Quality Of Results Research Articles

Ant-colony optimization of pumping schedule to minimize the energy cost using variable-speed pumps in water distribution networks

Despite considerable pumping energy costs in pumping stations of water distribution networks (WDNs), there are not many studies offering pumping schedule in order to optimize pumping energy costs regarding the WDN design. This paper aims to focus on the optimization of the WDN pumping station schedule by means of variable-speed pump (VSP) and using a combination of the ant system iteration best algorithm (ASib) and EPANET2.0. In fact, the VSP is implemented to increase the flexibility of pumping station and obtain the pumping schedule with optimized energy cost as the water demand changes during a day. Given that vast search space in optimization process leads to a decrease in the quality of final results, in this study, two heuristic methods coupled with ASib are proposed in order to reduce the number of feasible solutions in the search space. The optimization results showed that the proposed heuristic approaches have considerably improved the quality of solutions produced by the ASib and enhanced the navigation of the optimization process. The results of optimization for the Richmond network, similar to the genetic algorithm (GA), showed that the ASib was capable of improving pumping energy costs. Besides, using the variable-speed pump in an optimized pump scheduling could lead to greater savings (about 10%) in pumping energy costs compared with the single-speed pump (SSP).

PS2-39: Key Challenges and Decisions in the Development of HMO Death Data

BackgroundThe mortality status of an HMO?s members, whether a person is alive or dead, is critically important to health care research. The uses of mortality status include determination of causes of death, death rates, and for selection of study cohorts. Unlike other clinical activity and health statuses, mortality status cannot be determined solely with a health plan?s internal data, even for well-defined populations, because health plan members often die outside of the plan?s care delivery and claims payment systems. For such members, determination of mortality status and date of death requires linkage of health plan data to external sources of mortality data, such as state death certificate or federal Social Security data. This person-level statistical linkage is a complex, multi-step process that involves many decisions, assumptions, and choosing of priorities. Even when death data from internal systems is available, internal data sources can disagree, likewise requiring complex decisions to determine a member?s ?true? mortality status.MethodsThis presentation highlights key challenges and decisions points in the development of death data logic at Kaiser Permanente Northern California (KPNC).ResultsKey decisions in KPNC?s death data logic include: handling internal membership data with conflicting personal identifiers, e.g., multiple Social Security Numbers associated with a single Medical Record Number; ranking, grading, and selecting from multiple matches between internal and external data; finding members with multiple MRNs; using utilization contact dates and membership activity dates to evaluate death records, judging reliability of internal health plan data, setting thresholds and criteria for confidence scoring, selecting between multiple possible dates of death, chart validation of final death data.ConclusionsThe development of death data logic at KPNC is a complex process that requires intricate decisions, careful analysis, and a higher degree of discretionary judgment than is typical of building other data areas. The quality of final results depends upon validation and iterative improvements to the process.

Study of electrical resistivity: variability assessment on two concretes: protocol study in laboratory and assessment on site

This article presents electrical resistivity measurement on concrete. The first part presents the study of a lighter protocol for measuring electrical resistivity, allowing investigations of a large number of specimens, without degradation of the quality of final results. The second part is based on measurements made on two concretes cast regularly during one year each, on two sites. Measurements done to assess the different variability sources distinguish variability linked to the measurement of those related to the material. The third part of the article compares the laboratory measurements to those made on site. Finally, all the results reflected the interests of the resistivity measurement because of low variability obtained, and consistency between results. Les travaux présentés portent sur la mesure de résistivité électrique sur les bétons. Une première partie présente l’étude d’un protocole de mesure électrique allégé, qui a permis de traiter un grand nombre d’éprouvette sans que la qualité finale des résultats n’en soit altérée. La seconde partie repose sur les mesures faites sur deux bétons coulés régulièrement sur deux chantiers durant une année. Les mesures réalisées permettent d’évaluer les différentes sources de variabilité des résistivités en distinguant les variabilités inhérentes à la mesure de celles liées au matériau. Une troisième partie de l’article confronte les mesures en laboratoires à celles réalisées sur site. L’ensemble des résultats traduit finalement l’intérêt de la mesure de résistivité du fait des faibles niveaux de variabilités obtenus, et de leur cohérence entre les différents résultats.

Employing Adaptive Particle Swarm Optimization Algorithm for Parameter Estimation of an Exciter Machine

Winding inductances of an exciter machine of brushless generator normally consist of nonsinusoidal terms versus rotor position angle, so evaluations of the inductances necessitate detailed modeling and complicated parameter identification procedures. In this paper, an adaptive particle swarm optimization (APSO), which is a novel heuristic computation technique, is proposed to identify parameters of an exciter machine. The proposed approach evaluates the model parameters just knowing the main field impedance, measured exciter field voltage and current. APSO is employed to solve the optimization problem of minimizing the difference between output quantities (exciter field current) of the model and real systems. Two modifications are incorporated into the conventional particle swarm optimization (PSO) scheme that prevents local convergence and provides excellent quality of final result. Performance of the proposed APSO is compared with those of the real-coded genetic algorithm (GA) and PSO with linearly decreasing inertia weight (LDW-PSO), in terms of the parameter accuracy and convergence speed. Simulation results illustrated in the paper show that the proposed APSO is more successful in comparison with LDW-PSO and GA.

Parallel Environment with High Accuracy for Resolution of Numerical Problems

In this paper we describe a high performance environment, like cluster computers, with high accuracy obtained by use of C-XSC library. The C-XSC library is a (free) C++ class library for scientific computing for the development of numerical algorithms delivering highly accurate and automatically verified results by use of the interval arithmetic. These calculus in high accuracy must be available for some basic arithmetic operations, mainly the operations that accomplish the summation and dot product. Because of these aspects, we wish to use the high performance through a cluster environment where we have several nodes executing tasks or calculus. The communication will be done by message passing using the MPI communication library. To obtain the high accuracy in this environment extensions or changes in the parallel programs had done to guarantee that the quality of final result done on cluster, where several nodes collaborate for the final result of the calculus, maintain the same result quality obtained in one sequential high accuracy environment. To validate the environment developed in this work we done basic tests about the dot product, the matrix multiplications, the implementation of interval solvers for banded and dense matrices and the implementation of some numeric methods to solve linear systems with the high accuracy characteristic (some of the methods implemented are used in real life applications like hydrodynamic, agriculture and power electric systems). With these tests we done analysis and comparisons about the performance and accuracy obtained with and without the use of C-XSC library in sequential and parallel programs. With the implementation of these routines and methods will be open a large research field about the study of real life applications that need during their resolution (or in part of their resolution) to calculate arithmetic operations with more accuracy than the accuracy obtained by the traditional computational tools. Our software run on labtec (UFRGS) and Colorado (UPF) clusters. Nowadays we are working in the implementation of parallel versions of programs to solve linear systems (without and with high accuracy) and the optimization of C-XSC library on cluster computers.

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

Computing with data non-determinism: Wait time management for peer-to-peer systems

One of the unusual challenges faced by peer-to-peer algorithms as opposed to classical distributed algorithms is that these have to compute with data non-determinism where there is no guarantee that data from a particular node will be delivered in time or delivered at all. Each distributed component not only has to work in such environment, but also has to decide how long to wait for peers to respond. A large wait can inordinately delay entire computation. A smaller wait can reduce the coverage of the algorithm and drastically degenerate the quality of final result produced. In this paper, we investigate a set of wait management schemas which tries to minimize the overall completion time and maximize the quality of solution. We present detail analyses of the schemas for various scenarios including large power law networks and forms of non-responsiveness. The work promises dramatic improvement in peer-to-peer search and other computations.

Programming ad-hoc networks of mobile and resource-constrained devices

Ad-hoc networks of mobile devices such as smart phones and PDAs represent a new and exciting distributed system architecture. Building distributed applications on such an architecture poses new design challenges in programming models, languages, compilers, and runtime systems. This paper discusses SpatialViews, a high-level language designed for programming mobile devices connected through a wireless ad-hoc network. SpatialViews allows specification of virtual networks with nodes providing desired services and residing in interesting spaces. These nodes are discovered dynamically with user-specified time constraints and quality of result (QoR). The programming model supports "best-effort" semantics, i.e., different executions of the same program may result in "correct" answers of different quality. It is the responsibility of the compiler and runtime system to produce a high-quality answer for the particular network and resource conditions encountered during program execution. Four applications, which exercise different features of the SpatialViews language, are presented to demonstrate the expressiveness of the language and the efficiency of the compiler generated code. The applications are an application that collects and aggregates sensor data in network, an application that performs dynamic service installation, a mobile camera application that supports computation offloading for image understanding, and an augmented-reality (AR) Pacman game. The efficiency of the compiler generated code is verified through simulation and physical measurements. The reported results show that SpatialViews is an expressive and effective language for ad-hoc networks. In addition, compiler optimizations can significantly improve response times and energy consumption.