment safety, quality control, and protection of the environment.Many of the sections are supplemented with problem sets to reinforce concepts.

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31

Beavers, John, and Andrew Koontz-Garboden. The Roots of Verbal Meaning. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198855781.001.0001.

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This book explores possible and impossible word meanings, with a specific focus on the meanings of verbs. It adopts the now common view that verb meanings consist at least partly of an event structure, made up of an event template describing the verb’s broad temporal and causal contours that occurs across lots of verbs and groups them into semantic and grammatical classes, plus an idiosyncratic root describing specific, real world states and actions that distinguish verbs with the same template. While much work has focused on templates, less work has addressed the truth conditional contributions of roots, despite the importance of a theory of root meaning in fully defining the predictions event structural approaches make. This book addresses this lacuna, exploring two previously proposed constraints on root meaning: The Bifurcation Thesis of Roots, whereby roots never introduce the meanings introduced by templates, and Manner/Result Complementarity, which has as a component that roots can describe either a manner or a result state but never both at the same time. Two extended case studies, on change-of-state verbs and ditransitive verbs of caused possession, show that neither hypothesis holds, and that ultimately there may be no constraints on what a root can mean. Nonetheless, the book argues that event structures still have predictive value, and it presents a new theory of possible root meanings and how they interact with event templates that produces a new typology of possible verbs, albeit one where not just templates but also roots determine systematic semantic and grammatical properties.

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32

Raes, F. Real Time Radioactivity Monitoring and Its Interface with Predictive Atmospheric Transport Modelling: Proceedings of the 2nd REM Workshop, Ispra 5-6 December 1989. European Communities / Union (EUR-OP/OOPEC/OPOCE), 1990.

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33

F, Raes, and Workshop on Real Time Radioactivity Monitoring, (2nd : 1989 : Ispra), eds. Real time radioactivity monitoring and its interface with predictive atmospheric transport modelling: Proceedings of the 2nd REM Workshop,Ispra, 5-6 December 1989. Luxembourg: Commission of the European Communities, 1991.

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34

Buu, Anne, and Runze Li. New Statistical Methods Inspired by Data Collected from Alcohol and Substance Abuse Research. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190676001.003.0021.

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This chapter provides a nontechnical review of new statistical methodology for longitudinal data analysis that has been published in statistical journals in recent years. The methodology has applications in four important areas: (1) conducting variable selection among many highly correlated risk factors when the outcome measure is zero-inflated count; (2) characterizing developmental trajectories of symptomatology using regression splines; (3) modeling the longitudinal association between risk factors and substance use outcomes as time-varying effects; and (4) testing measurement reactivity and predictive validity using daily process data. The excellent statistical properties of the methods introduced have been supported by simulation studies. The applications in alcohol and substance abuse research have also been demonstrated by graphs on real longitudinal data.

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35

Davenport, Thomas H., and Steven M. Miller. Working with AI. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14453.001.0001.

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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

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36

Gelman, Andrew, and Deborah Nolan. Linear regression and correlation. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0005.

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This chapter addresses the descriptive treatment of linear regression with a single predictor: straight-line fitting, interpretation of the regression line and standard deviation, the confusing phenomenon of “regression to the mean,” correlation, and conducting regressions on the computer. These concepts are illustrated with student discussions and activities. Many examples are of the sort commonly found in statistics textbooks, but the focus here is on how to work the examples into student-participation activities rather than simply examples to be read or shown on the blackboard. Topics include the following relationships: height and income, height and hand span, world population over time, and exam scores.

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37

Anti-Ballistic Missile Laser Predictive Avoidance of Satellites: Theory and Software for Real-Time Processing and Deconfliction of Satellite Ephemerides With a Moving Platform Laser, Book 1. Storming Media, 1999.

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38

Anti-Ballistic Missile Laser Predictive Avoidance of Satellites: Theory and Software for Real- Time Processing and Deconfliction of Satellite Ephemerides With a Moving Platform Laser, Book 2. Storming Media, 1999.

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39

Llewellyn, Sue. What Do Dreams Do? Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198818953.001.0001.

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What is a dream? It’s a complex, non-obvious pattern derived from your experience. But you haven’t actually experienced it. Strange. Revealing complex, hidden patterns makes dreams odd. Dreams associate elements of different experiences to make something new: a pattern you didn’t know was there until you dreamt it. Patterns are discernible forms in the way something happens or is done. Some patterns are easy to spot, being certain and obvious: night follows day. Patterns in human/animal experiences are less obvious because, first, the patterned elements appear at different times or places and, second, the pattern exhibits tendencies not certainties. Spotting such patterns depends on non-obvious associations. If prompted with ‘sea’, while awake, your logical brain makes obvious associations, ‘beach’ or ‘boat’, with a seaside pattern i.e. beach-boat-seaside. But after awakening from dreaming, when your brain is still tuned to non-obvious associations, ‘sick’ may come to mind. A less obvious element of sea experiences. You tend to seasickness when it’s rough. But you also get sick if you eat shellfish, have a migraine, or travel in cars—but only if you read. Sea–rough–car–read–shellfish–migraine. Visualizing these non-obvious associations between elements of different experiences becomes dream-like. Dreaming brains evolved to identify non-obvious associations. Across evolutionary time, you didn’t want to get sick. Survival depended on being well enough to anticipate the non-obvious patterns of predators and human competitors, while securing access to food and water. Making associations drives many, if not all, brain functions. Dream associations support memory, emotional stability, creativity, unconscious decision-making, and prediction, while also contributing to mental illness. This book explains how.

