Providing Effective Access to Shared Resources: A COIN Approach

NASA Technical Reports Server (NTRS)

Airiau, Stephane; Wolpert, David H.; Sen, Sandip; Tumer, Kagan

2003-01-01

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user's satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and 'aligned' with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the COllective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

NASA Technical Reports Server (NTRS)

Arellano, John; Young, M.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Goodenow, D. A.; Myers, J. G.

2016-01-01

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

Optimizing Resource Utilization in Grid Batch Systems

NASA Astrophysics Data System (ADS)

Gellrich, Andreas

2012-12-01

On Grid sites, the requirements of the computing tasks (jobs) to computing, storage, and network resources differ widely. For instance Monte Carlo production jobs are almost purely CPU-bound, whereas physics analysis jobs demand high data rates. In order to optimize the utilization of the compute node resources, jobs must be distributed intelligently over the nodes. Although the job resource requirements cannot be deduced directly, jobs are mapped to POSIX UID/GID according to the VO, VOMS group and role information contained in the VOMS proxy. The UID/GID then allows to distinguish jobs, if users are using VOMS proxies as planned by the VO management, e.g. ‘role=production’ for Monte Carlo jobs. It is possible to setup and configure batch systems (queuing system and scheduler) at Grid sites based on these considerations although scaling limits were observed with the scheduler MAUI. In tests these limitations could be overcome with a home-made scheduler.

Multidimensional optimal droop control for wind resources in DC microgrids

NASA Astrophysics Data System (ADS)

Bunker, Kaitlyn J.

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

Lean processes for optimizing OR capacity utilization: prospective analysis before and after implementation of value stream mapping (VSM).

PubMed

Schwarz, Patric; Pannes, Klaus Dieter; Nathan, Michel; Reimer, Hans Jorg; Kleespies, Axel; Kuhn, Nicole; Rupp, Anne; Zügel, Nikolaus Peter

2011-10-01

The decision to optimize the processes in the operating tract was based on two factors: competition among clinics and a desire to optimize the use of available resources. The aim of the project was to improve operating room (OR) capacity utilization by reduction of change and throughput time per patient. The study was conducted at Centre Hospitalier Emil Mayrisch Clinic for specialized care (n = 618 beds) Luxembourg (South). A prospective analysis was performed before and after the implementation of optimized processes. Value stream analysis and design (value stream mapping, VSM) were used as tools. VSM depicts patient throughput and the corresponding information flows. Furthermore it is used to identify process waste (e.g. time, human resources, materials, etc.). For this purpose, change times per patient (extubation of patient 1 until intubation of patient 2) and throughput times (inward transfer until outward transfer) were measured. VSM, change and throughput times for 48 patient flows (VSM A(1), actual state = initial situation) served as the starting point. Interdisciplinary development of an optimized VSM (VSM-O) was evaluated. Prospective analysis of 42 patients (VSM-A(2)) without and 75 patients (VSM-O) with an optimized process in place were conducted. The prospective analysis resulted in a mean change time of (mean ± SEM) VSM-A(2) 1,507 ± 100 s versus VSM-O 933 ± 66 s (p < 0.001). The mean throughput time VSM-A(2) (mean ± SEM) was 151 min (±8) versus VSM-O 120 min (±10) (p < 0.05). This corresponds to a 23% decrease in waiting time per patient in total. Efficient OR capacity utilization and the optimized use of human resources allowed an additional 1820 interventions to be carried out per year without any increase in human resources. In addition, perioperative patient monitoring was increased up to 100%.

Effective Teaching of Economics: A Constrained Optimization Problem?

ERIC Educational Resources Information Center

Hultberg, Patrik T.; Calonge, David Santandreu

2017-01-01

One of the fundamental tenets of economics is that decisions are often the result of optimization problems subject to resource constraints. Consumers optimize utility, subject to constraints imposed by prices and income. As economics faculty, instructors attempt to maximize student learning while being constrained by their own and students'…

FPGA Implementation of Optimal 3D-Integer DCT Structure for Video Compression

PubMed Central

2015-01-01

A novel optimal structure for implementing 3D-integer discrete cosine transform (DCT) is presented by analyzing various integer approximation methods. The integer set with reduced mean squared error (MSE) and high coding efficiency are considered for implementation in FPGA. The proposed method proves that the least resources are utilized for the integer set that has shorter bit values. Optimal 3D-integer DCT structure is determined by analyzing the MSE, power dissipation, coding efficiency, and hardware complexity of different integer sets. The experimental results reveal that direct method of computing the 3D-integer DCT using the integer set [10, 9, 6, 2, 3, 1, 1] performs better when compared to other integer sets in terms of resource utilization and power dissipation. PMID:26601120

Earth resources data analysis program, phase 3

NASA Technical Reports Server (NTRS)

1975-01-01

Tasks were performed in two areas: (1) systems analysis and (2) algorithmic development. The major effort in the systems analysis task was the development of a recommended approach to the monitoring of resource utilization data for the Large Area Crop Inventory Experiment (LACIE). Other efforts included participation in various studies concerning the LACIE Project Plan, the utility of the GE Image 100, and the specifications for a special purpose processor to be used in the LACIE. In the second task, the major effort was the development of improved algorithms for estimating proportions of unclassified remotely sensed data. Also, work was performed on optimal feature extraction and optimal feature extraction for proportion estimation.

Autonomous In-Situ Resources Prospector

NASA Technical Reports Server (NTRS)

Dissly, R. W.; Buehler, M. G.; Schaap, M. G.; Nicks, D.; Taylor, G. J.; Castano, R.; Suarez, D.

2004-01-01

This presentation will describe the concept of an autonomous, intelligent, rover-based rapid surveying system to identify and map several key lunar resources to optimize their ISRU (In Situ Resource Utilization) extraction potential. Prior to an extraction phase for any target resource, ground-based surveys are needed to provide confirmation of remote observation, to quantify and map their 3-D distribution, and to locate optimal extraction sites (e.g. ore bodies) with precision to maximize their economic benefit. The system will search for and quantify optimal minerals for oxygen production feedstock, water ice, and high glass-content regolith that can be used for building materials. These are targeted because of their utility and because they are, or are likely to be, variable in quantity over spatial scales accessible to a rover (i.e., few km). Oxygen has benefits for life support systems and as an oxidizer for propellants. Water is a key resource for sustainable exploration, with utility for life support, propellants, and other industrial processes. High glass-content regolith has utility as a feedstock for building materials as it readily sinters upon heating into a cohesive matrix more readily than other regolith materials or crystalline basalts. Lunar glasses are also a potential feedstock for oxygen production, as many are rich in iron and titanium oxides that are optimal for oxygen extraction. To accomplish this task, a system of sensors and decision-making algorithms for an autonomous prospecting rover is described. One set of sensors will be located in the wheel tread of the robotic search vehicle providing contact sensor data on regolith composition. Another set of instruments will be housed on the platform of the rover, including VIS-NIR imagers and spectrometers, both for far-field context and near-field characterization of the regolith in the immediate vicinity of the rover. Also included in the sensor suite are a neutron spectrometer, ground-penetrating radar, and an instrumented cone penetrometer for subsurface assessment. Output from these sensors will be evaluated autonomously in real-time by decision-making software to evaluate if any of the targeted resources has been detected, and if so, to quantify their abundance. Algorithms for optimizing the mapping strategy based on target resource abundance and distribution are also included in the autonomous software. This approach emphasizes on-the-fly survey measurements to enable efficient and rapid prospecting of large areas, which will improve the economics of ISRU system approaches. The mature technology will enable autonomous rovers to create in-situ resource maps of lunar or other planetary surfaces, which will facilitate human and robotic exploration.

LCA-based optimization of wood utilization under special consideration of a cascading use of wood.

PubMed

Höglmeier, Karin; Steubing, Bernhard; Weber-Blaschke, Gabriele; Richter, Klaus

2015-04-01

Cascading, the use of the same unit of a resource in multiple successional applications, is considered as a viable means to improve the efficiency of resource utilization and to decrease environmental impacts. Wood, as a regrowing but nevertheless limited and increasingly in demand resource, can be used in cascades, thereby increasing the potential efficiency per unit of wood. This study aims to assess the influence of cascading wood utilization on optimizing the overall environmental impact of wood utilization. By combining a material flow model of existing wood applications - both for materials provision and energy production - with an algebraic optimization tool, the effects of the use of wood in cascades can be modelled and quantified based on life cycle impact assessment results for all production processes. To identify the most efficient wood allocation, the effects of a potential substitution of non-wood products were taken into account in a part of the model runs. The considered environmental indicators were global warming potential, particulate matter formation, land occupation and an aggregated single score indicator. We found that optimizing either the overall global warming potential or the value of the single score indicator of the system leads to a simultaneous relative decrease of all other considered environmental impacts. The relative differences between the impacts of the model run with and without the possibility of a cascading use of wood were 7% for global warming potential and the single score indicator, despite cascading only influencing a small part of the overall system, namely wood panel production. Cascading led to savings of up to 14% of the annual primary wood supply of the study area. We conclude that cascading can improve the overall performance of a wood utilization system. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Optimization Model for Scheduling Problems with Two-Dimensional Spatial Resource Constraint

NASA Technical Reports Server (NTRS)

Garcia, Christopher; Rabadi, Ghaith

2010-01-01

Traditional scheduling problems involve determining temporal assignments for a set of jobs in order to optimize some objective. Some scheduling problems also require the use of limited resources, which adds another dimension of complexity. In this paper we introduce a spatial resource-constrained scheduling problem that can arise in assembly, warehousing, cross-docking, inventory management, and other areas of logistics and supply chain management. This scheduling problem involves a twodimensional rectangular area as a limited resource. Each job, in addition to having temporal requirements, has a width and a height and utilizes a certain amount of space inside the area. We propose an optimization model for scheduling the jobs while respecting all temporal and spatial constraints.

An Analysis of the DER Adoption Climate in Japan UsingOptimization Results for Prototype Buildings with U.S. Comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2006-06-16

This research demonstrates economically optimal distributedenergy resource (DER) system choice using the DER choice and operationsoptimization program, the Distributed Energy Resources Customer AdoptionModel (DER-CAM). DER-CAM finds the optimal combination of installedequipment given prevailing utility tariffs and fuel prices, siteelectrical and thermal loads (including absorption cooling), and a menuof available equipment. It provides a global optimization, albeitidealized, that shows how site useful energy loads can be served atminimum cost. Five prototype Japanese commercial buildings are examinedand DER-CAM is applied to select the economically optimal DER system foreach. Based on the optimization results, energy and emission reductionsare evaluated. Significant decreases in fuelmore » consumption, carbonemissions, and energy costs were seen in the DER-CAM results. Savingswere most noticeable in the prototype sports facility, followed by thehospital, hotel, and office building. Results show that DER with combinedheat and power equipment is a promising efficiency and carbon mitigationstrategy, but that precise system design is necessary. Furthermore, aJapan-U.S. comparison study of policy, technology, and utility tariffsrelevant to DER installation is presented.« less

Community Design for Optimal Energy and Resource Utilization.

ERIC Educational Resources Information Center

Bilenky, Stephen; And Others

Presented is a study which investigated the energy and resource dynamics of a semi-autonomous domestic system for 30 people. The investigation is organized on three levels: (1) developing a preliminary design and design parameters; (2) development and quantification of the energy and resource dynamics; and (3) designing a model to extrapolate…

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Economic and environmental optimization of a multi-site utility network for an industrial complex.

PubMed

Kim, Sang Hun; Yoon, Sung-Geun; Chae, Song Hwa; Park, Sunwon

2010-01-01

Most chemical companies consume a lot of steam, water and electrical resources in the production process. Given recent record fuel costs, utility networks must be optimized to reduce the overall cost of production. Environmental concerns must also be considered when preparing modifications to satisfy the requirements for industrial utilities, since wastes discharged from the utility networks are restricted by environmental regulations. Construction of Eco-Industrial Parks (EIPs) has drawn attention as a promising approach for retrofitting existing industrial parks to improve energy efficiency. The optimization of the utility network within an industrial complex is one of the most important undertakings to minimize energy consumption and waste loads in the EIP. In this work, a systematic approach to optimize the utility network of an industrial complex is presented. An important issue in the optimization of a utility network is the desire of the companies to achieve high profits while complying with the environmental regulations. Therefore, the proposed optimization was performed with consideration of both economic and environmental factors. The proposed approach consists of unit modeling using thermodynamic principles, mass and energy balances, development of a multi-period Mixed Integer Linear Programming (MILP) model for the integration of utility systems in an industrial complex, and an economic/environmental analysis of the results. This approach is applied to the Yeosu Industrial Complex, considering seasonal utility demands. The results show that both the total utility cost and waste load are reduced by optimizing the utility network of an industrial complex. 2009 Elsevier Ltd. All rights reserved.

Favorable cardiovascular risk factor profile is associated with lower healthcare expenditure and resource utilization among adults with diabetes mellitus free of established cardiovascular disease: 2012 Medical Expenditure Panel Survey (MEPS).

