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Books on the topic 'Load prediction and scheduling'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Wiendahl, Hans-Peter. Load-oriented manufacturing control. Berlin: Springer-Verlag, 1995.

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2

Papini, Marcello. Fracture load prediction of structural adhesive joints. Ottawa: National Library of Canada, 1993.

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3

Wiendahl, Hans-Peter. Load-Oriented Manufacturing Control. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995.

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4

R, Hurson A., and Kavi Krishna M, eds. Scheduling and load balancing in parallel and distributed systems. Los Alamitos, Calif: IEEE Computer Society Press, 1995.

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5

Yusof, Norzan Mohd. Environmental load versus concrete quality: Prediction of structure's design life. Birmingham: University of Birmingham, 1994.

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6

Kondo, Yusuke. Prediction methods of rough-road-load applied to vehicle body. Warrendale, Pa: Society of Automative Engineers, 1990.

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7

McTaggart, Kevin A. A review of eight seakeeping and hydrodynamic load prediction codes. Dartmouth, N.S: Defence Research Establishment Atlantic, 1992.

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8

Tomar, Anuradha, Prerna Gaur, and Xiaolong Jin, eds. Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6490-9.

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9

Hirst, Eric. Ancillary-service details: Dynamic scheduling. Oak Ridge, Tenn: Oak Ridge National Laboratory, 1997.

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10

Venugopal, Sesh. Effects of partitioning and scheduling sparse matrix factorization on communication and load balance. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1991.

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11

Joseph, Katz. Evaluation of an aerodynamic-load prediction method on an STOL fighter configuration. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1985.

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12

Fleming, David P. Transient vibration prediction for rotors on ball bearings using load-dependent non-linear bearing stiffness. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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13

Currie, Robert Hamilton. Distribution management: An investigation into a full-load, multi-terminal, vehicle scheduling problem with backhauling and time windows. Birmingham: University of Birmingham, 2003.

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14

Meeting, Advisory Group for Aerospace Research and Development Structures and Materials Panel. Gust load prediction and alleviation on a fighter aircraft: Papers presented at the 61st meeting of the Structures and Materials Panel of Agard in Oberammergau, Germany on 8-13 September 1985. Neuilly sur Seine: Agard, 1986.

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15

Grynchenko, Oleksandr, and Oleksiy Alfyorov. Mechanical Reliability: Prediction and Management Under Extreme Load Conditions. Springer, 2020.

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16

Grynchenko, Oleksandr, and Oleksiy Alfyorov. Mechanical Reliability: Prediction and Management under Extreme Load Conditions. Springer International Publishing AG, 2021.

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17

Jin, XiaoLong, Anuradha Tomar, and Prerna Gaur. Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting. Springer, 2023.

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18

Prediction of contact path and load sharing in spiral bevel gears. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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19

Jacob, Joseph. Automatic scheduling and dynamic load sharing of parallel computations on heterogeneous workstation clusters. 1995.

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20

Hi-Fidelity Simulation and Prediction of Helicopter Single Point External Load Stabilization. Storming Media, 2001.

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21

Simulation Validation and Flight Prediction of UH-60A Black Hawk Helicopter/Slung Load Characteristics. Storming Media, 1999.

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22

Chakravarthy, Sharma, and Qingchun Jiang. Stream Data Processing - A Quality of Service Perspective: Modeling, Scheduling, Load Shedding, and Complex Event Processing. Springer, 2010.

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23

National Aeronautics and Space Administration (NASA) Staff. Transient Vibration Prediction for Rotors on Ball Bearings Using Load-Dependent Non-Linear Bearing Stiffness. Independently Published, 2018.

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24

Chakravarthy, Sharma, and Qingchun Jiang. Stream Data Processing: A Quality of Service Perspective: Modeling, Scheduling, Load Shedding, and Complex Event Processing (Advances in Database Systems Book 36). Springer, 2009.

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25

United States. National Aeronautics and Space Administration., ed. Program to develop a performance and heat load prediction system for multistate turbines: Forty-fourth technical progress narrative and financial management report for the period January 12 to January 31, 1994. East Hartford, Conn: United Technologies, Pratt & Whitney, 1994.

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26

Gould, JS, WL McCaw, NP Cheney, PF Ellis, IK Knight, and AL Sullivan. Project Vesta: Fire in Dry Eucalypt Forest. CSIRO Publishing, 2008. http://dx.doi.org/10.1071/9780643101296.

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Abstract:
Project Vesta was a comprehensive research project to investigate the behaviour and spread of high-intensity bushfires in dry eucalypt forests with different fuel ages and understorey vegetation structures. The project was designed to quantify age-related changes in fuel attributes and fire behaviour in dry eucalypt forests typical of southern Australia. The four main scientific aims of Project Vesta were: To quantify the changes in the behaviour of fire in dry eucalypt forest as fuel develops with age (i.e. time since fire); To characterise wind speed profiles in forest with different overstorey and understorey vegetation structure in relation to fire behaviour; To develop new algorithms describing the relationship between fire spread and wind speed, and fire spread and fuel characteristics including load, structure and height; and to develop a National Fire Behaviour Prediction System for dry eucalypt forests. These aims have been addressed through a program of experimental burning and associated studies at two sites in the south-west of Western Australia.
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27

Mills, Gary H. Pulmonary disease and anaesthesia. Edited by Philip M. Hopkins. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0082.

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Respiratory adverse events are the commonest complications after anaesthesia and have profound implications for the recovery of the patient and their subsequent health. Outcome prediction related to respiratory disease and complications is vital when determining the risk:benefit balance of surgery and providing informed consent. Surgery produces an inflammatory response and pain, which affects the respiratory system. Anaesthesia produces atelectasis, decreases the drive to breathe, and causes muscle weakness. As the respiratory system ages, closing capacity increases and airway closure becomes an increasing issue, resulting in atelectasis. Increasing comorbidity and polypharmacy reduces the patient’s ability to eliminate drugs. The proportion of major operations on older frailer patients is rising and postoperative recovery becomes more complicated and the demand for critical care rises. At the same time, the population is becoming more obese, producing rapid decreases in end-expiratory lung volume on induction, together with a high incidence of sleep-disordered breathing. Despite this, many high-risk patients are not accurately identified preoperatively, and of those that are admitted to critical care, some are discharged and then readmitted to the intensive care unit with complications. Respiratory diseases may lead to increases in pulmonary vascular resistance and increased load on the right heart. Some lung diseases are primarily fibrotic or obstructive. Some are inflammatory, autoimmune, or vasculitic. Other diseases relate to the drive to breathe, the nerve supply to, or the respiratory muscles themselves. The range of types of respiratory disease is wide and the physiological consequences of respiratory support are complex. Research continues into the best modes of respiratory support in theatre and in the postoperative period and how best to protect the normal lung. It is therefore essential to understand the effects of surgery and anaesthesia and how this impacts existing respiratory disease, and the way this affects the balance between load on the respiratory system and its capacity to cope.
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