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40

illustrator, Gower Neil, ed. How to read water: Clues and patterns from puddles to the sea : learn to gauge depth, navigate, forecast weather and make other predictions with water. The Experiment, 2016.

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41

Lambert, Heather. Urinary tract infection in infancy and childhood. Edited by Neil Sheerin. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0180_update_001.

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Urinary tract infection (UTI) in childhood is a common problem, which is frequently dismissed as trivial because most children with UTI have a good outcome. However, UTI is an important cause of acute illness in children and causes a considerable burden of ill health on children and families. In addition, UTI may be a marker of an underlying urinary tract abnormality. UTI in a few may cause significant long-term morbidity, renal scarring, hypertension, and renal impairment that may not present until adult life. Predicting which children will go on to have long-term sequelae remains a challenge.The risk of renal scarring is greatest in infants, the very group in whom diagnosis is often overlooked or delayed because clinical features are non-specific. Delay in treatment is associated with an increased risk of scarring in susceptible children. Thus accurate and rapid diagnosis of UTI is essential and requires a very high index of suspicion particularly in the youngest.The role of vesicoureteric reflux in acquired scarring is not fully understood though there is clearly an association, possibly because it is a risk factor for acute pyelonephritis. Scarring when it occurs is in the areas affected by acute pyelonephritis. Higher grades of reflux are associated with a worse outcome.Management and investigation of children with UTI consumes considerable healthcare resources. Limited understanding of the natural history and basic pathophysiology, variations in strategy with time and setting, and lack of evidence on long-term outcomes have resulted in considerable uncertainty. Some propose a minimal approach doing little investigation unless there is clear evidence for it; others favour an approach of continuation of current practice based on clinical experience until further evidence evolves. Some of the themes behind these controversies are explored.

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42

Martens, David. Data Science Ethics. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192847263.001.0001.

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Data science ethics is all about what is right and wrong when conducting data science. Data science has so far mainly been used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. This book looks at the different concepts and techniques related to data science ethics. Data scientists and business managers are not inherently unethical, but at the same time not trained to think this through either. This book aims to address this important gap. The techniques discussed range from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, measurements to assess, and techniques to remove discrimination against sensitive groups, and various explainable AI techniques. The real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, discrimination in recruitment, predicting pregnancy, redlining, re-identification of persons based on movie viewing and location data, cheating academics, and face recognition. Additionally, 10 discussions are provided with hypothetical scenarios, for example:‘you are the founder of a startup …’, which then present an ethical dilemma related to data science. These can serve as structured exercises to be completed with your fellow colleagues, and will teach you how to balance the ethical concerns and the utility of your data.

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43

Bucy, Erik P., and Patrick Stewart. The Personalization of Campaigns: Nonverbal Cues in Presidential Debates. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228637.013.52.

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Nonverbal cues are important elements of persuasive communication whose influence in political debates are receiving renewed attention. Recent advances in political debate research have been driven by biologically grounded explanations of behavior that draw on evolutionary theory and view televised debates as contests for social dominance. The application of biobehavioral coding to televised presidential debates opens new vistas for investigating this time-honored campaign tradition by introducing a systematic and readily replicated analytical framework for documenting the unspoken signals that are a continuous feature of competitive candidate encounters. As research utilizing biobehavioral measures of presidential debates and other political communication progresses, studies are becoming increasingly characterized by the use of multiple methodologies and merging of disparate data into combined systems of coding that support predictive modeling.Key elements of nonverbal persuasion include candidate appearance, communication style and behavior, as well as gender dynamics that regulate candidate interactions. Together, the use of facial expressions, voice tone, and bodily gestures form uniquely identifiable display repertoires that candidates perform within televised debate settings. Also at play are social and political norms that govern candidate encounters. From an evaluative standpoint, the visual equivalent of a verbal gaffe is the commission of a nonverbal expectancy violation, which draws viewer attention and interferes with information intake. Through second screens, viewers are able to register their reactions to candidate behavior in real time, and merging biobehavioral and social media approaches to debate effects is showing how such activity can be used as an outcome measure to assess the efficacy of candidate nonverbal communication during televised presidential debates.Methodological approaches employed to investigate nonverbal cues in presidential debates have expanded well beyond the time-honored technique of content analysis to include lab experiments, focus groups, continuous response measurement, eye tracking, vocalic analysis, biobehavioral coding, and use of the Facial Action Coding System to document the muscle movements that comprise leader expressions. Given the tradeoffs and myriad considerations involved in analyzing nonverbal cues, critical issues in measurement and methodology must be addressed when conducting research in this evolving area. With automated coding of nonverbal behavior just around the corner, future research should be designed to take advantage of the growing number of methodological advances in this rapidly evolving area of political communication research.

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