PubMed

Feldman, David I; Valero-Elizondo, Javier; Salami, Joseph A; Rana, Jamal S; Ogunmoroti, Oluseye; Osondu, Chukwuemeka U; Spatz, Erica S; Virani, Salim S; Blankstein, Ron; Blaha, Michael J; Veledar, Emir; Nasir, Khurram

2017-03-01

Given the prevalence and economic burden of diabetes mellitus (DM), we studied the impact of a favorable cardiovascular risk factor (CRF) profile on healthcare expenditures and resource utilization among individuals without cardiovascular disease (CVD), by DM status. 25,317 participants were categorized into 3 mutually-exclusive strata: "Poor", "Average" and "Optimal" CRF profiles (≥4, 2-3, 0-1 CRF, respectively). Two-part econometric models were utilized to study cost data. Mean age was 45 (48% male), with 54% having optimal, 39% average, and 7% poor CRF profiles. Individuals with DM were more likely to have poor CRF profile vs. those without DM (OR 7.7, 95% CI 6.4, 9.2). Individuals with DM/poor CRF profile had a mean annual expenditure of $9,006, compared to $6,461 among those with DM/optimal CRF profile (p < 0.001). A favorable CRF profile is associated with significantly lower healthcare expenditures and utilization in CVD-free individuals across DM status, suggesting that these individuals require aggressive individualized prescriptions targeting lifestyle modifications and therapeutic treatments. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal Design of Biomass Utilization System for Rural Area Includes Technical and Economic Dimensions

NASA Astrophysics Data System (ADS)

Morioka, Yasuki; Nakata, Toshihiko

In order to design optimal biomass utilization system for rural area, OMNIBUS (The Optimization Model for Neo-Integrated Biomass Utilization System) has been developed. OMNIBUS can derive the optimal system configuration to meet different objective function, such as current account balance, amount of biomass energy supply, and CO2 emission. Most of biomass resources in a focused region e.g. wood biomass, livestock biomass, and crop residues are considered in the model. Conversion technologies considered are energy utilization technologies e.g. direct combustion and methane fermentation, and material utilization technologies e.g. composting and carbonization. Case study in Miyakojima, Okinawa prefecture, has been carried out for several objective functions and constraint conditions. Considering economics of the utilization system as a priority requirement, composting and combustion heat utilization are mainly chosen in the optimal system configuration. However gasification power plant and methane fermentation are included in optimal solutions, only when both biomass energy utilization and CO2 reduction have been set as higher priorities. External benefit of CO2 reduction has large impacts on the system configuration. Provided marginal external benefit of more than 50,000 JPY/t-C, external benefit becomes greater than the revenue from electricity and compost etc. Considering technological learning in the future, expensive technologies such as gasification power plant and methane fermentation will have economic feasibility as well as market competitiveness.

Opportunistic Computing with Lobster: Lessons Learned from Scaling up to 25k Non-Dedicated Cores

NASA Astrophysics Data System (ADS)

Wolf, Matthias; Woodard, Anna; Li, Wenzhao; Hurtado Anampa, Kenyi; Yannakopoulos, Anna; Tovar, Benjamin; Donnelly, Patrick; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2017-10-01

We previously described Lobster, a workflow management tool for exploiting volatile opportunistic computing resources for computation in HEP. We will discuss the various challenges that have been encountered while scaling up the simultaneous CPU core utilization and the software improvements required to overcome these challenges. Categories: Workflows can now be divided into categories based on their required system resources. This allows the batch queueing system to optimize assignment of tasks to nodes with the appropriate capabilities. Within each category, limits can be specified for the number of running jobs to regulate the utilization of communication bandwidth. System resource specifications for a task category can now be modified while a project is running, avoiding the need to restart the project if resource requirements differ from the initial estimates. Lobster now implements time limits on each task category to voluntarily terminate tasks. This allows partially completed work to be recovered. Workflow dependency specification: One workflow often requires data from other workflows as input. Rather than waiting for earlier workflows to be completed before beginning later ones, Lobster now allows dependent tasks to begin as soon as sufficient input data has accumulated. Resource monitoring: Lobster utilizes a new capability in Work Queue to monitor the system resources each task requires in order to identify bottlenecks and optimally assign tasks. The capability of the Lobster opportunistic workflow management system for HEP computation has been significantly increased. We have demonstrated efficient utilization of 25 000 non-dedicated cores and achieved a data input rate of 30 Gb/s and an output rate of 500GB/h. This has required new capabilities in task categorization, workflow dependency specification, and resource monitoring.

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

NASA Technical Reports Server (NTRS)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Energy Systems Integration News - September 2016 | Energy Systems

Science.gov Websites

, Smarter Grid Solutions demonstrated a new distributed energy resources (DER) software control platform utility interconnections require distributed generation (DG) devices to disconnect from the grid during OpenFMB distributed applications on the microgrid test site to locally optimize renewable energy resources

WMOST

EPA Pesticide Factsheets

The Watershed Management Optimization Support Tool (WMOST) allows water-resource managers and planners to screen a wide range of practices for cost-effectiveness in achieving watershed or water utilities management goals.

Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.

PubMed

Cherchi, Carla; Badruzzaman, Mohammad; Gordon, Matthew; Bunn, Simon; Jacangelo, Joseph G

2015-11-17

Holistic management of water and energy resources through energy and water quality management systems (EWQMSs) have traditionally aimed at energy cost reduction with limited or no emphasis on energy efficiency or greenhouse gas minimization. This study expanded the existing EWQMS framework and determined the impact of different management strategies for energy cost and energy consumption (e.g., carbon footprint) reduction on system performance at two drinking water utilities in California (United States). The results showed that optimizing for cost led to cost reductions of 4% (Utility B, summer) to 48% (Utility A, winter). The energy optimization strategy was successfully able to find the lowest energy use operation and achieved energy usage reductions of 3% (Utility B, summer) to 10% (Utility A, winter). The findings of this study revealed that there may be a trade-off between cost optimization (dollars) and energy use (kilowatt-hours), particularly in the summer, when optimizing the system for the reduction of energy use to a minimum incurred cost increases of 64% and 184% compared with the cost optimization scenario. Water age simulations through hydraulic modeling did not reveal any adverse effects on the water quality in the distribution system or in tanks from pump schedule optimization targeting either cost or energy minimization.

Favorable Cardiovascular Health Is Associated With Lower Health Care Expenditures and Resource Utilization in a Large US Employee Population: The Baptist Health South Florida Employee Study.

PubMed

Osondu, Chukwuemeka U; Aneni, Ehimen C; Valero-Elizondo, Javier; Salami, Joseph A; Rouseff, Maribeth; Das, Sankalp; Guzman, Henry; Younus, Adnan; Ogunmoroti, Oluseye; Feldman, Theodore; Agatston, Arthur S; Veledar, Emir; Katzen, Barry; Calitz, Chris; Sanchez, Eduardo; Lloyd-Jones, Donald M; Nasir, Khurram

2017-03-13

To examine the association of favorable cardiovascular health (CVH) status with 1-year health care expenditures and resource utilization in a large health care employee population. Employees of Baptist Health South Florida participated in a health risk assessment from January 1 through September 30, 2014. Information on dietary patterns, physical activity, blood pressure, blood glucose level, total cholesterol level, and smoking were collected. Participants were categorized into CVH profiles using the American Heart Association's ideal CVH construct as optimal (6-7 metrics), moderate (3-5 metrics), and low (0-2 metrics). Two-part econometric models were used to analyze health care expenditures. Of 9097 participants (mean ± SD age, 42.7±12.1 years), 1054 (11.6%) had optimal, 6945 (76.3%) had moderate, and 1098 (12.1%) had low CVH profiles. The mean annual health care expenditures among those with a low CVH profile was $10,104 (95% CI, $8633-$11,576) compared with $5824 (95% CI, $5485-$6164) and $4282 (95% CI, $3639-$4926) in employees with moderate and optimal CVH profiles, respectively. In adjusted analyses, persons with optimal and moderate CVH had a $2021 (95% CI, -$3241 to -$801) and $940 (95% CI, -$1560 to $80) lower mean expenditure, respectively, than those with low CVH. This trend remained even after adjusting for demographic characteristics and comorbid conditions as well as across all demographic subgroups. Similarly, health care resource utilization was significantly lower in those with optimal CVH profiles compared with those with moderate or low CVH profiles. Favorable CVH profile is associated with significantly lower total medical expenditures and health care utilization in a large, young, ethnically diverse, and fully insured employee population. Copyright © 2017 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Optimal control, investment and utilization schemes for energy storage under uncertainty

NASA Astrophysics Data System (ADS)

Mirhosseini, Niloufar Sadat

Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency operations; (ii) optimal market strategy of buy and sell over 24-hour periods; (iii) optimal storage charge and discharge in much shorter time intervals.

Multi-Dimensional Optimization for Cloud Based Multi-Tier Applications

ERIC Educational Resources Information Center

Jung, Gueyoung

2010-01-01

Emerging trends toward cloud computing and virtualization have been opening new avenues to meet enormous demands of space, resource utilization, and energy efficiency in modern data centers. By being allowed to host many multi-tier applications in consolidated environments, cloud infrastructure providers enable resources to be shared among these…

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach.

PubMed

Ozcan, Yasar A; Tànfani, Elena; Testi, Angela

2017-03-01

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.

International Research on ISS - The Benefits of Working Together

NASA Technical Reports Server (NTRS)

Uri, John J.; Thomas, Donald A.

2005-01-01

International Space Station is the most complex multinational cooperative space endeavor in history. Interagency agreements define utilization accommodations and resources available to each partner. Based on these arrangements, the partners select and implement research to meet agency goals and objectives. But to optimize the limited resources available to utilization, cooperation among the partners is essential. This paper describes various avenues available for partner cooperation and provides specific examples to demonstrate the value of such cooperation to accelerate and enhance science return.

Assessment of Distributed Generation Potential in JapaneseBuildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2005-05-25

To meet growing energy demands, energy efficiency, renewable energy, and on-site generation coupled with effective utilization of exhaust heat will all be required. Additional benefit can be achieved by integrating these distributed technologies into distributed energy resource (DER) systems (or microgrids). This research investigates a method of choosing economically optimal DER, expanding on prior studies at the Berkeley Lab using the DER design optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM finds the optimal combination of installed equipment from available DER technologies, given prevailing utility tariffs, site electrical and thermal loads, and a menu of available equipment.more » It provides a global optimization, albeit idealized, that shows how the site energy loads can be served at minimum cost by selection and operation of on-site generation, heat recovery, and cooling. Five prototype Japanese commercial buildings are examined and DER-CAM applied to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Based on the optimization results, energy and emission reductions are evaluated. Furthermore, a Japan-U.S. comparison study of policy, technology, and utility tariffs relevant to DER installation is presented. Significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the DER-CAM results. Savings were most noticeable in the sports facility (a very favourable CHP site), followed by the hospital, hotel, and office building.« less

What do adolescents and young adults want from cancer resources? Insights from a Delphi panel of AYA patients.

PubMed

Cheung, Christabel K; Zebrack, Brad

2017-01-01

Cancer treatment programs and community-based support organizations are increasingly producing information and support resources geared to adolescent and young adult patients (AYAs); however, systematically-derived knowledge about user preferences for these resources is lacking. The primary purpose of this study was to generate findings from informed AYA cancer patients that resource developers can use to create products consistent with AYAs' expressed preferences for information and support. Utilizing a modified Delphi technique, AYA cancer patients identified barriers to optimal AYA cancer care, cancer resources that address their needs, and specific characteristics of cancer resources they find helpful. The Delphi panel consisted of a convenience sample of 21 patients aged 18-39 years, who were diagnosed with cancer between ages 15-39 and were no more than 8 years out from cancer treatment at the time of the study. Survey data were collected in three consecutive and iterative rounds over the course of 6 months in 2015. Findings indicated that AYA patients prefer resources that reduce feelings of loneliness, create a sense of community or belonging, and provide opportunities to meet other AYA patients. Among the top barriers to optimal cancer care, AYAs identified a lack of cancer care providers specializing in AYA care, a lack of connection to an AYA patient community, and their own lack of ability to navigate the health system. Participants also described aspects of cancer information and supportive care resources that they believe address AYAs' concerns. Information derived from this study will help developers of cancer information and support resources to better reach their intended audience. From the point of view of AYA cancer patients, optimal cancer care and utilization of information and support resources requires that cancer support programs foster meaningful connections among AYA patients. Results also suggest that patient resources should equip AYAs with practical knowledge and skills necessary to navigate the health system and advocate for themselves. Given patient interest in social media, future research should further investigate optimizing online resources to serve the AYA cancer population.

Managing Watersheds with WMOST

EPA Pesticide Factsheets

The Watershed Management Optimization Support Tool (WMOST) allows water-resource managers and planners to screen a wide range of practices for cost-effectiveness in achieving watershed or water utilities management goals.

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-01-07

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-04-03

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Optimization and Control of Cyber-Physical Vehicle Systems

PubMed Central

Bradley, Justin M.; Atkins, Ella M.

2015-01-01

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541

Optimization and Control of Cyber-Physical Vehicle Systems.

PubMed

Bradley, Justin M; Atkins, Ella M

2015-09-11

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.

Optimal Operation and Dispatch of Voltage Regulation Devices Considering High Penetrations of Distributed Photovoltaic Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mather, Barry A; Hodge, Brian S; Cho, Gyu-Jung

Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation ofmore » the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.« less

WMOST 1.0 Download Page

EPA Pesticide Factsheets

The Watershed Management Optimization Support Tool (WMOST) allows water-resource managers and planners to screen a wide range of practices for cost-effectiveness in achieving watershed or water utilities management goals.

Optimizing Emory oak woodlands for multiple resource benefits [Poster

Treesearch

Catlow Shipek; Peter F. Ffolliott; Gerald J. Gottfried; Leonard F. DeBano

2005-01-01

The Emory oak woodlands in the southwestern United States present a diverse range of resources. People utilize these woodlands for wood products, cattle grazing, and recreational purposes. The woodlands provide a diversity of wildlife habitats for resident and migratory species. Occupying predominantly upland regions, the oak woodlands protect watersheds from excessive...

Optimizing Medical Kits for Spaceflight

NASA Technical Reports Server (NTRS)

Keenan, A. B,; Foy, Millennia; Myers, G.

2014-01-01

The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.

NASA Space Engineering Research Center for utilization of local planetary resources

NASA Technical Reports Server (NTRS)

1992-01-01

Reports covering the period from 1 Nov. 1991 to 31 Oct. 1992 and documenting progress at the NASA Space Engineering Research Center are included. Topics covered include: (1) processing of propellants, volatiles, and metals; (2) production of structural and refractory materials; (3) system optimization discovery and characterization; (4) system automation and optimization; and (5) database development.

A Mathematical Model for Allocation of School Resources to Optimize a Selected Output.

ERIC Educational Resources Information Center

McAfee, Jackson K.

The methodology of costing an education program by identifying the resources it utilizes places all costs within the framework of staff, equipment, materials, facilities, and services. This paper suggests that this methodology is much stronger than the more traditional budgetary and cost per pupil approach. The techniques of data collection are…

Optimal Capacitor Bank Capacity and Placement in Distribution Systems with High Distributed Solar Power Penetration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Mather, Barry A; Cho, Gyu-Jung

Capacitor banks have been generally installed and utilized to support distribution voltage during period of higher load or on longer, higher impedance, feeders. Installations of distributed energy resources in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile across a feeder, and therefore when a new capacitor bank is needed analysis of optimal capacity and location of the capacitor bank is required. In this paper, we model a particular distribution system including essential equipment. An optimization method is adopted to determine the best capacitymore » and location sets of the newly installed capacitor banks, in the presence of distributed solar power generation. Finally we analyze the optimal capacitor banks configuration through the optimization and simulation results.« less

Delineation of site-specific management units in a saline region at the Venice Lagoon margin, Italy, using soil reflectance and apparent electrical conductivity

USDA-ARS?s Scientific Manuscript database

Site-specific crop management utilizes site-specific management units (SSMUs) to apply inputs when, where, and in the amount needed to increase food productivity, optimize resource utilization, increase profitability, and reduce detrimental environmental impacts. It is the objective of this study to...

Risk and utility in portfolio optimization

NASA Astrophysics Data System (ADS)

Cohen, Morrel H.; Natoli, Vincent D.

2003-06-01

Modern portfolio theory (MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to alleviate that weakness which, typically, combine utility and risk. We present here a modification of MPT based on the inclusion of separate risk and utility criteria. We define risk as the probability of failure to meet a pre-established investment goal. We define utility as the expectation of a utility function with positive and decreasing marginal value as a function of yield. The emphasis throughout is on long investment horizons for which risk-free assets do not exist. Analytic results are presented for a Gaussian probability distribution. Risk-utility relations are explored via empirical stock-price data, and an illustrative portfolio is optimized using the empirical data.

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, DMS Integration of Distributed Energy Resources and Microgrids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Ravindra; Reilly, James T.; Wang, Jianhui

Deregulation of the electric utility industry, environmental concerns associated with traditional fossil fuel-based power plants, volatility of electric energy costs, Federal and State regulatory support of “green” energy, and rapid technological developments all support the growth of Distributed Energy Resources (DERs) in electric utility systems and ensure an important role for DERs in the smart grid and other aspects of modern utilities. DERs include distributed generation (DG) systems, such as renewables; controllable loads (also known as demand response); and energy storage systems. This report describes the role of aggregators of DERs in providing optimal services to distribution networks, through DERmore » monitoring and control systems—collectively referred to as a Distributed Energy Resource Management System (DERMS)—and microgrids in various configurations.« less

Advanced Performance Modeling with Combined Passive and Active Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dovrolis, Constantine; Sim, Alex

2015-04-15

To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performancemore » information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.« less

Favorable Cardiovascular Risk Profile Is Associated With Lower Healthcare Costs and Resource Utilization: The 2012 Medical Expenditure Panel Survey.

PubMed

Valero-Elizondo, Javier; Salami, Joseph A; Ogunmoroti, Oluseye; Osondu, Chukwuemeka U; Aneni, Ehimen C; Malik, Rehan; Spatz, Erica S; Rana, Jamal S; Virani, Salim S; Blankstein, Ron; Blaha, Michael J; Veledar, Emir; Nasir, Khurram

2016-03-01

The American Heart Association's 2020 Strategic Goals emphasize the value of optimizing risk factor status to reduce the burden of morbidity and mortality. In this study, we aimed to quantify the overall and marginal impact of favorable cardiovascular risk factor (CRF) profile on healthcare expenditure and resource utilization in the United States among those with and without cardiovascular disease (CVD). The study population was derived from the 2012 Medical Expenditure Panel Survey (MEPS). Direct and indirect costs were calculated for all-cause healthcare resource utilization. Variables of interest included CVD diagnoses (coronary artery disease, stroke, peripheral artery disease, dysrhythmias, or heart failure), ascertained by International Classification of Diseases, Ninth Edition, Clinical Modification codes, and CRF profile (hypertension, diabetes mellitus, hypercholesterolemia, smoking, physical activity, and obesity). Two-part econometric models were used to study expenditure data. The final study sample consisted of 15 651 MEPS participants (58.5±12 years, 54% female). Overall, 5921 (37.8%) had optimal, 7002 (44.7%) had average, and 2728 (17.4%) had poor CRF profile, translating to 54.2, 64.1, and 24.9 million adults in United States, respectively. Significantly lower health expenditures were noted with favorable CRF profile across CVD status. Among study participants with established CVD, overall healthcare expenditures with optimal and average CRF profile were $5946 and $3731 less compared with those with poor CRF profile. The respective differences were $4031 and $2560 in those without CVD. Favorable CRF profile is associated with significantly lower medical expenditure and healthcare utilization among individuals with and without established CVD. © 2016 American Heart Association, Inc.

In-Situ Resource Utilization for Space Exploration: Resource Processing, Mission-Enabling Technologies, and Lessons for Sustainability on Earth and Beyond

NASA Technical Reports Server (NTRS)

Hepp, A. F.; Palaszewski, B. A.; Landis, G. A.; Jaworske, D. A.; Colozza, A. J.; Kulis, M. J.; Heller, R. S.

2015-01-01

As humanity begins to reach out into the solar system, it has become apparent that supporting a human or robotic presence in transit andor on station requires significant expendable resources including consumables (to support people), fuel, and convenient reliable power. Transporting all necessary expendables is inefficient, inconvenient, costly, and, in the final analysis, a complicating factor for mission planners and a significant source of potential failure modes. Over the past twenty-five years, beginning with the Space Exploration Initiative, researchers at the NASA Glenn Research Center (GRC), academic collaborators, and industrial partners have analyzed, researched, and developed successful solutions for the challenges posed by surviving and even thriving in the resource limited environment(s) presented by near-Earth space and non-terrestrial surface operations. In this retrospective paper, we highlight the efforts of the co-authors in resource simulation and utilization, materials processing and consumable(s) production, power systems and analysis, fuel storage and handling, propulsion systems, and mission operations. As we move forward in our quest to explore space using a resource-optimized approach, it is worthwhile to consider lessons learned relative to efficient utilization of the (comparatively) abundant natural resources and improving the sustainability (and environment) for life on Earth. We reconsider Lunar (and briefly Martian) resource utilization for potential colonization, and discuss next steps moving away from Earth.

In-Situ Resource Utilization for Space Exploration: Resource Processing, Mission-Enabling Technologies, and Lessons for Sustainability on Earth and Beyond

NASA Technical Reports Server (NTRS)

Hepp, A. F.; Palaszewski, B. A.; Landis, G. A.; Jaworske, D. A.; Colozza, A. J.; Kulis, M. J.; Heller, Richard S.

2014-01-01

As humanity begins to reach out into the solar system, it has become apparent that supporting a human or robotic presence in transit and/or on station requires significant expendable resources including consumables (to support people), fuel, and convenient reliable power. Transporting all necessary expendables is inefficient, inconvenient, costly, and, in the final analysis, a complicating factor for mission planners and a significant source of potential failure modes. Over the past twenty-five years, beginning with the Space Exploration Initiative, researchers at the NASA Glenn Research Center (GRC), academic collaborators, and industrial partners have analyzed, researched, and developed successful solutions for the challenges posed by surviving and even thriving in the resource limited environment(s) presented by near-Earth space and non-terrestrial surface operations. In this retrospective paper, we highlight the efforts of the co-authors in resource simulation and utilization, materials processing and consumable(s) production, power systems and analysis, fuel storage and handling, propulsion systems, and mission operations. As we move forward in our quest to explore space using a resource-optimized approach, it is worthwhile to consider lessons learned relative to efficient utilization of the (comparatively) abundant natural resources and improving the sustainability (and environment) for life on Earth. We reconsider Lunar (and briefly Martian) resource utilization for potential colonization, and discuss next steps moving away from Earth.

Analysis of Department of Defense Organic Depot Maintenance Capacity Management and Facility Utilization Factors

DTIC Science & Technology

1991-09-01

System ( CAPMS ) in lieu of using DODI 4151.15H. Facility utilization rate computation is not explicitly defined; it is merely identified as a ratio of...front of a bottleneck buffers the critical resource and protects against disruption of the system. This approach optimizes facility utilization by...run titled BUFFERED BASELINE. Three different levels of inventory were used to evaluate the effect of increasing the inventory level on critical

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem. [Spacelab inventory procurement planning

NASA Technical Reports Server (NTRS)

Schlagheck, R. A.

1977-01-01

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

Korean Domestic Third Party Logistics Providers: Reach for a Global Market

DTIC Science & Technology

2010-03-01

receiving resources from oversea, parts production , assembling finished goods, sales, and customer service become more important. This is...businesses. Production can be located in an optimal area while efficient logistics systems allow world-wide distribution. Global logistics is activities...logistics is managing and utilizing production flow from resources to finished goods by gathering scattered production and sales footholds, and

Leveraging human decision making through the optimal management of centralized resources

NASA Astrophysics Data System (ADS)

Hyden, Paul; McGrath, Richard G.

2016-05-01

Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.

Nash Social Welfare in Multiagent Resource Allocation

NASA Astrophysics Data System (ADS)

Ramezani, Sara; Endriss, Ulle

We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness considerations. We show that the problem of finding an optimal outcome is NP-hard for a number of different languages for representing agent preferences; we establish new results regarding convergence to Nash-optimal outcomes in a distributed negotiation framework; and we design and test algorithms similar to those applied in combinatorial auctions for computing such an outcome directly.

Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation

NASA Astrophysics Data System (ADS)

Bedi, Amrit Singh; Rajawat, Ketan

2018-05-01

Stochastic network optimization problems entail finding resource allocation policies that are optimum on an average but must be designed in an online fashion. Such problems are ubiquitous in communication networks, where resources such as energy and bandwidth are divided among nodes to satisfy certain long-term objectives. This paper proposes an asynchronous incremental dual decent resource allocation algorithm that utilizes delayed stochastic {gradients} for carrying out its updates. The proposed algorithm is well-suited to heterogeneous networks as it allows the computationally-challenged or energy-starved nodes to, at times, postpone the updates. The asymptotic analysis of the proposed algorithm is carried out, establishing dual convergence under both, constant and diminishing step sizes. It is also shown that with constant step size, the proposed resource allocation policy is asymptotically near-optimal. An application involving multi-cell coordinated beamforming is detailed, demonstrating the usefulness of the proposed algorithm.

Hierarchical control framework for integrated coordination between distributed energy resources and demand response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Di; Lian, Jianming; Sun, Yannan

Demand response is representing a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. In this paper, a hierarchical control framework is proposed to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. In the coordination layer, various resource aggregations are optimally coordinated in a distributed manner to achieve the system-level objectives. In the device layer, individual resources are controlled in real time to follow the optimal power generation or consumption dispatched from the coordination layer. For the purpose of practical applications,more » a method is presented to determine the utility functions of controllable loads by taking into account the real-time load dynamics and the preferences of individual customers. The effectiveness of the proposed framework is validated by detailed simulation studies.« less

Mass and Volume Optimization of Space Flight Medical Kits

NASA Technical Reports Server (NTRS)

Keenan, A. B.; Foy, Millennia Hope; Myers, Jerry

2014-01-01

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Intelligent Transportation Infrastructure Benefits: Expected And Experienced

DOT National Transportation Integrated Search

1996-08-20

In traffic engineering, the concept of traffic control is giving way to the broader philosophy of Transportation Systems Management (TSM), whose purpose is not to move vehicles, but to optimize the utilization of transportation resources to improve t...

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

NASA Technical Reports Server (NTRS)

Otto, John C.; Paraschivoiu, Marius; Yesilyurt, Serhat; Patera, Anthony T.

1995-01-01

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

NASA Space Engineering Research Center for Utilization of Local Planetary Resources

NASA Technical Reports Server (NTRS)

Ramohalli, Kumar; Lewis, John S.

1991-01-01

In the processing of propellants, volatiles, and metals subject area, the following topics are discussed: reduction of lunar regolith; reduction of carbon dioxide; and reduction of carbonaceous materials. Other areas addressed include: (1) production of structural and refractory materials; (2) resource discovery and characterization; (3) system automation and optimization; and (4) database development. The majority of these topics are discussed with respect to the development of lunar and mars bases. Some main topics of interest include: asteroid resources, lunar resources, mars resources, materials processing, construction materials, propellant production, oxygen production, and space-based oxygen production plants.

Develop feedback system for intelligent dynamic resource allocation to improve application performance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gentile, Ann C.; Brandt, James M.; Tucker, Thomas

2011-09-01

This report provides documentation for the completion of the Sandia Level II milestone 'Develop feedback system for intelligent dynamic resource allocation to improve application performance'. This milestone demonstrates the use of a scalable data collection analysis and feedback system that enables insight into how an application is utilizing the hardware resources of a high performance computing (HPC) platform in a lightweight fashion. Further we demonstrate utilizing the same mechanisms used for transporting data for remote analysis and visualization to provide low latency run-time feedback to applications. The ultimate goal of this body of work is performance optimization in the facemore » of the ever increasing size and complexity of HPC systems.« less

Effect of video server topology on contingency capacity requirements

NASA Astrophysics Data System (ADS)

Kienzle, Martin G.; Dan, Asit; Sitaram, Dinkar; Tetzlaff, William H.

1996-03-01

Video servers need to assign a fixed set of resources to each video stream in order to guarantee on-time delivery of the video data. If a server has insufficient resources to guarantee the delivery, it must reject the stream request rather than slowing down all existing streams. Large scale video servers are being built as clusters of smaller components, so as to be economical, scalable, and highly available. This paper uses a blocking model developed for telephone systems to evaluate video server cluster topologies. The goal is to achieve high utilization of the components and low per-stream cost combined with low blocking probability and high user satisfaction. The analysis shows substantial economies of scale achieved by larger server images. Simple distributed server architectures can result in partitioning of resources with low achievable resource utilization. By comparing achievable resource utilization of partitioned and monolithic servers, we quantify the cost of partitioning. Next, we present an architecture for a distributed server system that avoids resource partitioning and results in highly efficient server clusters. Finally, we show how, in these server clusters, further optimizations can be achieved through caching and batching of video streams.

Exploring Faculty Integration of Moodle Resources: Effects of Theory-Based Training on Performance Objectives, Moodle Resource Integration, and Their Alignment

ERIC Educational Resources Information Center

Agamba, Joachim Jack

2012-01-01

Higher education institutions have been noted to be lacking in increasing the utilization of technology for student achievement. The lack of motivation by individual faculty members to optimize their use of technology has been identified as one of the main problems affecting appropriate technology use. The purpose of this research was to determine…

Evaluation method to floodwater amount of difficult control and utilization in flood season for hyperconcentration rivers and its application

NASA Astrophysics Data System (ADS)

Li, X.

2013-05-01

The severe soil erosion in the Chinese Loess Plateau has resulted in high sediment concentration in runoff, which can cause tremendous pressure to the development and utilization of regional floodwater resources as well as the regional flood control and disaster mitigation. The floodwater amount of difficult control and utilization in flood season (FADCUFS) is an important part of the available amount of surface water resources. It also has a critical role in the sustainable development of water resources, especially for those hyperconcentration rivers (HRs) in the Loess Plateau. The evaluation of FADCUFS for HRs is an important issue in the field of hydrology and water resources. However, the understandings of its connotation, evaluation method, and nature are limited. Combined engineering measures with non-engineering ones, the evaluation method of FADCUFS for HRs was presented based on the angles of water quantity and quality. The method divides the FADCUFS into two parts in terms of the flood control operation characteristics of reservoir in HR and the relationship between water resources utilization and sediment in runoff, respectively. One is the amount of difficult regulation-control floodwater (DRCF), and the other is the volume of difficult utilization floodwater (DUF). A case study of the Bajiazui Reservoir, located in the typical Jinghe River (the second tributary of the Chinese Yellow River with high sediment concentration) was performed. Three typical years, wet year (1988), average year (1986), and dry years (1995 and 2000), were employed. According to the daily optimal operation model of Bajiazui Reservoir, the DRCF occurs for only the wet year instead of the average and the dry years. There are four times of DRCF with the amount of 26.74 m3/s (July 14), 14.58 m3/s (August 5), 10.27 m3/s (August 9), and 1.23 m3/s (August 12) in 1988, respectively, with a total amount of 4.56 million m3. A certain close relationship exists between the amount of DRCF and the flood inflows to Bajiazui. When the events of DRCF occur, there must be big flood inflows several days ago. And the outflows from the daily optimal operation model exceed their permitted limits of discharges. In addition, they are close to the measured runoffs from the Bajiazui Hydrological Station downstream the dam. It indicates that the presented daily optimal operation model has a high accuracy and can achieve credible results. On the other hand, the maximum grade approach is used to achieve the coefficients of surplus floodwater in flood season in terms of the daily outflows from the daily optimal operation model and the corresponding sediment concentration in runoffs. When the water resources utilization limit of sediment concentration in runoff is set as 10%, the volume of DUF in flood season of 1988 is then calculated as 108.29 million m3. So the value of FADCUFS can be determined as 112.85 (=4.56+108.29) million m3, accounting for 78.06% of the total discharge of reservoir in flood season. The study deepens the understandings of the connotation and the evaluation method of FADCUFS. It offers a new and reliable approach to assess the FADCUFS for HRs. The results are beneficial to the sustainable development of regional water resources.

Habitat management utilizing native wildflowers to foster pollinator abundance

USDA-ARS?s Scientific Manuscript database

Pollinators provide essential ecosystem services to agricultural crops, however their population has come under threat globally as a result of intensive agricultural practices and landscape simplification. Designing diverse heterogeneous agricultural landscapes to provide optimal resources serves as...

An optimization method of VON mapping for energy efficiency and routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Liu, Huanlin; Xiong, Cuilian; Chen, Yong; Li, Changping; Chen, Derun

2018-03-01

To improve resources utilization efficiency, network virtualization in elastic optical networks has been developed by sharing the same physical network for difference users and applications. In the process of virtual nodes mapping, longer paths between physical nodes will consume more spectrum resources and energy. To address the problem, we propose a virtual optical network mapping algorithm called genetic multi-objective optimize virtual optical network mapping algorithm (GM-OVONM-AL), which jointly optimizes the energy consumption and spectrum resources consumption in the process of virtual optical network mapping. Firstly, a vector function is proposed to balance the energy consumption and spectrum resources by optimizing population classification and crowding distance sorting. Then, an adaptive crossover operator based on hierarchical comparison is proposed to improve search ability and convergence speed. In addition, the principle of the survival of the fittest is introduced to select better individual according to the relationship of domination rank. Compared with the spectrum consecutiveness-opaque virtual optical network mapping-algorithm and baseline-opaque virtual optical network mapping algorithm, simulation results show the proposed GM-OVONM-AL can achieve the lowest bandwidth blocking probability and save the energy consumption.

Evaluation on equality and efficiency of health resources allocation and health services utilization in China.

PubMed

Sun, Jian; Luo, Hongye

2017-07-14

China is faced with a daunting challenge to equality and efficiency in health resources allocation and health services utilization in the context of rapid economic growth. This study sought to evaluate the equality and efficiency of health resources allocation and health services utilization in China. Demographic, economic, and geographic area data was sourced from China Statistical Yearbook 2012-2016. Data related to health resources and health services was obtained from China Health Statistics Yearbook 2012-2016. Furthermore, we evaluated the equality of health resources allocation based on Gini coefficient. Concentration index was used to measure the equality in utilization of health services. Data envelopment analysis (DEA) was employed to assess the efficiency of health resources allocation. From 2011 to 2015, the Gini coefficients for health resources by population ranged between 0.0644 and 0.1879, while the Gini coefficients for the resources by geographic area ranged from 0.6136 to 0.6568. Meanwhile, the concentration index values for health services utilization ranged from -0.0392 to 0.2110. Moreover, in 2015, 10 provinces (32.26%) were relatively efficient in terms of health resources allocation, while 7 provinces (22.58%) and 14 provinces (45.16%) were weakly efficient and inefficient, respectively. There exist distinct regional disparities in the distribution of health resources in China, which are mainly reflected in the geographic distribution of health resources. Furthermore, the people living in the eastern developed areas are more likely to use outpatient care, while the people living in western underdeveloped areas are more likely to use inpatient care. Moreover, the efficiency of health resources allocation in 21 provinces (67.74%) of China was low and needs to be improved. Thus, the government should pay more attention to the equality based on geographic area, guide patients to choose medical treatment rationally, and optimize the resource investments for different provinces.

Hybrid protection algorithms based on game theory in multi-domain optical networks

NASA Astrophysics Data System (ADS)

Guo, Lei; Wu, Jingjing; Hou, Weigang; Liu, Yejun; Zhang, Lincong; Li, Hongming

2011-12-01

With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user's utility, the network operator's utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator's utility, while IEP has better user's utility.

Ecological enrichment in agroecosystems: Utilizing wildflowers to promote beneficial arthropod communities

USDA-ARS?s Scientific Manuscript database

Beneficial arthropods which provide important ecosystems services have come under threat as a result of intensive agricultural practices and landscape simplification. Engineering diverse heterogeneous agricultural landscapes to provide optimal resources for beneficial arthropods may recover and enha...

Instrumentation for optimizing an underground coal-gasification process

NASA Astrophysics Data System (ADS)

Seabaugh, W.; Zielinski, R. E.

1982-06-01

While the United States has a coal resource base of 6.4 trillion tons, only seven percent is presently recoverable by mining. The process of in-situ gasification can recover another twenty-eight percent of the vast resource, however, viable technology must be developed for effective in-situ recovery. The key to this technology is system that can optimize and control the process in real-time. An instrumentation system is described that optimizes the composition of the injection gas, controls the in-situ process and conditions the product gas for maximum utilization. The key elements of this system are Monsanto PRISM Systems, a real-time analytical system, and a real-time data acquisition and control system. This system provides from complete automation of the process but can easily be overridden by manual control. The use of this cost effective system can provide process optimization and is an effective element in developing a viable in-situ technology.

Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things.

PubMed

Sun, Yanjing; Guo, Yiyu; Li, Song; Wu, Dapeng; Wang, Bin

2018-05-15

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Optimization of Supercomputer Use on EADS II System

NASA Technical Reports Server (NTRS)

Ahmed, Ardsher

1998-01-01

The main objective of this research was to optimize supercomputer use to achieve better throughput and utilization of supercomputers and to help facilitate the movement of non-supercomputing (inappropriate for supercomputer) codes to mid-range systems for better use of Government resources at Marshall Space Flight Center (MSFC). This work involved the survey of architectures available on EADS II and monitoring customer (user) applications running on a CRAY T90 system.

Optimal route discovery for soft QOS provisioning in mobile ad hoc multimedia networks

NASA Astrophysics Data System (ADS)

Huang, Lei; Pan, Feng

2007-09-01

In this paper, we propose an optimal routing discovery algorithm for ad hoc multimedia networks whose resource keeps changing, First, we use stochastic models to measure the network resource availability, based on the information about the location and moving pattern of the nodes, as well as the link conditions between neighboring nodes. Then, for a certain multimedia packet flow to be transmitted from a source to a destination, we formulate the optimal soft-QoS provisioning problem as to find the best route that maximize the probability of satisfying its desired QoS requirements in terms of the maximum delay constraints. Based on the stochastic network resource model, we developed three approaches to solve the formulated problem: A centralized approach serving as the theoretical reference, a distributed approach that is more suitable to practical real-time deployment, and a distributed dynamic approach that utilizes the updated time information to optimize the routing for each individual packet. Examples of numerical results demonstrated that using the route discovered by our distributed algorithm in a changing network environment, multimedia applications could achieve better QoS statistically.

Stand-alone hybrid wind-photovoltaic power generation systems optimal sizing

NASA Astrophysics Data System (ADS)

Crǎciunescu, Aurelian; Popescu, Claudia; Popescu, Mihai; Florea, Leonard Marin

2013-10-01

Wind and photovoltaic energy resources have attracted energy sectors to generate power on a large scale. A drawback, common to these options, is their unpredictable nature and dependence on day time and meteorological conditions. Fortunately, the problems caused by the variable nature of these resources can be partially overcome by integrating the two resources in proper combination, using the strengths of one source to overcome the weakness of the other. The hybrid systems that combine wind and solar generating units with battery backup can attenuate their individual fluctuations and can match with the power requirements of the beneficiaries. In order to efficiently and economically utilize the hybrid energy system, one optimum match design sizing method is necessary. In this way, literature offers a variety of methods for multi-objective optimal designing of hybrid wind/photovoltaic (WG/PV) generating systems, one of the last being genetic algorithms (GA) and particle swarm optimization (PSO). In this paper, mathematical models of hybrid WG/PV components and a short description of the last proposed multi-objective optimization algorithms are given.

Evaluating and optimizing horticultural regimes in space plant growth facilities

NASA Astrophysics Data System (ADS)

Berkovich, Y.; Chetirkin, R.; Wheeler, R.; Sager, J.

In designing innovative Space Plant Growth Facilities (SPGF) for long duration space f ightl various limitations must be addressed including onboard resources: volume, energy consumption, heat transfer and crew labor expenditure. The required accuracy in evaluating onboard resources by using the equivalent mass methodology and applying it to the design of such facilities is not precise. This is due to the uncertainty of the structure and not completely understanding of the properties of all associated hardware, including the technology in these systems. We present a simple criteria of optimization for horticultural regimes in SPGF: Qmax = max [M · (EBI) 2 / (V · E · T) ], where M is the crop harvest in terms of total dry biomass in the plant growth system; EBI is the edible biomass index (harvest index), V is a volume occupied by the crop; E is the crop light energy supply during growth; T is the crop growth duration. The criterion reflects directly on the consumption of onboard resources for crop production. We analyzed the efficiency of plant crops and the environmental parameters by examining the criteria for 15 salad and 12 wheat crops from the data in the ALS database at Kennedy Space Center. Some following conclusion have been established: 1. The technology involved in growing salad crops on a cylindrical type surface provides a more meaningful Q-criterion; 2. Wheat crops were less efficient than leafy greens (salad crops) when examining resource utilization; 3. By increasing light intensity of the crop the efficiency of the resource utilization could decrease. Using the existing databases and Q-criteria we have found that the criteria can be used in optimizing design and horticultural regimes in the SPGF.

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

NASA Astrophysics Data System (ADS)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

Coordinative Voltage Control Strategy with Multiple Resources for Distribution Systems of High PV Penetration: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Xiangqi; Zhang, Yingchen

This paper presents an optimal voltage control methodology with coordination among different voltage-regulating resources, including controllable loads, distributed energy resources such as energy storage and photovoltaics (PV), and utility voltage-regulating devices such as voltage regulators and capacitors. The proposed methodology could effectively tackle the overvoltage and voltage regulation device distortion problems brought by high penetrations of PV to improve grid operation reliability. A voltage-load sensitivity matrix and voltage-regulator sensitivity matrix are used to deploy the resources along the feeder to achieve the control objectives. Mixed-integer nonlinear programming is used to solve the formulated optimization control problem. The methodology has beenmore » tested on the IEEE 123-feeder test system, and the results demonstrate that the proposed approach could actively tackle the voltage problem brought about by high penetrations of PV and improve the reliability of distribution system operation.« less

A self-organizing neural network for job scheduling in distributed systems

NASA Astrophysics Data System (ADS)

Newman, Harvey B.; Legrand, Iosif C.

2001-08-01

The aim of this work is to describe a possible approach for the optimization of the job scheduling in large distributed systems, based on a self-organizing Neural Network. This dynamic scheduling system should be seen as adaptive middle layer software, aware of current available resources and making the scheduling decisions using the "past experience." It aims to optimize job specific parameters as well as the resource utilization. The scheduling system is able to dynamically learn and cluster information in a large dimensional parameter space and at the same time to explore new regions in the parameters space. This self-organizing scheduling system may offer a possible solution to provide an effective use of resources for the off-line data processing jobs for future HEP experiments.

Modeling Road Vulnerability to Snow Using Mixed Integer Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Tony K; Omitaomu, Olufemi A; Ostrowski, James A

As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roadsmore » using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.« less

Trade-offs between energy maximization and parental care in a central place forager, the sea otter

USGS Publications Warehouse

Thometz, N M; Staedler, M.M.; Tomoleoni, Joseph; Bodkin, James L.; Bentall, G.B.; Tinker, M. Tim

2016-01-01

Between 1999 and 2014, 126 archival time–depth recorders (TDRs) were used to examine the foraging behavior of southern sea otters (Enhydra lutris nereis) off the coast of California, in both resource-abundant (recently occupied, low sea otter density) and resource-limited (long-occupied, high sea otter density) locations. Following predictions of foraging theory, sea otters generally behaved as energy rate maximizers. Males and females without pups employed similar foraging strategies to optimize rates of energy intake in resource-limited habitats, with some exceptions. Both groups increased overall foraging effort and made deeper, longer and more energetically costly dives as resources became limited, but males were more likely than females without pups to utilize extreme dive profiles. In contrast, females caring for young pups (≤10 weeks) prioritized parental care over energy optimization. The relative importance of parental care versus energy optimization for adult females with pups appeared to reflect developmental changes as dependent young matured. Indeed, contrary to females during the initial stages of lactation, females with large pups approaching weaning once again prioritized optimizing energy intake. The increasing prioritization of energy optimization over the course of lactation was possible due to the physiological development of pups and likely driven by the energetic deficit incurred by females early in lactation. Our results suggest that regardless of resource availability, females at the end of lactation approach a species-specific ceiling for percent time foraging and that reproductive females in the central portion of the current southern sea otter range are disproportionately affected by resource limitation.

Optimized model tuning in medical systems.

PubMed

Kléma, Jirí; Kubalík, Jirí; Lhotská, Lenka

2005-12-01

In medical systems it is often advantageous to utilize specific problem situations (cases) in addition to or instead of a general model. Decisions are then based on relevant past cases retrieved from a case memory. The reliability of such decisions depends directly on the ability to identify cases of practical relevance to the current situation. This paper discusses issues of automated tuning in order to obtain a proper definition of mutual case similarity in a specific medical domain. The main focus is on a reasonably time-consuming optimization of the parameters that determine case retrieval and further utilization in decision making/ prediction. The two case studies - mortality prediction after cardiological intervention, and resource allocation at a spa - document that the optimization process is influenced by various characteristics of the problem domain.

In-Situ Resource Utilization Experiment for the Asteroid Redirect Crewed Mission

NASA Astrophysics Data System (ADS)

Elliott, J.; Fries, M.; Love, S.; Sellar, R. G.; Voecks, G.; Wilson, D.

2015-10-01

The Asteroid Redirect Crewed Mission (ARCM) represents a unique opportunity to perform in-situ testing of concepts that could lead to full-scale exploitation of asteroids for their valuable resources [1]. This paper describes a concept for an astronautoperated "suitcase" experiment to would demonstrate asteroid volatile extraction using a solar-heated oven and integral cold trap in a configuration scalable to full-size asteroids. Conversion of liberated water into H2 and O2 products would also be demonstrated through an integral processing and storage unit. The plan also includes development of a local prospecting system consisting of a suit-mounted multi-spectral imager to aid the crew in choosing optimal samples, both for In-Situ Resource Utilization (ISRU) and for potential return to Earth.

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Risk Decision Making Model for Reservoir Floodwater resources Utilization

NASA Astrophysics Data System (ADS)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

Integrated planning for regional development planning and water resources management under uncertainty: A case study of Xining, China

NASA Astrophysics Data System (ADS)

Fu, Z. H.; Zhao, H. J.; Wang, H.; Lu, W. T.; Wang, J.; Guo, H. C.

2017-11-01

Economic restructuring, water resources management, population planning and environmental protection are subjects to inner uncertainties of a compound system with objectives which are competitive alternatives. Optimization model and water quality model are usually used to solve problems in a certain aspect. To overcome the uncertainty and coupling in reginal planning management, an interval fuzzy program combined with water quality model for regional planning and management has been developed to obtain the absolutely ;optimal; solution in this study. The model is a hybrid methodology of interval parameter programming (IPP), fuzzy programing (FP), and a general one-dimensional water quality model. The method extends on the traditional interval parameter fuzzy programming method by integrating water quality model into the optimization framework. Meanwhile, as an abstract concept, water resources carrying capacity has been transformed into specific and calculable index. Besides, unlike many of the past studies about water resource management, population as a significant factor has been considered. The results suggested that the methodology was applicable for reflecting the complexities of the regional planning and management systems within the planning period. The government policy makers could establish effective industrial structure, water resources utilization patterns and population planning, and to better understand the tradeoffs among economic, water resources, population and environmental objectives.

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 1: Technical description

NASA Technical Reports Server (NTRS)

1971-01-01

The optimal allocation of resources to the national space program over an extended time period requires the solution of a large combinatorial problem in which the program elements are interdependent. The computer model uses an accelerated search technique to solve this problem. The model contains a large number of options selectable by the user to provide flexible input and a broad range of output for use in sensitivity analyses of all entering elements. Examples of these options are budget smoothing under varied appropriation levels, entry of inflation and discount effects, and probabilistic output which provides quantified degrees of certainty that program costs will remain within planned budget. Criteria and related analytic procedures were established for identifying potential new space program directions. Used in combination with the optimal resource allocation model, new space applications can be analyzed in realistic perspective, including the advantage gain from existing space program plant and on-going programs such as the space transportation system.

Sort-Mid tasks scheduling algorithm in grid computing.

PubMed

Reda, Naglaa M; Tawfik, A; Marzok, Mohamed A; Khamis, Soheir M

2015-11-01

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.

Sort-Mid tasks scheduling algorithm in grid computing

PubMed Central

Reda, Naglaa M.; Tawfik, A.; Marzok, Mohamed A.; Khamis, Soheir M.

2014-01-01

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan. PMID:26644937

A Predictive Analysis of the Department of Defense Distribution System Utilizing Random Forests

DTIC Science & Technology

2016-06-01

resources capable of meeting both customer and individual resource constraints and goals while also maximizing the global benefit to the supply...and probability rules to determine the optimal red wine distribution network for an Italian-based wine producer. The decision support model for...combinations of factors that will result in delivery of the highest quality wines . The model’s first stage inputs basic logistics information to look

Optimization Model for Web Based Multimodal Interactive Simulations.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2015-07-15

This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update . In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.

Optimization Model for Web Based Multimodal Interactive Simulations

PubMed Central

Halic, Tansel; Ahn, Woojin; De, Suvranu

2015-01-01

This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update. In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach. PMID:26085713

Effect of provider volume on resource utilization for surgical procedures of the knee.

PubMed

Jain, Nitin; Pietrobon, Ricardo; Guller, Ulrich; Shankar, Anoop; Ahluwalia, Ajit S; Higgins, Laurence D

2005-05-01

Operating-room time and patient disposition on discharge are important determinants of healthcare resource utilization and cost. We examined the relation between these determinants and hospital/surgeon volume for anterior cruciate ligament (ACL) reconstruction and meniscectomy procedures. Patients undergoing ACL reconstruction (18,390 cases) and meniscectomy (123,012 cases) were extracted from the State Ambulatory Surgery Databases for the years 1997-2000. Surgeon and hospital volume were divided into low-, intermediate-, and high-volume categories. Multivariate logistic regression models were used to estimate the adjusted association between surgeon and hospital volume and patient discharge status and operating-room time. Patients undergoing ACL reconstruction or meniscectomy performed by low-volume surgeons were significantly more likely to be non-routinely discharged as compared to high-volume surgeons (adjusted odds ratio 3.5, 95% confidence interval 1.7-7.2 for ACL reconstruction; adjusted odds ratio 2.0, 95% confidence interval 1.6-2.3 for meniscectomy). The mean operating-room time for performing ACL reconstruction or meniscectomy was significantly higher in low- and intermediate-volume surgeons and hospitals as compared to high-volume surgeons and hospitals (p < or = 0.001). High-volume providers utilize healthcare resources more efficiently. Our findings may help surgeons and hospitals in optimizing resource utilization and cost for routinely-performed ambulatory surgery procedures.

Predicting Short-Term Remembering as Boundedly Optimal Strategy Choice.

PubMed

Howes, Andrew; Duggan, Geoffrey B; Kalidindi, Kiran; Tseng, Yuan-Chi; Lewis, Richard L

2016-07-01

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: (a) the performance of the minority of participants who did not find boundedly optimal adaptations, and (b) the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training. Copyright © 2015 Cognitive Science Society, Inc.

Energy management system turns data into market info

DOE Office of Scientific and Technical Information (OSTI.GOV)

Traynor, P.J.; Ackerman, W.J.

1996-09-01

The designers claim that Wisconsin Power & Light Co`s new energy management system is the first system of its type in the world in terms of the comprehensiveness and scope of its stored and retrievable data. Furthermore, the system`s link to the utility`s generating assets enables powerplant management to dispatch generation resources based on up-to-date unit characteristics. That means that the new system gives WP&L a competitive tool to optimize operations as well as fine-tune its EMS based on timely load and unit response information. Additionally, the EMS gives WP&L insight into the complex issues related to the unbundling ofmore » generation resources.« less

About Distributed Simulation-based Optimization of Forming Processes using a Grid Architecture

NASA Astrophysics Data System (ADS)

Grauer, Manfred; Barth, Thomas

2004-06-01

Permanently increasing complexity of products and their manufacturing processes combined with a shorter "time-to-market" leads to more and more use of simulation and optimization software systems for product design. Finding a "good" design of a product implies the solution of computationally expensive optimization problems based on the results of simulation. Due to the computational load caused by the solution of these problems, the requirements on the Information&Telecommunication (IT) infrastructure of an enterprise or research facility are shifting from stand-alone resources towards the integration of software and hardware resources in a distributed environment for high-performance computing. Resources can either comprise software systems, hardware systems, or communication networks. An appropriate IT-infrastructure must provide the means to integrate all these resources and enable their use even across a network to cope with requirements from geographically distributed scenarios, e.g. in computational engineering and/or collaborative engineering. Integrating expert's knowledge into the optimization process is inevitable in order to reduce the complexity caused by the number of design variables and the high dimensionality of the design space. Hence, utilization of knowledge-based systems must be supported by providing data management facilities as a basis for knowledge extraction from product data. In this paper, the focus is put on a distributed problem solving environment (PSE) capable of providing access to a variety of necessary resources and services. A distributed approach integrating simulation and optimization on a network of workstations and cluster systems is presented. For geometry generation the CAD-system CATIA is used which is coupled with the FEM-simulation system INDEED for simulation of sheet-metal forming processes and the problem solving environment OpTiX for distributed optimization.

BESIII physical offline data analysis on virtualization platform

NASA Astrophysics Data System (ADS)

Huang, Q.; Li, H.; Kan, B.; Shi, J.; Lei, X.

2015-12-01

In this contribution, we present an ongoing work, which aims at benefiting BESIII computing system for higher resource utilization and more efficient job operations brought by cloud and virtualization technology with Openstack and KVM. We begin with the architecture of BESIII offline software to understand how it works. We mainly report the KVM performance evaluation and optimization from various factors in hardware and kernel. Experimental results show the CPU performance penalty of KVM can be approximately decreased to 3%. In addition, the performance comparison between KVM and physical machines in aspect of CPU, disk IO and network IO is also presented. Finally, we present our development work, an adaptive cloud scheduler, which allocates and reclaims VMs dynamically according to the status of TORQUE queue and the size of resource pool to improve resource utilization and job processing efficiency.

NASA Space Engineering Research Center for Utilization of Local Planetary Resources

NASA Technical Reports Server (NTRS)

Ramohalli, Kumar; Lewis, John S.

1989-01-01

Progress toward the goal of exploiting extraterrestrial resources for space missions is documented. Some areas of research included are as follows: Propellant and propulsion optimization; Automation of propellant processing with quantitative simulation; Ore reduction through chlorination and free radical production; Characterization of lunar ilmenite and its simulants; Carbothermal reduction of ilmenite with special reference to microgravity chemical reactor design; Gaseous carbonyl extraction and purification of ferrous metals; Overall energy management; and Information management for space processing.

An innovative time-cost-quality tradeoff modeling of building construction project based on resource allocation.

PubMed

Hu, Wenfa; He, Xinhua

2014-01-01

The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.

Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

NASA Astrophysics Data System (ADS)

Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

2017-08-01

Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

Integrating Reservations and Queuing in Remote Laboratory Scheduling

ERIC Educational Resources Information Center

Lowe, D.

2013-01-01

Remote laboratories (RLs) have become increasingly seen as a useful tool in supporting flexible shared access to scarce laboratory resources. An important element in supporting shared access is coordinating the scheduling of the laboratory usage. Optimized scheduling can significantly decrease access waiting times and improve the utilization level…

Exploring Cloud Computing for Distance Learning

ERIC Educational Resources Information Center

He, Wu; Cernusca, Dan; Abdous, M'hammed

2011-01-01

The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

Soil erosion and organic matter variations for central Great Plains cropping systems under residue removal

USDA-ARS?s Scientific Manuscript database

The diversity of geo-climatic land bases and potential feedstocks within the United States Central Great Plains (CGP) requires sustainable production that provides optimal resource utilization while maintaining or enhancing localized soil and environmental quality as much as possible. This study exa...

Dataset: Soil erosion and organic matter for central Great Plains cropping systems under residue removal

USDA-ARS?s Scientific Manuscript database

The diversity of geo-climatic land bases and potential feedstocks within the United States Central Great Plains (CGP) requires sustainable production that provides optimal resource utilization while maintaining or enhancing localized soil and environmental quality as much as possible. This study exa...

A hybrid system dynamics and optimization approach for supporting sustainable water resources planning in Zhengzhou City, China

NASA Astrophysics Data System (ADS)

Li, Zhi; Li, Chunhui; Wang, Xuan; Peng, Cong; Cai, Yanpeng; Huang, Weichen

2018-01-01

Problems with water resources restrict the sustainable development of a city with water shortages. Based on system dynamics (SD) theory, a model of sustainable utilization of water resources using the STELLA software has been established. This model consists of four subsystems: population system, economic system, water supply system and water demand system. The boundaries of the four subsystems are vague, but they are closely related and interdependent. The model is applied to Zhengzhou City, China, which has a serious water shortage. The difference between the water supply and demand is very prominent in Zhengzhou City. The model was verified with data from 2009 to 2013. The results show that water demand of Zhengzhou City will reach 2.57 billion m3 in 2020. A water resources optimization model is developed based on interval-parameter two-stage stochastic programming. The objective of the model is to allocate water resources to each water sector and make the lowest cost under the minimum water demand. Using the simulation results, decision makers can easily weigh the costs of the system, the water allocation objectives, and the system risk. The hybrid system dynamics method and optimization model is a rational try to support water resources management in many cities, particularly for cities with potential water shortage and it is solidly supported with previous studies and collected data.

Theoretical Calculations on the Feasibility of Microalgal Biofuels: Utilization of Marine Resources Could Help Realizing the Potential of Microalgae

PubMed Central

Park, Hanwool

2016-01-01

Abstract Microalgae have long been considered as one of most promising feedstocks with better characteristics for biofuels production over conventional energy crops. There have been a wide range of estimations on the feasibility of microalgal biofuels based on various productivity assumptions and data from different scales. The theoretical maximum algal biofuel productivity, however, can be calculated by the amount of solar irradiance and photosynthetic efficiency (PE), assuming other conditions are within the optimal range. Using the actual surface solar irradiance data around the world and PE of algal culture systems, maximum algal biomass and biofuel productivities were calculated, and feasibility of algal biofuel were assessed with the estimation. The results revealed that biofuel production would not easily meet the economic break‐even point and may not be sustainable at a large‐scale with the current algal biotechnology. Substantial reductions in the production cost, improvements in lipid productivity, recycling of resources, and utilization of non‐conventional resources will be necessary for feasible mass production of algal biofuel. Among the emerging technologies, cultivation of microalgae in the ocean shows great potentials to meet the resource requirements and economic feasibility in algal biofuel production by utilizing various marine resources. PMID:27782372

Theoretical Calculations on the Feasibility of Microalgal Biofuels: Utilization of Marine Resources Could Help Realizing the Potential of Microalgae.

PubMed

Park, Hanwool; Lee, Choul-Gyun

2016-11-01

Microalgae have long been considered as one of most promising feedstocks with better characteristics for biofuels production over conventional energy crops. There have been a wide range of estimations on the feasibility of microalgal biofuels based on various productivity assumptions and data from different scales. The theoretical maximum algal biofuel productivity, however, can be calculated by the amount of solar irradiance and photosynthetic efficiency (PE), assuming other conditions are within the optimal range. Using the actual surface solar irradiance data around the world and PE of algal culture systems, maximum algal biomass and biofuel productivities were calculated, and feasibility of algal biofuel were assessed with the estimation. The results revealed that biofuel production would not easily meet the economic break-even point and may not be sustainable at a large-scale with the current algal biotechnology. Substantial reductions in the production cost, improvements in lipid productivity, recycling of resources, and utilization of non-conventional resources will be necessary for feasible mass production of algal biofuel. Among the emerging technologies, cultivation of microalgae in the ocean shows great potentials to meet the resource requirements and economic feasibility in algal biofuel production by utilizing various marine resources. © 2016 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machine (M2M) Communications.

PubMed

Li, Ning; Cao, Chao; Wang, Cong

2017-06-15

Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them.

Optimal throughput for cognitive radio with energy harvesting in fading wireless channel.

PubMed

Vu-Van, Hiep; Koo, Insoo

2014-01-01

Energy resource management is a crucial problem of a device with a finite capacity battery. In this paper, cognitive radio is considered to be a device with an energy harvester that can harvest energy from a non-RF energy resource while performing other actions of cognitive radio. Harvested energy will be stored in a finite capacity battery. At the start of the time slot of cognitive radio, the radio needs to determine if it should remain silent or carry out spectrum sensing based on the idle probability of the primary user and the remaining energy in order to maximize the throughput of the cognitive radio system. In addition, optimal sensing energy and adaptive transmission power control are also investigated in this paper to effectively utilize the limited energy of cognitive radio. Finding an optimal approach is formulated as a partially observable Markov decision process. The simulation results show that the proposed optimal decision scheme outperforms the myopic scheme in which current throughput is only considered when making a decision.

Optimizing latency in Xilinx FPGA implementations of the GBT

NASA Astrophysics Data System (ADS)

Muschter, S.; Baron, S.; Bohm, C.; Cachemiche, J.-P.; Soos, C.

2010-12-01

The GigaBit Transceiver (GBT) [1] system has been developed to replace the Timing, Trigger and Control (TTC) system [2], currently used by LHC, as well as to provide data transmission between on-detector and off-detector components in future sLHC detectors. A VHDL version of the GBT-SERDES, designed for FPGAs, was released in March 2010 as a GBT-FPGA Starter Kit for future GBT users and for off-detector GBT implementation [3]. This code was optimized for resource utilization [4], as the GBT protocol is very demanding. It was not, however, optimized for latency — which will be a critical parameter when used in the trigger path. The GBT-FPGA Starter Kit firmware was first analyzed in terms of latency by looking at the separate components of the VHDL version. Once the parts which contribute most to the latency were identified and modified, two possible optimizations were chosen, resulting in a latency reduced by a factor of three. The modifications were also analyzed in terms of logic utilization. The latency optimization results were compared with measurement results from a Virtex 6 ML605 development board [5] equipped with a XC6VLX240T with speedgrade-1 and the package FF1156. Bit error rate tests were also performed to ensure an error free operation. The two final optimizations were analyzed for utilization and compared with the original code, distributed in the Starter Kit.

Real-time information management environment (RIME)

NASA Astrophysics Data System (ADS)

DeCleene, Brian T.; Griffin, Sean; Matchett, Garry; Niejadlik, Richard

2000-08-01

Whereas data mining and exploitation improve the quality and quantity of information available to the user, there remains a mission requirement to assist the end-user in managing the access to this information and ensuring that the appropriate information is delivered to the right user in time to make decisions and take action. This paper discusses TASC's federated architecture to next- generation information management, contrasts the approach against emerging technologies, and quantifies the performance gains. This architecture and implementation, known as Real-time Information Management Environment (RIME), is based on two key concepts: information utility and content-based channelization. The introduction of utility allows users to express the importance and delivery requirements of their information needs in the context of their mission. Rather than competing for resources on a first-come/first-served basis, the infrastructure employs these utility functions to dynamically react to unanticipated loading by optimizing the delivered information utility. Furthermore, commander's resource policies shape these functions to ensure that resources are allocated according to military doctrine. Using information about the desired content, channelization identifies opportunities to aggregate users onto shared channels reducing redundant transmissions. Hence, channelization increases the information throughput of the system and balances sender/receiver processing load.

An integrated model of water resources optimization allocation based on projection pursuit model - Grey wolf optimization method in a transboundary river basin

NASA Astrophysics Data System (ADS)

Yu, Sen; Lu, Hongwei

2018-04-01

Under the effects of global change, water crisis ranks as the top global risk in the future decade, and water conflict in transboundary river basins as well as the geostrategic competition led by it is most concerned. This study presents an innovative integrated PPMGWO model of water resources optimization allocation in a transboundary river basin, which is integrated through the projection pursuit model (PPM) and Grey wolf optimization (GWO) method. This study uses the Songhua River basin and 25 control units as examples, adopting the PPMGWO model proposed in this study to allocate the water quantity. Using water consumption in all control units in the Songhua River basin in 2015 as reference to compare with optimization allocation results of firefly algorithm (FA) and Particle Swarm Optimization (PSO) algorithms as well as the PPMGWO model, results indicate that the average difference between corresponding allocation results and reference values are 0.195 bil m3, 0.151 bil m3, and 0.085 bil m3, respectively. Obviously, the average difference of the PPMGWO model is the lowest and its optimization allocation result is closer to reality, which further confirms the reasonability, feasibility, and accuracy of the PPMGWO model. And then the PPMGWO model is adopted to simulate allocation of available water quantity in Songhua River basin in 2018, 2020, and 2030. The simulation results show water quantity which could be allocated in all controls demonstrates an overall increasing trend with reasonable and equal exploitation and utilization of water resources in the Songhua River basin in future. In addition, this study has a certain reference value and application meaning to comprehensive management and water resources allocation in other transboundary river basins.

Estimating Origin-Destination Matrices Using AN Efficient Moth Flame-Based Spatial Clustering Approach

NASA Astrophysics Data System (ADS)

Heidari, A. A.; Moayedi, A.; Abbaspour, R. Ali

2017-09-01

Automated fare collection (AFC) systems are regarded as valuable resources for public transport planners. In this paper, the AFC data are utilized to analysis and extract mobility patterns in a public transportation system. For this purpose, the smart card data are inserted into a proposed metaheuristic-based aggregation model and then converted to O-D matrix between stops, since the size of O-D matrices makes it difficult to reproduce the measured passenger flows precisely. The proposed strategy is applied to a case study from Haaglanden, Netherlands. In this research, moth-flame optimizer (MFO) is utilized and evaluated for the first time as a new metaheuristic algorithm (MA) in estimating transit origin-destination matrices. The MFO is a novel, efficient swarm-based MA inspired from the celestial navigation of moth insects in nature. To investigate the capabilities of the proposed MFO-based approach, it is compared to methods that utilize the K-means algorithm, gray wolf optimization algorithm (GWO) and genetic algorithm (GA). The sum of the intra-cluster distances and computational time of operations are considered as the evaluation criteria to assess the efficacy of the optimizers. The optimality of solutions of different algorithms is measured in detail. The traveler's behavior is analyzed to achieve to a smooth and optimized transport system. The results reveal that the proposed MFO-based aggregation strategy can outperform other evaluated approaches in terms of convergence tendency and optimality of the results. The results show that it can be utilized as an efficient approach to estimating the transit O-D matrices.

An integrated decision support system for TRAC: A proposal

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

1991-01-01

Optimal allocation and usage of resources is a key to effective management. Resources of concern to TRAC are: Manpower (PSY), Money (Travel, contracts), Computing, Data, Models, etc. Management activities of TRAC include: Planning, Programming, Tasking, Monitoring, Updating, and Coordinating. Existing systems are insufficient, not completely automated, manpower intensive, and has the potential for data inconsistency exists. A system is proposed which suggests a means to integrate all project management activities of TRAC through the development of a sophisticated software and by utilizing the existing computing systems and network resources. The systems integration proposal is examined in detail.

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

PubMed Central

Doebbeling, Bradley N.; Burton, Matthew M.; Wiebke, Eric A.; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction. PMID:23304284

Optimizing perioperative decision making: improved information for clinical workflow planning.

PubMed

Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks

NASA Astrophysics Data System (ADS)

Liao, Wei-Cheng; Hong, Mingyi; Liu, Ya-Feng; Luo, Zhi-Quan

2014-08-01

In a densely deployed heterogeneous network (HetNet), the number of pico/micro base stations (BS) can be comparable with the number of the users. To reduce the operational overhead of the HetNet, proper identification of the set of serving BSs becomes an important design issue. In this work, we show that by jointly optimizing the transceivers and determining the active set of BSs, high system resource utilization can be achieved with only a small number of BSs. In particular, we provide formulations and efficient algorithms for such joint optimization problem, under the following two common design criteria: i) minimization of the total power consumption at the BSs, and ii) maximization of the system spectrum efficiency. In both cases, we introduce a nonsmooth regularizer to facilitate the activation of the most appropriate BSs. We illustrate the efficiency and the efficacy of the proposed algorithms via extensive numerical simulations.

Energy and water quality management systems for water utility's operations: a review.

PubMed

Cherchi, Carla; Badruzzaman, Mohammad; Oppenheimer, Joan; Bros, Christopher M; Jacangelo, Joseph G

2015-04-15

Holistic management of water and energy resources is critical for water utilities facing increasing energy prices, water supply shortage and stringent regulatory requirements. In the early 1990s, the concept of an integrated Energy and Water Quality Management System (EWQMS) was developed as an operational optimization framework for solving water quality, water supply and energy management problems simultaneously. Approximately twenty water utilities have implemented an EWQMS by interfacing commercial or in-house software optimization programs with existing control systems. For utilities with an installed EWQMS, operating cost savings of 8-15% have been reported due to higher use of cheaper tariff periods and better operating efficiencies, resulting in the reduction in energy consumption of ∼6-9%. This review provides the current state-of-knowledge on EWQMS typical structural features and operational strategies and benefits and drawbacks are analyzed. The review also highlights the challenges encountered during installation and implementation of EWQMS and identifies the knowledge gaps that should motivate new research efforts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Low-Temperature Utilization of Geothermal Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Brian

Full realization of the potential of what might be considered “low-grade” geothermal resources will require that we examine many more uses for the heat than traditional electricity generation. To demonstrate that geothermal energy truly has the potential to be a national energy source we will be designing, assessing, and evaluating innovative uses for geothermal-produced water such as hybrid biomass-geothermal cogeneration of electricity and district heating and efficiency improvements to the use of cellulosic biomass in addition to utilization of geothermal in district heating for community redevelopment projects. The objectives of this project were: 1) to perform a techno-economic analysis ofmore » the integration and utilization potential of low-temperature geothermal sources. Innovative uses of low-enthalpy geothermal water were designed and examined for their ability to offset fossil fuels and decrease CO2 emissions. 2) To perform process optimizations and economic analyses of processes that can utilize low-temperature geothermal fluids. These processes included electricity generation using biomass and district heating systems. 3) To scale up and generalize the results of three case study locations to develop a regionalized model of the utilization of low-temperature geothermal resources. A national-level, GIS-based, low-temperature geothermal resource supply model was developed and used to develop a series of national supply curves. We performed an in-depth analysis of the low-temperature geothermal resources that dominate the eastern half of the United States. The final products of this study include 17 publications, an updated version of the cost estimation software GEOPHIRES, and direct-use supply curves for low-temperature utilization of geothermal resources. The supply curves for direct use geothermal include utilization from known hydrothermal, undiscovered hydrothermal, and near-hydrothermal EGS resources and presented these results at the Stanford Geothermal Workshop. We also have incorporated our wellbore model into TOUGH2-EGS and began coding TOUGH2-EGS with the wellbore model into GEOPHIRES as a reservoir thermal drawdown option. Additionally, case studies for the WVU and Cornell campuses were performed to assess the potential for district heating and cooling at these two eastern U.S. sites.« less

Overrepresentation of extreme events in decision making reflects rational use of cognitive resources.

PubMed

Lieder, Falk; Griffiths, Thomas L; Hsu, Ming

2018-01-01

People's decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision makers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision makers should overrepresent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account, we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people's availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Performance evaluation of multi-stratum resources integration based on network function virtualization in software defined elastic data center optical interconnect.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tian, Rui; Han, Jianrui; Lee, Young

2015-11-30

Data center interconnect with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented multi-stratum resilience between IP and elastic optical networks that allows to accommodate data center services. In view of this, this study extends to consider the resource integration by breaking the limit of network device, which can enhance the resource utilization. We propose a novel multi-stratum resources integration (MSRI) architecture based on network function virtualization in software defined elastic data center optical interconnect. A resource integrated mapping (RIM) scheme for MSRI is introduced in the proposed architecture. The MSRI can accommodate the data center services with resources integration when the single function or resource is relatively scarce to provision the services, and enhance globally integrated optimization of optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of OpenFlow-based enhanced software defined networking (eSDN) testbed. The performance of RIM scheme under heavy traffic load scenario is also quantitatively evaluated based on MSRI architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning schemes.

Optimal glucose management in the perioperative period.

PubMed

Evans, Charity H; Lee, Jane; Ruhlman, Melissa K

2015-04-01

Hyperglycemia is a common finding in surgical patients during the perioperative period. Factors contributing to poor glycemic control include counterregulatory hormones, hepatic insulin resistance, decreased insulin-stimulated glucose uptake, use of dextrose-containing intravenous fluids, and enteral and parenteral nutrition. Hyperglycemia in the perioperative period is associated with increased morbidity, decreased survival, and increased resource utilization. Optimal glucose management in the perioperative period contributes to reduced morbidity and mortality. To readily identify hyperglycemia, blood glucose monitoring should be instituted for all hospitalized patients. Published by Elsevier Inc.

TeleProbe: design and development of an efficient system for telepathology

NASA Astrophysics Data System (ADS)

Ahmed, Wamiq M.; Robinson, J. Paul; Ghafoor, Arif

2005-10-01

This paper describes an internet-based system for telepathology. This system provides support for multiple users and exploits the opportunities for optimization that arise in multi-user environment. Techniques for increasing system responsiveness by improving resource utilization and lowering network traffic are explored. Some of the proposed optimizations include an auto-focus module, client and server side caching, and request reordering. These systems can be an economic solution not only for remote pathology consultation but also for pathology and biology education.

Simulation Tool for Optimizing Non-Combatant Evacuation (STONE): Optimization of Evacuation Time and Transportation Resource Utilization

DTIC Science & Technology

2015-05-01

2015 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2015 Abstract A Non-Combatant Evacuation...Standing Senate Committee on Foreign Affairs and International Trade recommended that more frequent assessments of NEO plans be conducted...étrangères et du commerce international a recommandé que des évaluations dans ses missions à l’étranger soient faites plus fréquemment

The state of autotrophic ethanol production in Cyanobacteria.

PubMed

Dexter, J; Armshaw, P; Sheahan, C; Pembroke, J T

2015-07-01

Ethanol production directly from CO2 , utilizing genetically engineered photosynthetic cyanobacteria as a biocatalyst, offers significant potential as a renewable and sustainable source of biofuel. Despite the current absence of a commercially successful production system, significant resources have been deployed to realize this goal. Utilizing the pyruvate decarboxylase from Zymomonas species, metabolically derived pyruvate can be converted to ethanol. This review of both peer-reviewed and patent literature focuses on the genetic modifications utilized for metabolic engineering and the resultant effect on ethanol yield. Gene dosage, induced expression and cassette optimizat-ion have been analyzed to optimize production, with production rates of 0·1-0·5 g L(-1) day(-1) being achieved. The current 'toolbox' of molecular manipulations and future directions focusing on applicability, addressing the primary challenges facing commercialization of cyanobacterial technologies are discussed. © 2015 The Society for Applied Microbiology.

Filter Media Tests Under Simulated Martian Atmospheric Conditions

NASA Technical Reports Server (NTRS)

Agui, Juan H.

2016-01-01

Human exploration of Mars will require the optimal utilization of planetary resources. One of its abundant resources is the Martian atmosphere that can be harvested through filtration and chemical processes that purify and separate it into its gaseous and elemental constituents. Effective filtration needs to be part of the suite of resource utilization technologies. A unique testing platform is being used which provides the relevant operational and instrumental capabilities to test articles under the proper simulated Martian conditions. A series of tests were conducted to assess the performance of filter media. Light sheet imaging of the particle flow provided a means of detecting and quantifying particle concentrations to determine capturing efficiencies. The media's efficiency was also evaluated by gravimetric means through a by-layer filter media configuration. These tests will help to establish techniques and methods for measuring capturing efficiency and arrestance of conventional fibrous filter media. This paper will describe initial test results on different filter media.

Predicting hospital visits from geo-tagged Internet search logs.

PubMed

Agarwal, Vibhu; Han, Lichy; Madan, Isaac; Saluja, Shaurya; Shidham, Aaditya; Shah, Nigam H

2016-01-01

The steady rise in healthcare costs has deprived over 45 million Americans of healthcare services (1, 2) and has encouraged healthcare providers to look for opportunities to improve their operational efficiency. Prior studies have shown that evidence of healthcare seeking intent in Internet searches correlates well with healthcare resource utilization. Given the ubiquitous nature of mobile Internet search, we hypothesized that analyzing geo-tagged mobile search logs could enable us to machine-learn predictors of future patient visits. Using a de-identified dataset of geo-tagged mobile Internet search logs, we mined text and location patterns that are predictors of healthcare resource utilization and built statistical models that predict the probability of a user's future visit to a medical facility. Our efforts will enable the development of innovative methods for modeling and optimizing the use of healthcare resources-a crucial prerequisite for securing healthcare access for everyone in the days to come.

Integrating Hospital Administrative Data to Improve Health Care Efficiency and Outcomes: “The Socrates Story”

PubMed Central

Lawrence, Justin; Delaney, Conor P.

2013-01-01

Evaluation of health care outcomes has become increasingly important as we strive to improve quality and efficiency while controlling cost. Many groups feel that analysis of large datasets will be useful in optimizing resource utilization; however, the ideal blend of clinical and administrative data points has not been developed. Hospitals and health care systems have several tools to measure cost and resource utilization, but the data are often housed in disparate systems that are not integrated and do not permit multisystem analysis. Systems Outcomes and Clinical Resources AdministraTive Efficiency Software (SOCRATES) is a novel data merging, warehousing, analysis, and reporting technology, which brings together disparate hospital administrative systems generating automated or customizable risk-adjusted reports. Used in combination with standardized enhanced care pathways, SOCRATES offers a mechanism to improve the quality and efficiency of care, with the ability to measure real-time changes in outcomes. PMID:24436649

Integrating hospital administrative data to improve health care efficiency and outcomes: "the socrates story".

PubMed

Lawrence, Justin; Delaney, Conor P

2013-03-01

Evaluation of health care outcomes has become increasingly important as we strive to improve quality and efficiency while controlling cost. Many groups feel that analysis of large datasets will be useful in optimizing resource utilization; however, the ideal blend of clinical and administrative data points has not been developed. Hospitals and health care systems have several tools to measure cost and resource utilization, but the data are often housed in disparate systems that are not integrated and do not permit multisystem analysis. Systems Outcomes and Clinical Resources AdministraTive Efficiency Software (SOCRATES) is a novel data merging, warehousing, analysis, and reporting technology, which brings together disparate hospital administrative systems generating automated or customizable risk-adjusted reports. Used in combination with standardized enhanced care pathways, SOCRATES offers a mechanism to improve the quality and efficiency of care, with the ability to measure real-time changes in outcomes.

To Determine the Method of Scheduling Surgery to Optimize Utilization of Surgical Resources at Landstuhl Army Regional Medical Center

DTIC Science & Technology

1984-05-01

exceed one manyear. 5. The new scheduling system will be more responsive to the dynanic forces that affect the use of surgical resources. a. Elective...will be removed when the OR is relocated to the new addition (see Figure 3 for floor design of future OR location). The OR Scheduling System The days of...obtaining new appointment openings. This would insure that the names on the waiting list are rotating regularly. Identified Problems With The Current

PTBS segmentation scheme for synthetic aperture radar

NASA Astrophysics Data System (ADS)

Friedland, Noah S.; Rothwell, Brian J.

1995-07-01

The Image Understanding Group at Martin Marietta Technologies in Denver, Colorado has developed a model-based synthetic aperture radar (SAR) automatic target recognition (ATR) system using an integrated resource architecture (IRA). IRA, an adaptive Markov random field (MRF) environment, utilizes information from image, model, and neighborhood resources to create a discrete, 2D feature-based world description (FBWD). The IRA FBWD features are peak, target, background and shadow (PTBS). These features have been shown to be very useful for target discrimination. The FBWD is used to accrue evidence over a model hypothesis set. This paper presents the PTBS segmentation process utilizing two IRA resources. The image resource (IR) provides generic (the physics of image formation) and specific (the given image input) information. The neighborhood resource (NR) provides domain knowledge of localized FBWD site behaviors. A simulated annealing optimization algorithm is used to construct a `most likely' PTBS state. Results on simulated imagery illustrate the power of this technique to correctly segment PTBS features, even when vehicle signatures are immersed in heavy background clutter. These segmentations also suppress sidelobe effects and delineate shadows.

Geometric Design of Scalable Forward Scatterers for Optimally Efficient Solar Transformers.

PubMed

Kim, Hye-Na; Vahidinia, Sanaz; Holt, Amanda L; Sweeney, Alison M; Yang, Shu

2017-11-01

It will be ideal to deliver equal, optimally efficient "doses" of sunlight to all cells in a photobioreactor system, while simultaneously utilizing the entire solar resource. Backed by the numerical scattering simulation and optimization, here, the design, synthesis, and characterization of the synthetic iridocytes that recapitulated the salient forward-scattering behavior of the Tridacnid clam system are reported, which presents the first geometric solution to allow narrow, precise forward redistribution of flux, utilizing the solar resource at the maximum quantum efficiency possible in living cells. The synthetic iridocytes are composed of silica nanoparticles in microspheres embedded in gelatin, both are low refractive index materials and inexpensive. They show wavelength selectivity, have little loss (the back-scattering intensity is reduced to less than ≈0.01% of the forward-scattered intensity), and narrow forward scattering cone similar to giant clams. Moreover, by comparing experiments and theoretical calculation, it is confirmed that the nonuniformity of the scatter sizes is a "feature not a bug" of the design, allowing for efficient, forward redistribution of solar flux in a micrometer-scaled paradigm. This method is environmentally benign, inexpensive, and scalable to produce optical components that will find uses in efficiency-limited solar conversion technologies, heat sinks, and biofuel production. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Workflow-based Intelligent Network Data Movement Advisor with End-to-end Performance Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Michelle M.; Wu, Chase Q.

2013-11-07

Next-generation eScience applications often generate large amounts of simulation, experimental, or observational data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate such massive data transfer. However, these technologies and services have not been fully utilized mainly because their use typically requires significant domain knowledge and in many cases application users are even not aware of their existence. By leveraging the functionalities of an existing Network-Aware Data Movement Advisor (NADMA) utility, we propose a new Workflow-based Intelligent Network Data Movement Advisor (WINDMA) with end-to-end performance optimization formore » this DOE funded project. This WINDMA system integrates three major components: resource discovery, data movement, and status monitoring, and supports the sharing of common data movement workflows through account and database management. This system provides a web interface and interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP and GlobusOnline, and network resource provisioning brokers such as ION and OSCARS. We demonstrate the efficacy of the proposed transport-support workflow system in several use cases based on its implementation and deployment in DOE wide-area networks.« less

Research on evaluating water resource resilience based on projection pursuit classification model

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhao, Dan; Liang, Xu; Wu, Qiuchen

2016-03-01

Water is a fundamental natural resource while agriculture water guarantees the grain output, which shows that the utilization and management of water resource have a significant practical meaning. Regional agricultural water resource system features with unpredictable, self-organization, and non-linear which lays a certain difficulty on the evaluation of regional agriculture water resource resilience. The current research on water resource resilience remains to focus on qualitative analysis and the quantitative analysis is still in the primary stage, thus, according to the above issues, projection pursuit classification model is brought forward. With the help of artificial fish-swarm algorithm (AFSA), it optimizes the projection index function, seeks for the optimal projection direction, and improves AFSA with the application of self-adaptive artificial fish step and crowding factor. Taking Hongxinglong Administration of Heilongjiang as the research base and on the basis of improving AFSA, it established the evaluation of projection pursuit classification model to agriculture water resource system resilience besides the proceeding analysis of projection pursuit classification model on accelerating genetic algorithm. The research shows that the water resource resilience of Hongxinglong is the best than Raohe Farm, and the last 597 Farm. And the further analysis shows that the key driving factors influencing agricultural water resource resilience are precipitation and agriculture water consumption. The research result reveals the restoring situation of the local water resource system, providing foundation for agriculture water resource management.

Strategic plan to optimize the management of right-of-way parcel and utility information at FDOT : [research summary].

DOT National Transportation Integrated Search

2013-05-01

The Florida Department of Transportation (FDOT) manages more than 12,000 centerline-miles of highway that run through hundreds of jurisdictions. The right-of-way (ROW) that these roads are built on is a massive and complex resource in its own right a...

Chantey Castings: A Hands-On Simulation to Teach Constraint Management and Demand-Driven Supply Chain Approaches

ERIC Educational Resources Information Center

Grandzol, Christian J.; Grandzol, John R.

2018-01-01

Supply chain design and constraint management are widely-adopted techniques in industry, necessitating that operations and supply chain educators teach these topics in ways that enhance student learning and retention, optimize resource utilization (especially time), and maximize student interest. The Chantey Castings Simulation provides a platform…

Staff Perceptions of E-Learning in a Community Health Care Organization

ERIC Educational Resources Information Center

Gabriel, Monica; Longman, Sandra

2004-01-01

How do organizations cope with the increased speed of technological change? How do leaders optimize resources with tightened budgets? How do staff and students acquire the necessary knowledge and skills in the midst of constant change? Electronic learning (e-learning) is one form of learning that utilizes technology to deliver, interact or…

Product costing program for wood component manufacturers

Treesearch

Adrienn Andersch; Urs Buehlmann; Jeff Palmer; Janice K Wiedenbeck; Steve Lawser

2013-01-01

Accurate and timely product costing information is critically important for companies in planning the optimal utilization of company resources. While an overestimation of product costs can lead to loss of potential business and market share, underestimation of product costs can result in financial losses to the company. This article introduces a product costing program...

Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

NASA Astrophysics Data System (ADS)

Shaat, Musbah; Bader, Faouzi

2010-12-01

Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

Performance evaluation of data center service localization based on virtual resource migration in software defined elastic optical network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tan, Yuanlong; Lin, Yi; Han, Jianrui; Lee, Young

2015-09-07

Data center interconnection with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate data center services. In view of this, this study extends the data center resources to user side to enhance the end-to-end quality of service. We propose a novel data center service localization (DCSL) architecture based on virtual resource migration in software defined elastic data center optical network. A migration evaluation scheme (MES) is introduced for DCSL based on the proposed architecture. The DCSL can enhance the responsiveness to the dynamic end-to-end data center demands, and effectively reduce the blocking probability to globally optimize optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of our OpenFlow-based enhanced SDN testbed. The performance of MES scheme under heavy traffic load scenario is also quantitatively evaluated based on DCSL architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning scheme.

Energy-water-food nexus under financial constraint environment: good, the bad, and the ugly sustainability reforms in sub-Saharan African countries.

PubMed

Zaman, Khalid; Shamsuddin, Sadaf; Ahmad, Mehboob

2017-05-01

Environmental sustainability agenda are generally compromised by energy, water, and food production resources, while in the recent waves of global financial crisis, it mediates to increase the intensity of air pollutants, which largely affected the less developing countries due to their ease of environmental regulation policies and lack of optimal utilization of economic resources. Sub-Saharan African (SSA) countries are no exception that majorly hit by the recent global financial crisis, which affected the country's natural environment through the channel of unsustainable energy-water-food production. The study employed panel random effect model that addresses the country-specific time-invariant shocks to examine the non-linear relationship between water-energy-food resources and air pollutants in a panel of 19 selected SSA countries, for a period of 2000-2014. The results confirmed the carbon-fossil-methane environmental Kuznets curve (EKC) that turned into inverted U-shaped relationships in a panel of selected SSA countries. Food resources largely affected greenhouse gas (GHG), methane (CH 4 ), and nitrous oxide (N 2 O) emissions while water resource decreases carbon dioxide (CO 2 ), fossil fuel, and CH 4 emissions in a region. Energy efficiency improves air quality indicators while industry value added increases CO 2 emissions, fossil fuel energy, and GHG emissions. Global financial crisis increases the risk of climate change across countries. The study concludes that although SSA countries strive hard to take some "good" initiatives to reduce environmental degradation in a form of improved water and energy sources, however, due to lack of optimal utilization of food resources and global financial constraints, it leads to "the bad" and "the ugly" sustainability reforms in a region.

The role of information and communication technology in developing smart education

NASA Astrophysics Data System (ADS)

Roslina; Zarlis, Muhammad; Mawengkang, Herman; Sembiring, R. W.

2017-09-01

The right to get a proper education for every citizen had been regulated by the government, but not all citizens have the same opportunity. This is due to the other factors in the nation's infrastructure, Frontier, Outermost, and Disadvantaged (3T) which have not beenaccomodatedto access information and communication technology (ICT), and the ideal learning environment in order to pursue knowledge. This condition could be achieved by reforming higher education. Such reforms include the provision of educational services in the form of a flexible learner-oriented, and to change the curriculum with market based.These changes would include the provision of lecturers, professors, and professional teaching force. Another important effort is to update the quality of higher education with resource utilization. This paper proposes a new education business model to realize the Smart Education (SE), with an orientation on the proven skills and competitive.SE is the higher education system to optimize output (outcome) learning with combine individual learning and collaboration techniques based network system, informal practice learning and formal theory. UtilizingICT resources can improve the quality and access to higher education in supporting activities of higher education.This paper shows that ICT resources can support virtual connected with the use of shared resources, such as resource of information, learning resources, computing resources, and human resources.

Assessment of nursing management and utilization of nursing resources with the RAFAELA patient classification system--case study from the general wards of one central hospital.

PubMed

Rainio, Anna-Kaisa; Ohinmaa, Arto E

2005-07-01

RAFAELA is a new Finnish PCS, which is used in several University Hospitals and Central Hospitals and has aroused considerable interest in hospitals in Europe. The aim of the research is firstly to assess the feasibility of the RAFAELA Patient Classification System (PCS) in nursing staff management and, secondly, whether it can be seen as the transferring of nursing resources between wards according to the information received from nursing care intensity classification. The material was received from the Central Hospital's 12 general wards between 2000 and 2001. The RAFAELA PCS consists of three different measures: a system measuring patient care intensity, a system recording daily nursing resources, and a system measuring the optimal nursing care intensity/nurse situation. The data were analysed in proportion to the labour costs of nursing work and, from that, we calculated the employer's loss (a situation below the optimal level) and savings (a situation above the optimal level) per ward as both costs and the number of nurses. In 2000 the wards had on average 77 days below the optimal level and 106 days above it. In 2001 the wards had on average 71 days below the optimal level and 129 above it. Converting all these days to monetary and personnel resources the employer lost 307,745 or 9.84 nurses and saved 369,080 or 11.80 nurses in total in 2000. In 2001 the employer lost in total 242,143 or 7.58 nurses and saved 457,615 or 14.32 nurses. During the time period of the research nursing resources seemed not have been transferred between wards. RAFAELA PCS is applicable to the allocation of nursing resources but its possibilities have not been entirely used in the researched hospital. The management of nursing work should actively use the information received in nursing care intensity classification and plan and implement the transferring of nursing resources in order to ensure the quality of patient care. Information on which units resources should be allocated to is needed in the planning of staff resources of the whole hospital. More resources do not solve the managerial problem of the right allocation of resources. If resources are placed wrongly, the problems of daily staff management and cost control continue.

Efficient Resources Provisioning Based on Load Forecasting in Cloud

PubMed Central

Hu, Rongdong; Jiang, Jingfei; Liu, Guangming; Wang, Lixin

2014-01-01

Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application's actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements. PMID:24701160

Pediatric acute sinusitis: predictors of increased resource utilization.

PubMed

Dugar, Deepak R; Lander, Lina; Mahalingam-Dhingra, Aditya; Shah, Rahul K

2010-11-01

To determine variations in resource utilization in the management of pediatric acute sinusitis. Retrospective analysis of a publicly available national dataset. The Kids' Inpatient Database 2006 was analyzed using ICD-9 codes for acute sinusitis. A total of 8,381 patients (55% male, mean age 8.5 years [SE = 0.2]) were admitted with acute sinusitis. Mean total charges was $20,062 (SE = 1,159.1). Mean length of stay was 4.2 days (SE = 0.12), with 4.8 diagnoses (SE = 0.06) and 0.85 procedures (SE = 0.06). Thirty-six percent had concomitant respiratory diseases, 11% otitis media, and 8% orbital symptoms. A total of 703 patients underwent operations on the upper aerodigestive tract (534 were nasal sinusectomies); 582 patients underwent lumbar puncture and 162 underwent orbital surgery. The primary payer was private insurance in 50% and Medicaid in 41%. Predictors of increased total charges were male gender (P =.028), being a teaching hospital (P < .0001), metropolitan patient location (P < .0001), hospitals in the western region (P < .0001), admission source from another hospital (P < .0001), and discharge status to another inpatient hospital or home healthcare (P < .0001). There is a large geographic variation in resource utilization (range = $5,837 [Arkansas] to $48,327 [California]). Race, primary payer, admission type, and urgency were not significant predictors of increased resource utilization. Despite being a common diagnosis, there exists a large national variation in management of acute pediatric sinusitis. Predictors of increased resource utilization included male gender, teaching hospital status, metropolitan patient location, western hospital region, admission source, and discharge status. Knowledge of these variables may allow interventions and potentially facilitate benchmarking to reduce the economic burden of this entity while ensuring optimal outcomes.

Carbon and nutrient use efficiencies optimally balance stoichiometric imbalances

NASA Astrophysics Data System (ADS)

Manzoni, Stefano; Čapek, Petr; Lindahl, Björn; Mooshammer, Maria; Richter, Andreas; Šantrůčková, Hana

2016-04-01

Decomposer organisms face large stoichiometric imbalances because their food is generally poor in nutrients compared to the decomposer cellular composition. The presence of excess carbon (C) requires adaptations to utilize nutrients effectively while disposing of or investing excess C. As food composition changes, these adaptations lead to variable C- and nutrient-use efficiencies (defined as the ratios of C and nutrients used for growth over the amounts consumed). For organisms to be ecologically competitive, these changes in efficiencies with resource stoichiometry have to balance advantages and disadvantages in an optimal way. We hypothesize that efficiencies are varied so that community growth rate is optimized along stoichiometric gradients of their resources. Building from previous theories, we predict that maximum growth is achieved when C and nutrients are co-limiting, so that the maximum C-use efficiency is reached, and nutrient release is minimized. This optimality principle is expected to be applicable across terrestrial-aquatic borders, to various elements, and at different trophic levels. While the growth rate maximization hypothesis has been evaluated for consumers and predators, in this contribution we test it for terrestrial and aquatic decomposers degrading resources across wide stoichiometry gradients. The optimality hypothesis predicts constant efficiencies at low substrate C:N and C:P, whereas above a stoichiometric threshold, C-use efficiency declines and nitrogen- and phosphorus-use efficiencies increase up to one. Thus, high resource C:N and C:P lead to low C-use efficiency, but effective retention of nitrogen and phosphorus. Predictions are broadly consistent with efficiency trends in decomposer communities across terrestrial and aquatic ecosystems.

An Innovative Time-Cost-Quality Tradeoff Modeling of Building Construction Project Based on Resource Allocation

PubMed Central

2014-01-01

The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

NASA Astrophysics Data System (ADS)

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-28

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

PubMed Central

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-01-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes. PMID:27465296

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Optimal allocation of resources over health care programmes: dealing with decreasing marginal utility and uncertainty.

PubMed

Al, Maiwenn J; Feenstra, