245,599 research outputs found
Improving operating policies of large-scale surface-groundwater systems through stochastic programming
[EN] The management of large-scale water resource systems with surface and groundwater resources requires considering stream-aquifer interactions. Optimization models applied of large-scale systems have either employed deterministic optimization (with perfect foreknowledge of future inflows, which hinders their applicability to real-life operations) or stochastic programming (in which stream-aquifer interaction is often neglected due to the computational burden associated with these methods). In this paper, stream-aquifer interaction is integrated in a stochastic programming framework by combining the Stochastic Dual Dynamic Programming (SDDP) optimization algorithm with the Embedded Multireservoir Model (EMM). The resulting extension of the SDDP algorithm, named Combined Surface-Groundwater SDDP (CSG-SDDP), is able to properly represent the stream-aquifer interaction within stochastic optimization models of large-scale surface-groundwater resources systems. The algorithm is applied to build a hydroeconomic model for the Jucar River Basin (Spain), in which stream-aquifer interactions are essential to the characterization of water resources in the system. Besides the uncertainties regarding the economic characterization of the demand functions, the results show that the economic efficiency of the operating policies under the current system can be improved by better management of groundwater and surface resourcesThe data used in this study was obtained from the references included. This study was partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economia y Competitividad) and FEDER funds. It also received funding from the European Union's Horizon 2020 research and innovation programme under the IMPREX project (grant agreement: 641.811). The authors want to thank the editor, the associated editor and the reviewers for their comments and suggestions in order to increase the quality of the paper. Readers interested in requesting data about the results of the study may send an e-mail to [email protected], H.; Tilmant, A.; Pulido-Velazquez, M. (2017). Improving operating policies of large-scale surface-groundwater systems through stochastic programming. Water Resources Research. 53(2):1407-1423. https://doi.org/10.1002/2016WR019573S1407142353
Integrated Sensor Systems for Vessels of Opportunity, National Oceanographic Centre, Southampton, UK, October 10-12,2006 : workshop proceedings
The use of self-contained, low-maintenance sensor systems installed on commercial vessels is
becoming an important monitoring and scientific tool in many regions around the world. These
systems integrate data from meteorological and water quality sensors with GPS data into a data
stream that is automatically transferred from ship to shore. To begin linking some of this developing
expertise, the Alliance for Coastal Technologies (ACT) and the European Coastal and Ocean
Observing Technology (ECOOT) organized a workshop on this topic in Southampton, United
Kingdom, October 10-12, 2006. The participants included technology users, technology developers,
and shipping representatives. They collaborated to identify sensors currently employed on
integrated systems, users of this data, limitations associated with these systems, and ways to overcome
these limitations. The group also identified additional technologies that could be employed
on future systems and examined whether standard architectures and data protocols for integrated
systems should be established.
Participants at the workshop defined 17 different parameters currently being measured by integrated
systems. They identified that diverse user groups utilize information from these systems
from resource management agencies, such as the Environmental Protection Agency (EPA), to local
tourism groups and educational organizations. Among the limitations identified were instrument
compatibility and interoperability, data quality control and quality assurance, and sensor calibration
andlor maintenance frequency. Standardization of these integrated systems was viewed to be
both advantageous and disadvantageous; while participants believed that standardization could be
beneficial on many levels, they also felt that users may be hesitant to purchase a suite of instruments
from a single manufacturer; and that a "plug and play" system including sensors from multiple
manufactures may be difficult to achieve.
A priority recommendation and conclusion for the general integrated sensor system community
was to provide vessel operators with real-time access to relevant data (e.g., ambient temperature
and salinity to increase efficiency of water treatment systems and meteorological data for increased
vessel safety and operating efficiency) for broader system value. Simplified data displays
are also required for education and public outreach/awareness. Other key recommendations were
to encourage the use of integrated sensor packages within observing systems such as 100s and
EuroGOOS, identify additional customers of sensor system data, and publish results of previous
work in peer-reviewed journals to increase agency and scientific awareness and confidence in the
technology.
Priority recommendations and conclusions for ACT entailed highlighting the value of integrated
sensor systems for vessels of opportunity through articles in the popular press, and marine science. [PDF contains 28 pages
Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management
As users of big data applications expect fresh results, we witness a new breed of stream processing systems (SPS) that are designed to scale to large numbers of cloud-hosted machines. Such systems face new challenges: (i) to benefit from the pay-as-you-go model of cloud computing, they must scale out on demand, acquiring additional virtual machines (VMs) and parallelising operators when the workload increases; (ii) failures are common with deployments on hundreds of VMs - systems must be fault-tolerant with fast recovery times, yet low per-machine overheads. An open question is how to achieve these two goals when stream queries include stateful operators, which must be scaled out and recovered without affecting query results. Our key idea is to expose internal operator state explicitly to the SPS through a set of state management primitives. Based on them, we describe an integrated approach for dynamic scale out and recovery of stateful operators. Externalised operator state is checkpointed periodically by the SPS and backed up to upstream VMs. The SPS identifies individual operator bottlenecks and automatically scales them out by allocating new VMs and partitioning the check-pointed state. At any point, failed operators are recovered by restoring checkpointed state on a new VM and replaying unprocessed tuples. We evaluate this approach with the Linear Road Benchmark on the Amazon EC2 cloud platform and show that it can scale automatically to a load factor of L=350 with 50 VMs, while recovering quickly from failures. Copyright © 2013 ACM
JEERP: Energy Aware Enterprise Resource Planning
Ever increasing energy costs, and saving requirements, especially in enterprise contexts, are pushing the limits of Enterprise Resource Planning to better account energy, with component-level asset granularity. Using an application-oriented approach we discuss the different aspects involved in designing Energy Aware ERPs and we show a prototypical open source implementation based on the Dog Domotic Gateway and the Oratio ER
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Developing Integrated Waste Management Systems: Information Needs and the Role of Locally Based Data
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Effective use of data in waste strategy planning in the UK
Effective waste strategy planning for sustainable and integrated waste management is predicated on high-quality information. However a review of recent local authority waste strategies in England, part of a research project into effective use of data and analysis in waste strategy planning carried out by researchers at the Open University, showed little evidence of being based on thorough analysis. Lack of good data on many aspects of performance restricts what can be achieved in planning better integrated, more sustainable waste management provision. This paper draws from the results of that project and illustrates improvements that could be achieved by using better quality data and analysis to inform decision making. The research explored the use of various types of information and analysis including compositional analysis and establishing diversion rates; scenario building; applications of geographical information systems; understanding and measuring public participation; the use of trials to collect relevant data; and understanding of the effects of recycling schemes on residual waste composition. The general principals and methodologies of each approach are illustrated by examples derived from the authors’ analysis and interpretation of local authority data provided by case study partners, and show how local data can provide relevant and effective local answers
STREAM Journal, Vol. 6, No. 1, pp 1-21. Jan-March 2007
CONTENTS: Approaches to understanding pond-dike systems in Asia: the POND-LIVE project approach, by Dave Little, Marc Verdegem and Roel Bosma. The contribution of fish ponds to nutrient cycling in integrated farming systems, by P.N. Muendo, J.J. Stoorvogel and Marc Verdegem. Improving the contribution of fishfarming to livelihoods in Northeast Thailand, by Chittra Arjinkit, Roel Bosma, Danai Turongrouang. Benefits of pond-dike systems in Bangladesh, by M.S. Kabir, M.A. Wahab and Marc Verdegem. Common carp increases rohu production in farmers ponds, by Mohammad Mustafizur Rahman, Md. Abdul Wahab and Marc C.J. Verdegem. Improving pond-dike farming systems in the Mekong delta, Vietnam; the Can Tho approach, by Dang Kieu Nhan, Le Thanh Duong, Le Thanh Phong, Roel H. Bosma and Marc C.J. Verdegem. Fuzzy pathways for farm development in Vietnam, by Roel H. Bosma, Le Thanh Phong, and Dang Kieu Nhan
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