Relevant bibliographies by topics / Energy and resource consumption

Contents

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

Academic literature on the topic 'Energy and resource consumption'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Energy and resource consumption"

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Kerr, Don. "Energy, resource consumption, and climate change." Canadian Studies in Population 45, no. 1-2 (May 3, 2018): 43. http://dx.doi.org/10.25336/csp29368.

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Population growth, at both the national and global level, will most certainly impact Canada’s climate, and, more broadly, its environment. While Canada’s population has been projected to continue to grow for many decades, what happens elsewhere in terms of population growth will be particularly important to Canada. Although greenhouse gas emissions (GHGs) in Canada have levelled off somewhat over the last decade and a half, global emissions have continued to climb. As a direct result, with increased GHGs in the atmosphere, Canada’s northern climate has already been impacted in a major way with considerable warming, particularly in its most northern forests and Arctic ecosystems.L’accroissement de la population, autant à l’échelle nationale que mondiale, aura certainement un effet sur le climat au Canada et, plus largement, sur son environnement. Selon les projections, la population canadienne devrait continuer à augmenter pendant encore plusieurs décennies. Or, ce qui se passe ailleurs en termes d’accroissement de la population sera particulièrement important pour le Canada. Bien que les émissions de gaz à effet de serre (GES) au Canada se soient nivelées au cours de la dernière décennie et demie, les émissions globales ont cependant continué à grimper. En conséquence directe de cette augmentation de GES dans l’atmosphère, le climat dans le nord du Canada a déjà subi un impact majeur par un réchauffement important, surtout dans les forêts les plus au nord et les écosystèmes arctiques.Mots-clés : population et environnement; climat; utilisation d’énergie; pointe de population
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Shrabanee, Swagatika, and Amiya Kumar Rath. "SDN-cloud: a power aware resource management system for efficient energy optimization." International Journal of Intelligent Unmanned Systems 8, no. 4 (May 15, 2020): 321–43. http://dx.doi.org/10.1108/ijius-07-2019-0032.

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PurposeIn modern cloud services, resource provisioning and allocation are significant for assigning the available resources in efficient way. Resource management in cloud becomes challenging due to high energy consumption at data center (DC), virtual machine (VM) migration, high operational cost and overhead on DC.Design/methodology/approachIn this paper, the authors proposed software-defined networking (SDN)-enabled cloud for resource management to reduce energy consumption in DC. SDN-cloud comprises four phases: (1) user authentication, (2) service-level agreement (SLA) constraints, (3) cloud interceder and (4) SDN-controller.FindingsResource management is significant for reducing power consumption in CDs that is based on scheduling, VM placement, with Quality of Service (QoS) requirements.Research limitations/implicationsThe main goal is to utilize the resources energy effectively for reducing power consumption in cloud environment. This method effectively increases the user service rate and reduces the unnecessary migration process.Originality/valueAs a result, the authors show a significant reduction in energy consumption by 20 KWh as well as over 60% power consumption in the presence of 500 VMs. In future, the authors have planned to concentrate the issues on resource failure and also SLA violation rate with respect to number of resources will be decreased.
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Casazza, Marco, Jingyan Xue, Shupan Du, Gengyuan Liu, and Sergio Ulgiati. "Simulations of scenarios for urban household water and energy consumption." PLOS ONE 16, no. 4 (April 7, 2021): e0249781. http://dx.doi.org/10.1371/journal.pone.0249781.

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The expansion of cities and their impacts currently constitutes a challenge for the achievement of sustainable development goals (SDGs). In this respect, assessments of resource consumption and the delivery of appropriate policies to support resource conservation are of paramount importance. Previous works in the literature have focused on one specific resource (e.g., water, energy, food) at the household level, while others have analysed the inter-relations among different resources (i.e., the nexus approach) at larger spatial scales (e.g., urban level). Moreover, household behavioural attitudes are generally excluded while assessing resource consumption scenarios. This work overcomes previous limitations by proposing a causal-loop structure derived from the literature, from which simulations of different scenarios can be generated that consider the nexus between food, energy and water at the household level. These simulations can provide alternative scenarios to assess the impacts of monetary policies as well as education and communication actions on the enhancement of resource savings and consider both their current use and household preferences. The metropolitan area of Napoli was chosen as the testbed area for the simulations. The results, in relation to the testbed, proved that communication actions would be most appropriate to increase the level of resource savings. The business-as-usual scenario was especially sensitive to variations in individual preferences towards pro-environmental behaviours and showed their higher impacts on the results. Improvements of this method and its derived scenarios in the context of the urban planning process could support the implementation of informed policies towards the conservation of key resources and promotion of sustainable citizen behaviour.
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Chen, I.-Chun, Kuang-Ly Cheng, Hwong-Wen Ma, and Cathy Chang-Wei Hung. "Identifying Spatial Driving Factors of Energy and Water Consumption in the Context of Urban Transformation." Sustainability 13, no. 19 (September 22, 2021): 10503. http://dx.doi.org/10.3390/su131910503.

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Urban energy and water consumption varies substantially across spatial and temporal scales, which can be attributed to changes of socio-economic variables, especially for a city undergoing urban transformation. Understanding these variations in variables related to resource consumptions would be beneficial to regional resource utilization planning and policy implementation. A geographically weighted regression method with modified procedures was used to explore and visualize the relationships between socio-economic factors and spatial non-stationarity of urban resource consumption to enhance the reliability of predicted results, taking Taichung city with 29 districts as an example. The results indicate that there is a strong positive correlation between socio-economic context and domestic resource consumption, but that there are relatively weak correlations for industrial and agricultural resource consumption. In 2015, domestic water and energy consumption was driven by the number of enterprises followed by population and average income level (depending on the target sectors). Domestic resource consumption is projected to increase by approximately 84% between 2015 and 2050. Again, the number of enterprises outperforms other factors to be the dominant variable responsible for the increase in resource consumption. Spatial regression analysis of non-stationarity resource consumption and its associated variables offers useful information that is helpful for targeting hotspots of dominant resource consumers and intervention measures.
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Gnedoy, N., S. Dubovskoy, and M. Kulik. "Economic, energy and ecological aspects of energy resource consumption in Ukraine." International Journal of Global Energy Issues 19, no. 2/3 (2003): 182. http://dx.doi.org/10.1504/ijgei.2003.002390.

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Mao, Li, De Yu Qi, Wei Wei Lin, Bo Liu, and Ye Da Li. "An Energy-Efficient Resource Scheduling Algorithm for Cloud Computing based on Resource Equivalence Optimization." International Journal of Grid and High Performance Computing 8, no. 2 (April 2016): 43–57. http://dx.doi.org/10.4018/ijghpc.2016040103.

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With the rapid growth of energy consumption in global data centers and IT systems, energy optimization has become an important issue to be solved in cloud data center. By introducing heterogeneous energy constraints of heterogeneous physical servers in cloud computing, an energy-efficient resource scheduling model for heterogeneous physical servers based on constraint satisfaction problems is presented. The method of model solving based on resource equivalence optimization is proposed, in which the resources in the same class are pruning treatment when allocating resource so as to reduce the solution space of the resource allocation model and speed up the model solution. Experimental results show that, compared with DynamicPower and MinPM, the proposed algorithm (EqPower) not only improves the performance of resource allocation, but also reduces energy consumption of cloud data center.
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Dewangan, Bhupesh Kumar, Amit Agarwal, Venkatadri M., and Ashutosh Pasricha. "Energy-Aware Autonomic Resource Scheduling Framework for Cloud." International Journal of Mathematical, Engineering and Management Sciences 4, no. 1 (February 1, 2019): 41–55. http://dx.doi.org/10.33889/ijmems.2019.4.1-004.

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Cloud computing is a platform where services are provided through the internet either free of cost or rent basis. Many cloud service providers (CSP) offer cloud services on the rental basis. Due to increasing demand for cloud services, the existing infrastructure needs to be scale. However, the scaling comes at the cost of heavy energy consumption due to the inclusion of a number of data centers, and servers. The extraneous power consumption affects the operating costs, which in turn, affects its users. In addition, CO2 emissions affect the environment as well. Moreover, inadequate allocation of resources like servers, data centers, and virtual machines increases operational costs. This may ultimately lead to customer distraction from the cloud service. In all, an optimal usage of the resources is required. This paper proposes to calculate different multi-objective functions to find the optimal solution for resource utilization and their allocation through an improved Antlion (ALO) algorithm. The proposed method simulated in cloudsim environments, and compute energy consumption for different workloads quantity and it increases the performance of different multi-objectives functions to maximize the resource utilization. It compared with existing frameworks and experiment results shows that the proposed framework performs utmost.
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Alcarria, Ramon, Borja Bordel, Tomás Robles, Diego Martín, and Miguel-Ángel Manso-Callejo. "A Blockchain-Based Authorization System for Trustworthy Resource Monitoring and Trading in Smart Communities." Sensors 18, no. 10 (October 20, 2018): 3561. http://dx.doi.org/10.3390/s18103561.

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Resource consumption in residential areas requires novel contributions in the field of consumer information management and collaborative mechanisms for the exchange of resources, in order to optimize the overall consumption of the community. We propose an authorization system to facilitate access to consumer information and resource trading, based on blockchain technology. Our proposal is oriented to the Smart communities, an evolution of Community Energy Management Systems, in which communities are involved in the monitoring and coordination of resource consumption. The proposed environment allows a more reliable management of monitoring and authorization functions, with secure data access and storage and delegation of controller functions among householders. We provide the definition of virtual assets for energy and water resource sharing as an auction, which encourages the optimization of global consumption and saves resources. The proposed solution is implemented and validated in application scenarios that demonstrate the suitability of the defined consensus mechanism, trustworthiness in the level of provided security for resource monitoring and delegation and reduction on resource consumption by the resource trading contribution.
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Ravi, G., and T. Sujithamani. "Autonomic Resource Management and Energy Consumption in Cloud Environment." International Journal of Computer Applications 129, no. 3 (November 17, 2015): 8–11. http://dx.doi.org/10.5120/ijca2015906778.

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Raileanu, Silviu, Florin Anton, Alexandru Iatan, Theodor Borangiu, Silvia Anton, and Octavian Morariu. "Resource scheduling based on energy consumption for sustainable manufacturing." Journal of Intelligent Manufacturing 28, no. 7 (August 20, 2015): 1519–30. http://dx.doi.org/10.1007/s10845-015-1142-5.

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Dissertations / Theses on the topic "Energy and resource consumption"

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Michaelis, Peter. "Reducing resource consumption in the UK steel sector : an exergy analysis." Thesis, University of Surrey, 1998. http://epubs.surrey.ac.uk/842698/.

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This study has investigated the use of exergy analysis when applied to the UK steel sector. The aim has been twofold: to assess whether exergy analysis provides greater insight into physical processes at this level than conventional thermodynamic analyses; and whether it can be used to identify ways that this sector has reduced its impact on the environment in the past, and how this might continue in the future. An overview of the issues surrounding resource consumption and waste generation and their relationship to the steel sector are given [Chapter 1]. The theory behind exergy analysis is then reviewed and its relevance to reducing resource use and waste minimisation examined [Chapter 2]. An exergy analysis was performed on all the processes within the steel sector [Chapters 3 & 4] and the reasons for thermodynamic inefficiencies discussed. Based on these analyses, exergy analysis was found to be superior to other methods in describing some, but not all, processes when compared with two forms of energy analysis [Chapter 5]. This is due to fact that exergy includes an account of entropy which quantifies thermodynamic quality. It was shown that reducing the exergy consumption of the steel sector leads to a reduction in resource use and to some extent will lead to a reduction in the emission of pollutants. Two different systems which could represent the UK steel sector were investigated to determine which best fitted the aims of the study [Chapter 6]. The first system was based on all processes within the UK which were linked to the use of steel; the second was based on all processes, regardless of location, which were linked to the use of steel in the UK. It was found that for the steel sector at least, there was little difference in the exergy consumption of each system, although these were structurally quite different. Finally a system was chosen to represent the UK steel sector which best suited the needs of the study. This system was used to examine the evolution of the steel sector from 1954-1994, detailing all the main steel and scrap flows, the exergy consumption in; mining, transport, steel production and scrap processing, the effects of trade and the role of manufacture and product use in generating scrap [Chapter 7]. It was found that the exergy consumption of the UK steel sector has fallen twofold in this time period, indicating a large reduction in resource consumption. Based on past evolution, scenarios for possible futures of the steel sector were constructed [Chapter 8]. These showed that from 1994 to 2019 substantial reductions in the exergy consumption of the sector are possible (between 15% and 72% of 1994 levels by 2019) through changes to: the overall demand for steel goods, the technology of steel production and the mix of steel production methods.
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Liu, Jiashang. "Resource Allocation and Energy Management in Green Network Systems." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587577356321898.

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Ackah, Ishmael. "Essays on energy consumption and oil resource management in oil producing African countries." Thesis, University of Portsmouth, 2015. https://researchportal.port.ac.uk/portal/en/theses/essays-on-energy-consumption-and-oil-resource-management-in-oil-producing-african-countries(5703d6fa-58c2-40fc-a130-c67da933bf04).html.

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In September 2011, the UN General Secretary declared his vision of making modern energy accessible to all by 2030. Unfortunately, less than 50% of the population of Sub-Saharan Africa have access to modern forms of energy. This implies that Africa requires sustained investment in the energy sector. In order to provide investment guide and policy recommendations, this thesis seeks to investigate the determinants of renewable energy, energy efficiency practices and natural gas demand in oil producing African countries. The choice of these types of fuel is dictated by the fact that, renewable energy, energy efficiency and natural gas have been considered the solution to the hydra-headed problems of energy security, energy access and climate change in Africa. The thesis contributes to the energy economics literature in four main ways. First, the thesis applies spatial analysis to the issue of ‗oil curse‘ which has often been associated with oil producing African countries since investments in energy will require finance which can be provided by proceeds from oil resources. Second, the effect of natural resource depletion and energy-related carbon emissions on renewable energy consumption is examined. Third, the natural gas consumption behavior of oil producing African countries is examined. Finally, the Product Generational Dematerialisation (PGD) is applied to the energy efficiency of fossil fuels and electricity consumption in Ghana. The thesis finds among other things that both economic and technical factors affect the demand for natural gas and renewable energy. Further, the results reveal that the consumption of both fossil fuel and renewables have not been efficient. Finally, the thesis confirms the oil curse hypothesis. However, how conducive the investment climate in a particular country has positive bearings on neighbouring countries. Whilst the study seeks to recommend for more investment into energy supply and demand, attention should be given to three factors: availability, the environment and finance. Whereas, renewable energy sources, natural gas and efficiency abound in Africa and are environmentally friendly, finance may be a major hindrance to investments. Therefore, the sixth chapter of this thesis, examines how oil resources are managed so that it can help fund investments in energy. The chapters are therefore linked by the need for oil producing African countries to harness the finances to invest in available and clean sources of energy. The thesis recommends that oil producing Africa should open their economies for international trade, invest in commercial sources of renewable energy, build strong accountability institutions, channel oil revenues into productive sectors and educate the public on energy efficiency not just electricity efficiency.
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Chen, Ting. "Energy-Efficient Resource Allocation in OFDMA Systems." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-98683.

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In this thesis, a resource allocation problem in OFDMA is studied for the energy efficiency of wireless network. The objective is to minimize the total energy consumption which includes transmission energy consumption, and circuit energy consumption at both transmitter and receiver with required per user’s rate constraint. For problem solution, a heuristic algorithm with low computational complexity and suboptimal solution is proposed, developed in two steps with an increasing order of complexity. Besides, a bounding scheme based on model linearization of formulated nonlinear system model is also proposed to give lower and upper bounds for both small- and large-scale OFDMA network for further algorithm performance evaluation, while the implemented exhaustive search is only capable to provide the optimal solution for small-scale instance for algorithm performance evaluation. Numerical results show that the proposal heuristic algorithm can achieve near-optimal performance with applicable computational complexity even for large-scale networks, and that the bounds from the bounding scheme are very tight for both small- and large-scale OFDMA networks.
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Leenes, Popkje Winfrieda. "Natural resource use for food land, water and energy in production and consumption systems /." [S.l. : [Groningen : s.n.] ; University Library Groningen] [Host], 2006. http://irs.ub.rug.nl/ppn/298187221.

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Muchawaya, Davidzo. "Energy consumption patterns in rural Zimbabwe with special reference to the role of electricity as a development incentive [electronic resource] /." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-09252008-151526/.

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Stellmann, Lars. "Germany's energy demand and supply until 2020 : implications for Germany's foreign energy policy." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FStellmann.pdf.

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Thesis (M.A. in National Security Affairs)--Naval Postgraduate School, June 2003.
Thesis advisor(s): Robert E. Looney, Maria Rasmussen. Includes bibliographical references (p. 55-57). Also available online.
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Staples, Jacob. "Resource banking an energy-efficient, run-time adaptive processor design technique." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5047.

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From the earliest and simplest scalar computation engines to modern superscalar out-of-order processors, the evolution of computational machinery during the past century has largely been driven by a single goal: performance. In today's world of cheap, billion-plus transistor count processors and with an exploding market in mobile computing, a design landscape has emerged where energy efficiency, arguably more than any other single metric, determines the viability of a processor for a given application. The historical emphasis on performance has left modern processors bloated and over provisioned for everyday tasks in the hope that during computationally intensive periods some performance improvement will be observed. This work explores an energy-efficient processor design technique that ensures even a highly over provisioned out-of-order processor has only as many of its computational resources active as it requires for efficient computation at any given time. Specifically, this paper examines the feasibility of a dynamically banked register file and reorder buffer with variable banking policies that enable unused rename registers or reorder buffer entries to be voltage gated (turned off) during execution to save power. The impact of bank placement, turn-off and turn-on policies as well as rail stabilization latencies for this approach are explored for high-performance desktop and server designs as well as low-power mobile processors.
ID: 030423232; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.Cp.E.)--University of Central Florida, 2011.; Includes bibliographical references (p. 77-79).
M.S.Cp.E.
Masters
Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Engineering
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Alnowiser, Abdulaziz Mohammed. "TOWARD ENERGY-EFFICIENT SCHEDULING USING WEIGHTED ROUND-ROBIN AND VM REUSE." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/theses/1303.

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AN ABSTRACT OF THE THESIS OF Abdulaziz M. AlNowiser, for the Master of Science degree in Computer Science, presented on November 1, 2013, at Southern Illinois University Carbondale. TITLE: TOWARD ENERGY-EFFICIENT SCHEDULING USING WEIGHTED ROUND- ROBIN AND VM REUSE MAJOR PROFESSOR: Dr. Michelle M. Zhu In recent years, the rapid evolving Cloud Computing technologies multiply challenges such as minimizing power consumption and meeting Quality-of-Services (QoS) requirements in the presence of heavy workloads from a large number of users using shared computing resources. Powering a middle-sized data center normally consumes 80,000kW power every year and computer servers consume around .5% of the global power [1]. Statistics for 5000 production servers over a six-month period show that only 10-50% of the total capacity has been effectively used, and a large portion of the resources is actually wasted. In order to address the skyrocket energy cost from the high level resource management aspect, we propose an energy efficient job scheduling approach based on a modified version of Weighted Round Robin scheduler that incorporates VMs reuse and live VM migration without compromising the Service Level Agreement (SLA). The Weighted Round Robin scheduler can monitor the running VMs status for possible VM sharing for job consolidation or migration. In addition, the VMs utilization rate is observed to start live migration from the over-utilizing Processing Element (PE) to under-utilized PEs or to the hibernated PEs by sending WOL (Wake-On-LAN) signal to activate them. The simulation experiments are conducted under the CloudReports environment based on open source CloudSim simulator. The comparisons with other similar scheduling algorithms demonstrate that our enhanced Weighted Round Robin algorithm (EWRR) can achieve considerable better performance in terms of energy consumption and resource utilization rate.
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Johansson, Susanne. "The Swedish foodprint : an agroecological study of food consumption /." Uppsala : Dept. of Ecology and Crop Production Science, Swedish University of Agricultural Sciences, 2005. http://epsilon.slu.se/200556.pdf.

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Books on the topic "Energy and resource consumption"

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Rainery, Richard. Alaska's public energy resources: Distribution of benefits of thermal energy and electric power energy resource consumption. [Juneau?]: Rural Research Agency, Alaska State Senate, 1985.

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Spilsbury, Richard. Energy resources. London: Wayland, 2009.

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Deborah, Ross. Puget Sound fuel blind integrated resource planning project: Final report. Olympia, WA (925 Plum St. S.E., Bldg 4, P.O. Box 43165, Olympia 98504-3165): Washington State Energy Office, 1994.

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Jakab, Cheryl. Energy use. North Mankato, MN: Smart Apple Media, 2007.

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Yount, Lisa. Energy supply. New York: Facts on File, Inc., 2005.

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Bendavid-Val, Avrom. More with less: Managing Energy and Resource Efficient Cities. Washington, D.C: Bureau for Science and Technology, Agency for International Development, 1987.

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Administration, Bonneville Power. 1990 resource program. [Portland, Or.]: Bonneville Power Administration, 1990.

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Education, E2: Environment &. Energy conservation: A student audit of resource use. Menlo Park, Ca: Dale Seymour, 1998.

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Net-energy analysis and the energy requirements of energy systems. New York: Praeger, 1988.

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Bank, Asian Development. Energy statistics in Asia and the Pacific, 1990-2006. Mandaluyong City, Metro Manila, Philippines: Asian Development Bank, 2009.

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Book chapters on the topic "Energy and resource consumption"

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Wiser, Wendell H. "Fossil Fuel Reserves Versus Consumption." In Energy Resources, 173–82. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1226-3_7.

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de Barros Correia, Tiago, Gabriel Moreira Pinto, and Vitor Hugo da Silva Oliveira. "Auction Design to Procure Energy Efficiency Measures as Distributed Energy Resources." In Sustainable Consumption, 409–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16985-5_23.

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Sarpong, Gideon, and Veera Gnaneswar Gude. "Energy Consumption and Recovery in Wastewater Treatment Systems." In Resource Recovery from Wastewater, 91–123. Includes bibliographical references and index.: Apple Academic Press, 2021. http://dx.doi.org/10.1201/9781003055501-4.

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Frisch, Jean-Romain. "Consumption Projections." In Future Stresses for Energy Resources, 3–21. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4209-7_1.

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Povoa, Lucas Venezian, Cesar Marcondes, and Hermes Senger. "Modeling Energy Consumption Based on Resource Utilization." In Computational Science and Its Applications – ICCSA 2019, 225–40. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24289-3_18.

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Dagiliūtė, Renata. "Material and Energy Consumption in Lithuania: Towards Sustainability." In International Economics of Resource Efficiency, 215–32. Heidelberg: Physica-Verlag HD, 2011. http://dx.doi.org/10.1007/978-3-7908-2601-2_10.

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Kersten, Rody, Paolo Parisen Toldin, Bernard van Gastel, and Marko van Eekelen. "A Hoare Logic for Energy Consumption Analysis." In Foundational and Practical Aspects of Resource Analysis, 93–109. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12466-7_6.

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Brown, Charles E. "USA Oil and Natural Gas Consumption Forecasts." In World Energy Resources, 295–308. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56342-3_19.

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Mastorakis, George, Spyros Panagiotakis, Kostas Kapetanakis, Giorgos Dagalakis, Constandinos X. Mavromoustakis, Athina Bourdena, and Evangelos Pallis. "Energy and Resource Consumption Evaluation of Mobile Cognitive Radio Devices." In Resource Management in Mobile Computing Environments, 359–88. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06704-9_16.

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Beyer, Dirk, and Philipp Wendler. "CPU Energy Meter: A Tool for Energy-Aware Algorithms Engineering." In Tools and Algorithms for the Construction and Analysis of Systems, 126–33. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45237-7_8.

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Abstract Verification algorithms are among the most resource-intensive computation tasks. Saving energy is important for our living environment and to save cost in data centers. Yet, researchers compare the efficiency of algorithms still in terms of consumption of CPU time (or even wall time). Perhaps one reason for this is that measuring energy consumption of computational processes is not as convenient as measuring the consumed time and there is no sufficient tool support. To close this gap, we contribute CPU Energy Meter, a small tool that takes care of reading the energy values that Intel CPUs track inside the chip. In order to make energy measurements as easy as possible, we integrated CPU Energy Meter into BenchExec, a benchmarking tool that is already used by many researchers and competitions in the domain of formal methods. As evidence for usefulness, we explored the energy consumption of some state-of-the-art verifiers and report some interesting insights, for example, that energy consumption is not necessarily correlated with CPU time.
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Conference papers on the topic "Energy and resource consumption"

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Silva, Edgar M., Pedro Malo, and Michele Albano. "Energy consumption awareness for resource-constrained devices." In 2016 European Conference on Networks and Communications (EuCNC). IEEE, 2016. http://dx.doi.org/10.1109/eucnc.2016.7561008.

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"RESOURCE SUBSTITUTION WITH COMPONENTS - Optimizing Energy Consumption." In 3rd International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001879000280035.

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Shah, Amip, and Kiara Corrigan. "Extending Lifecycle Exergy Analysis Beyond Resource Consumption." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90082.

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In this paper, we explore a reduced-order framework to predict the sustainability of a given system. The approach combines concepts from economic theory, thermodynamics, and the environmental sciences into a simple scheme that allows evaluation of system sustainability in terms of a small number of variables. The underlying hypothesis behind the work is that sustainability can be correlated to reversibility, and therefore should bear a relationship with transitions from an initial benign state. We propose evaluation along three dimensions: (i) physical; (ii) economic; and (iii) social. The measure of physical damage follows from the second law of thermodynamics, and specifically we show when and how second-law derived metrics (such as lifetime exergy consumption) can be extended to capture additional impacts. The measure of economic impact is derived by correlating physical transformations of objects with their relative economic value, specifically through use of input-output models that have been previously published in the literature. Lastly, we explore capturing social value through a proxy of indexed measures that correlate to the notion of a ‘social entropy’, which is suggested as an approximation for the deviation of society from a general state of well-being. We propose unifying all three of these approaches through a generalized framework, and thus suggest a simple but broad ‘sustainability performance’ metric. The paper concludes by discussing the challenges associated with widespread implementation, validation, and completeness of such a framework.
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Jagroep, Erik, Jan Martijn Werf, van der, Jordy Broekman, Leen Blom, Rob Vliet, van, and Sjaak Brinkkemper. "A Resource Utilization Score for Software Energy Consumption." In ICT for Sustainability 2016. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/ict4s-16.2016.3.

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WU, Jia, Liu Chao, Wei CUI, and Wei LIU. "The Resource Scheduling Algorithm of Energy Consumption Optimization." In 2020 IEEE 2nd International Conference on Power Data Science (ICPDS). IEEE, 2020. http://dx.doi.org/10.1109/icpds51559.2020.9332481.

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Olanrewaju, Oludolapo A., Josiah L. Munda, and Adisa A. Jimoh. "Understanding the Impacts of GDP and Population in South Africa's Energy Consumption." In Environment and Water Resource Management. Calgary,AB,Canada: ACTAPRESS, 2014. http://dx.doi.org/10.2316/p.2014.813-016.

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Philippot, Olivier, Alain Anglade, and Thierry Leboucq. "Characterization of the energy consumption of websites: Impact of website implementation on resource consumption." In ICT for Sustainability 2014 (ICT4S-14). Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/ict4s-14.2014.21.

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Lynar, Timothy M., Ric D. Herbert, Simon, and William J. Chivers. "Reducing grid energy consumption through choice of resource allocation method." In Distributed Processing, Workshops and Phd Forum (IPDPSW). IEEE, 2010. http://dx.doi.org/10.1109/ipdpsw.2010.5470911.

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Khan, M., R. S. Alhumaima, and H. S. Al-Raweshidy. "Reducing energy consumption by dynamic resource allocation in C-RAN." In 2015 European Conference on Networks and Communications (EuCNC). IEEE, 2015. http://dx.doi.org/10.1109/eucnc.2015.7194062.

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Qu, Li-juan, Li-nan Lei, Wei Chen, and Jin-yuan Qian. "Energy Consumption Prediction of University Buildings in China and Strategies for Energy Efficiency Management." In ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/es2015-49071.

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In 2007, Chinese Ministry of Education (MOE) and Ministry of Housing & Urban-Rural Development (MOHURD) carried out the Campus Resource Conservation Actions, in order to take full use of resources and to improve the energy efficiency. However, due to the large amounts of universities, the total energy consumption and the energy efficiency situation have no objective statistics. Taking modeling the energy consumption of university buildings as the starting point, this paper analyzes the characteristics of university buildings in China. Then, we do the prediction, trend and potential analysis of the total energy consumption in 2020. In addition, four strategies for energy efficiency management are carried out, which might be helpful for all the university managers and related departments.
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Reports on the topic "Energy and resource consumption"

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Baker, Justin S., George Van Houtven, Yongxia Cai, Fekadu Moreda, Chris Wade, Candise Henry, Jennifer Hoponick Redmon, and A. J. Kondash. A Hydro-Economic Methodology for the Food-Energy-Water Nexus: Valuation and Optimization of Water Resources. RTI Press, May 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0044.2105.

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Growing global water stress caused by the combined effects of growing populations, increasing economic development, and climate change elevates the importance of managing and allocating water resources in ways that are economically efficient and that account for interdependencies between food production, energy generation, and water networks—often referred to as the “food-energy-water (FEW) nexus.” To support these objectives, this report outlines a replicable hydro-economic methodology for assessing the value of water resources in alternative uses across the FEW nexus–including for agriculture, energy production, and human consumption—and maximizing the benefits of these resources through optimization analysis. The report’s goal is to define the core elements of an integrated systems-based modeling approach that is generalizable, flexible, and geographically portable for a range of FEW nexus applications. The report includes a detailed conceptual framework for assessing the economic value of water across the FEW nexus and a modeling framework that explicitly represents the connections and feedbacks between hydrologic systems (e.g., river and stream networks) and economic systems (e.g., food and energy production). The modeling components are described with examples from existing studies and applications. The report concludes with a discussion of current limitations and potential extensions of the hydro-economic methodology.
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Zankovskij, S. S. THE PROBLEM OF QUALIFICATION OF RECOVERY FROM A CONSUMER ENERGY RESOURCES IN THE MAXIMUM VOLUME WITH RUNNING OUT ELECTRICITY CONSUMPTION AS A PROPERTY MEASURE LIABILITY. Modern Science., 2020. http://dx.doi.org/10.18411/0131-5226-2020-60001.

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Guix, M., and G. Bronevetsky. Active Measurement of Memory Resource Consumption. Office of Scientific and Technical Information (OSTI), May 2013. http://dx.doi.org/10.2172/1080399.

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Author, Not Given. Household vehicles energy consumption, 1988. Office of Scientific and Technical Information (OSTI), February 1990. http://dx.doi.org/10.2172/7154211.

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Flanagan, D. M., H. J. Tsao, R. L. Jr Schmoyer, and J. M. MacDonald. Nonresidential Building Energy Consumption Survey (NBECS). Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6393534.

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Author, Not Given. Household energy consumption and expenditures 1987. Office of Scientific and Technical Information (OSTI), January 1990. http://dx.doi.org/10.2172/5127577.

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Yourtchenko, A., and L. Colitti. Reducing Energy Consumption of Router Advertisements. RFC Editor, February 2016. http://dx.doi.org/10.17487/rfc7772.

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Jerald Brevick, clark Mount-Campbell, and Carroll Mobley. Energy Consumption of Die Casting Operations. Office of Scientific and Technical Information (OSTI), March 2004. http://dx.doi.org/10.2172/822409.

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Szydlowski, R. F., and W. D. Jr Chvala. Energy consumption of personal computer workstations. Office of Scientific and Technical Information (OSTI), February 1994. http://dx.doi.org/10.2172/10134947.

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Leslie Roberts and Michael Hagood. Western Energy Corridor -- Energy Resource Report. Office of Scientific and Technical Information (OSTI), June 2011. http://dx.doi.org/10.2172/1027917.

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You might also be interested in the extended bibliographies on the topic 'Energy and resource consumption' for particular source types:
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