Littérature scientifique sur le sujet « Resource on Demand »
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Articles de revues sur le sujet "Resource on Demand"
Mondal, Sakib A. « Resource allocation problem under single resource assignment ». RAIRO - Operations Research 52, no 2 (avril 2018) : 371–82. http://dx.doi.org/10.1051/ro/2017035.
Texte intégralKania, Eugene. « Supply and Demand ». Mechanical Engineering 128, no 02 (1 février 2006) : 25–26. http://dx.doi.org/10.1115/1.2006-feb-2.
Texte intégralDungey, Mardi, Renee Fry-McKibbin et Verity Linehan. « Chinese resource demand and the natural resource supplier ». Applied Economics 46, no 2 (26 septembre 2013) : 167–78. http://dx.doi.org/10.1080/00036846.2013.835483.
Texte intégralRuff, Larry E. « Demand Response : Reality versus “Resource” ». Electricity Journal 15, no 10 (décembre 2002) : 10–23. http://dx.doi.org/10.1016/s1040-6190(02)00401-3.
Texte intégralPhaneuf, Daniel J. « Heterogeneity in Environmental Demand ». Annual Review of Resource Economics 5, no 1 (juin 2013) : 227–44. http://dx.doi.org/10.1146/annurev-resource-091912-151841.
Texte intégralRahayu, Puspita Puji. « Model Tuntutan Pekerjaan dan Sumber Daya Pekerjaan ». JUDICIOUS 2, no 2 (30 décembre 2021) : 214–18. http://dx.doi.org/10.37010/jdc.v2i2.603.
Texte intégralKalach, A. V., L. V. Rossikhina, E. B. Govorin, R. B. Golovkin et P. V. Shumov. « Resource allocation models at resource quantity dependence on demand ». IOP Conference Series : Materials Science and Engineering 537 (17 juin 2019) : 032003. http://dx.doi.org/10.1088/1757-899x/537/3/032003.
Texte intégralLu, Xingguang. « A Human Resource Demand Forecasting Method Based on Improved BP Algorithm ». Computational Intelligence and Neuroscience 2022 (29 mars 2022) : 1–9. http://dx.doi.org/10.1155/2022/3534840.
Texte intégralShakil, Kashish Ara, Mansaf Alam et Samiya Khan. « A latency-aware max-min algorithm for resource allocation in cloud ». International Journal of Electrical and Computer Engineering (IJECE) 11, no 1 (1 février 2021) : 671. http://dx.doi.org/10.11591/ijece.v11i1.pp671-685.
Texte intégralSpitz, Gabriel. « Flexibility in Resource Allocation and the Performance of Time-Sharing Tasks ». Proceedings of the Human Factors Society Annual Meeting 32, no 19 (octobre 1988) : 1466–70. http://dx.doi.org/10.1177/154193128803201934.
Texte intégralThèses sur le sujet "Resource on Demand"
Rainwater, Chase E. « Resource constrained assignment problems with flexible customer demand ». [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024847.
Texte intégralMiller, Benjamin Israel. « Estimating the Firm’s Demand for Human Resource Management Practices ». Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/econ_diss/34.
Texte intégralMiller, Benjamin Israel. « Estimating the firm's demand for human resource management practices ». unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-11192008-141353/.
Texte intégralTitle from file title page. Bruce E. Kaufman, committee chair; Barry T. Hirsch, Klara S. Peter, Hyeon J. Park, committee members. Description based on contents viewed Sept. 22, 2009. Includes bibliographical references (p. 159-165).
Muench, Andrew J. (Andrew James) 1970. « Redefining the aftermarket demand forecasting process using enterprise resource planning ». Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/89924.
Texte intégralIncludes bibliographical references (leaves 127-128).
by Andrew J. Muench.
S.M.
Cantwell, Marilyn L. « Resource and demand effects on elderly functionality and residential mobility / ». The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487671108307051.
Texte intégralLandi, Marco. « Bidirectional Metering Advancements and Applications to Demand Response Resource Management ». Doctoral thesis, Universita degli studi di Salerno, 2014. http://hdl.handle.net/10556/1448.
Texte intégralThe power grid is an electric system capable of performing electricity generation, transmission, distribution and control. Nowadays it has been subjected to a deep transformation, which will reshape it completely. In fact, growing electricity demand and consequent increase of power losses in transmission and distribution grids, the increase in prices of fossil fuels and the diffusion of renewable resources, the need for a more effective and efficient grid management and use of energy, the availability of new technologies to be integrated into the grid, they all push for a modernization of the power grid. Integrating technology and approaches typical of different areas (i.e. power systems, ICT, measurements, automatic controls), the aim is to build a grid capable of engulfing all types of sources and loads, capable of efficiently deliver electricity automatically adapting to changes in generation and demand, ultimately empowering customers with new and advanced services. This paradigm is known as Smart Grid. In this context, the role of measurement theories, techniques and instrumentation is a fundamental one: the automatic management and control of the grid is a completely unfeasible goal without a timely and reliable picture of the state of the electric network. For this reason, a metering infrastructure (including sensors, data acquisition and process system and communication devices and protocols) is needed to the development of a smarter grid. Among the features of such an infrastructure are the ability to execute accurate and real‐time measurements, the evaluation of power supply quality and the collection of measured data and its communication to the system operator. Moreover, a so defined architecture can be extended to all kinds of energy consumption, not only the electricity ones. With the development of an open energy market, an independent entity could be put in charge of the execution of measurements on the grid and the management of the metering infrastructure: in this way, “certified” measurements will be guaranteed, ensuring an equal treatment of all grid and market users. In the thesis, different aspects relative to measurement applications in the context of a Smart Grid have been covered. A smart meter prototype to be installed in customers’ premises has been realized: it is an electricity meter also capable of interfacing with gas and hot water meters, acting as a hub for monitoring the overall energy consumption. The realized prototype is based on an ARM Cortex M3 microcontroller architecture (precisely, the ST STM32F103), which guarantees a good compromise among cost, performance and availability of internal peripherals. Advanced measurement algorithms to ensure accurate bidirectional measurements even in non‐sinusoidal conditions have been implemented in the meter software. Apart from voltage and current transducer, the meter embeds also a proportional and three binary actuators: through them is possible to intervene directly on the monitored network, allowing for load management policies implementation. Naturally the smart meter is only functional if being a part of a metering and communication infrastructure: this allows not only the collection of measured data and its transmission to a Management Unit, which can so build an image of the state of the network, but also to provide users with relevant information regarding their consumptions and to realize load management policies. In fact, the realized prototype architecture manages load curtailments in Demand Response programs relying on the price of energy and on a cost threshold that can be set up by the user. Using a web interface, the user can verify his own energy consumptions, manage contracts with the utility companies and eventually his participation in DR programs, and also manually intervene on his loads. In the thesis storage systems, of fundamental importance in a Smart Grid Context for the chance they offer of decoupling generation and consumption, have been studied. They represent a key driver towards an effective and more efficient use of renewable energy sources and can provide the grid with additional services (such as down and up regulation). In this context, the focus has been on li‐ion batteries: measurement techniques for the estimation of their state of life have been realized. Since batteries are becoming increasingly important in grid operation and management, knowing the degradation they are subjected has a relevant impact not only on grid resource planning (i.e. substitution of worn off devices and its scheduling) but also on the reliability in the services based on batteries. The implemented techniques, based on Fuzzy logic and neural networks, allow to estimate the State of Life of li‐ion batteries even for variation of the external factors influencing battery life (temperature, discharge current, DoD). Among the requisites a Smart Grid architecture has, is the integration into the grid of Electric Vehicles. EVs include both All Electric Vehicles and Plug‐in Hybrid Electric Vehicles and have been considered by governments and industry as sustainable means of transportation and, therefore, have been the object of intensive study and development in recent years. Their number is forecasted to increase considerably in the next future, with alleged consequences on the power grid: while charging, they represent a consistent additional load that, if not properly managed, could be unbearable for the grid. Nonetheless, EVs can be also a resource, providing their locally stored energy to the power grid, thus realizing useful ancillary services. The paradigm just described is usually referred to as Vehicle‐to‐Grid (V2G). Being the storage systems onboard the EVs based on li‐ion batteries, starting from the measurement and estimation techniques precedently introduced, aim of the thesis work will be the realization of a management systems for EV fleets for the provision of V2G services. Assuming the system model in which the aggregator not only manages such services, but can also be the owner of the batteries, the goal is to manage the fleets so to maximize battery life, and guarantee equal treatment to all the users participating in the V2G program. [edited by author]
XII n.s.
Hong, Seong-Jong. « Analysis of the Benefits of Resource Flexibility, Considering Different Flexibility Structures ». Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11185.
Texte intégralPh. D.
Acharya, Gayatri. « Hydrological-economic linkages in water resource management ». Thesis, University of York, 1998. http://etheses.whiterose.ac.uk/10809/.
Texte intégralJuana, James Sharka. « Efficiency and equity considerations in modeling inter-sectoral water demand in South Africa ». Pretoria : [S.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-06062008-140425/.
Texte intégralXu, Dongsheng. « Resource allocation among multiple stochastic demand classes in express delivery chains / ». View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?IELM%202007%20XU.
Texte intégralLivres sur le sujet "Resource on Demand"
Agency, Environment, dir. Resource demand management techniques for sustainable development. Bristol : Environment Agency, 1998.
Trouver le texte intégralKhadr, Ali M. Nonrenewable resource allocation under intertemporally dependent demand. Oxford : Oxford Institute for Energy Studies, 1987.
Trouver le texte intégralAmerican Medical Association. Physician Manpower Clearinghouse., dir. Physician manpower : A resource guide. [Chicago, IL] : Physician Manpower Clearinghouse, Center for Health Policy Research, American Medical Association, 1987.
Trouver le texte intégralRutledge, Patrice-Anne. WordPress on demand. Indianapolis, IN : Que, 2013.
Trouver le texte intégralSystems, Adobe, dir. Adobe InDesign CS4 : On demand. Indianapolis, Ind : Que Pub., 2008.
Trouver le texte intégralAgency, Environment, dir. Resource demand management for sustainable development March 1998. Bristol : Environment Agency, 1998.
Trouver le texte intégralAdobe Muse on demand. Indianapolis, IN : Que Pub., 2012.
Trouver le texte intégralHu, Zhaoguang, Xinyang Han et Quan Wen. Integrated Resource Strategic Planning and Power Demand-Side Management. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37084-7.
Texte intégralAgency, Environment. Resource demand management techniques for sustainable development : March 1998. Bristol : Environment Agency, 1998.
Trouver le texte intégralHu, Zhaoguang. Integrated Resource Strategic Planning and Power Demand-Side Management. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013.
Trouver le texte intégralChapitres de livres sur le sujet "Resource on Demand"
Kounev, Samuel, Klaus-Dieter Lange et Jóakim von Kistowski. « Resource Demand Estimation ». Dans Systems Benchmarking, 365–88. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41705-5_17.
Texte intégralDerks, R. « Demand Management ». Dans Integrated Electricity Resource Planning, 475–84. Dordrecht : Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1054-9_26.
Texte intégralChandrakanth, M. G. « Demand Side Economics of Micro-irrigation ». Dans Water Resource Economics, 125–38. New Delhi : Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2479-2_9.
Texte intégralLloyd Owen, David. « Demand Management and Resource Recovery ». Dans Global Water Funding, 317–41. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49454-4_9.
Texte intégralRajegopal, Shan, Philip McGuin et James Waller. « Map resource capacity and demand ». Dans Project Portfolio Management, 175–84. London : Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230206496_9.
Texte intégralFrisch, Jean-Romain. « General Table of Demand/Resource Stresses ». Dans Future Stresses for Energy Resources, 29–32. Dordrecht : Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4209-7_3.
Texte intégralRosenfeld, Arthur H. « Policy : Integrated Resource Planning to Optimize Energy Services ». Dans Global Energy Demand in Transition, 251. Boston, MA : Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1048-6_23.
Texte intégralSiddiqui, Mumtaz, et Thomas Fahringer. « Semantics-Based Activity Synthesis : Improving On-Demand Provisioning and Planning ». Dans Grid Resource Management, 179–98. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11579-0_8.
Texte intégralGrigg, Neil S. « Demand for Water, Water Services, and Ecosystem Services ». Dans Integrated Water Resource Management, 207–25. London : Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-57615-6_11.
Texte intégralRyoo, Jeong-dong, et Shivendra S. Panwar. « Resource Optimization in Video-On-Demand Networks ». Dans Multimedia Communications and Video Coding, 125–31. Boston, MA : Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0403-6_16.
Texte intégralActes de conférences sur le sujet "Resource on Demand"
Kowli, Anupama S., et George Gross. « Incorporation of demand response resources in resource investment analysis ». Dans 2009 IEEE Bucharest PowerTech (POWERTECH). IEEE, 2009. http://dx.doi.org/10.1109/ptc.2009.5282141.
Texte intégralGrohmann, Johannes, Nikolas Herbst, Simon Spinner et Samuel Kounev. « Self-Tuning Resource Demand Estimation ». Dans 2017 IEEE International Conference on Autonomic Computing (ICAC). IEEE, 2017. http://dx.doi.org/10.1109/icac.2017.19.
Texte intégralDavis, Allen L., et Robert C. Brawn. « General Purpose Demand Allocator (DALLOC) ». Dans Joint Conference on Water Resource Engineering and Water Resources Planning and Management 2000. Reston, VA : American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40517(2000)190.
Texte intégralEbneyousef, Sepideh, et Saeed Ghazanfari-Rad. « Cloud Resource Demand Prediction to Achieve Efficient Resource Provisioning ». Dans 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS). IEEE, 2022. http://dx.doi.org/10.1109/icspis56952.2022.10043900.
Texte intégralZhang, Ying, Gang Huang, Xuanzhe Liu et Hong Mei. « Integrating Resource Consumption and Allocation for Infrastructure Resources on-Demand ». Dans 2010 IEEE International Conference on Cloud Computing (CLOUD). IEEE, 2010. http://dx.doi.org/10.1109/cloud.2010.11.
Texte intégral« Traffic Engineering, Resource Allocation, and QoS ». Dans 2006 IEEE First International Workshop on Bandwidth on Demand. IEEE, 2006. http://dx.doi.org/10.1109/bod.2006.320795.
Texte intégralSilva, Thiciane Suely Couto, Fabio Gomes Rocha et Rodrigo Pereira dos Santos. « Resource Demand Management in Java Ecosystem ». Dans SBSI'19 : XV Brazilian Symposium on Information Systems. New York, NY, USA : ACM, 2019. http://dx.doi.org/10.1145/3330204.3330212.
Texte intégralAndersen, Johannes, et Roger Powell. « DMA Structured State-Estimation for Demand Monitoring ». Dans Joint Conference on Water Resource Engineering and Water Resources Planning and Management 2000. Reston, VA : American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40517(2000)214.
Texte intégralShah, Amip, Ratnesh Sharma, Cullen Bash, Manish Marwah, Tom Christian, Chandrakant Patel et Kiara Corrigan. « IT-Enabled Resource Management ». Dans ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90083.
Texte intégralHariharan, Smitha, et Venkat Allada. « Uncertain Demand Driven Resource Platform Design for a Service Center ». Dans ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81191.
Texte intégralRapports d'organisations sur le sujet "Resource on Demand"
Kalsi, Karanjit, Tess L. Williams, Laurentiu D. Marinovici, Marcelo A. Elizondo et Jianming Lian. Loads as a Resource : Frequency Responsive Demand. Office of Scientific and Technical Information (OSTI), novembre 2015. http://dx.doi.org/10.2172/1375378.
Texte intégralKalsi, Karanjit, Jacob Hansen, Jason C. Fuller, Laurentiu D. Marinovici, Marcelo A. Elizondo, Tess L. Williams, Jianming Lian et Yannan Sun. Loads as a Resource : Frequency Responsive Demand. Office of Scientific and Technical Information (OSTI), décembre 2015. http://dx.doi.org/10.2172/1375379.
Texte intégralKalsi, Karanjit, Jianming Lian, Laurentiu D. Marinovici, Marcelo A. Elizondo, Wei Zhang et Christian Moya. Loads as a Resource : Frequency Responsive Demand. Office of Scientific and Technical Information (OSTI), octobre 2014. http://dx.doi.org/10.2172/1375380.
Texte intégralEto, Joseph H., Nancy Jo Lewis, David Watson, Sila Kiliccote, David Auslander, Igor Paprotny et Yuri Makarov. Demand Response as a System Reliability Resource. Office of Scientific and Technical Information (OSTI), décembre 2012. http://dx.doi.org/10.2172/1172114.
Texte intégralSwiler, Laura, Teresa Portone et Walter Beyeler. Uncertainty analysis of Resource Demand Model for Covid-19. Office of Scientific and Technical Information (OSTI), mai 2020. http://dx.doi.org/10.2172/1630395.
Texte intégralKang, Shian C. Learning to Predict Demand in a Transport-Resource Sharing Task. Fort Belvoir, VA : Defense Technical Information Center, septembre 2015. http://dx.doi.org/10.21236/ad1009057.
Texte intégralSatchwell, Andrew, et Ryan Hledik. Analytical Frameworks to Incorporate Demand Response in Long-term Resource Planning. Office of Scientific and Technical Information (OSTI), décembre 2013. http://dx.doi.org/10.2172/1164372.
Texte intégralFrazier, Christopher, Daniel Krofcheck, Jared Gearhart et Walter Beyeler. Integrated Resource Supply-Demand-Routing Model for the COVID-19 Crisis. Office of Scientific and Technical Information (OSTI), mai 2020. http://dx.doi.org/10.2172/1763531.
Texte intégralRaab, J., et M. Schweitzer. Public involvement in integrated resource planning : A study of demand-side management collaboratives. Office of Scientific and Technical Information (OSTI), février 1992. http://dx.doi.org/10.2172/10146196.
Texte intégralRaab, J., et M. Schweitzer. Public involvement in integrated resource planning : A study of demand-side management collaboratives. Office of Scientific and Technical Information (OSTI), février 1992. http://dx.doi.org/10.2172/5241653.
Texte intégral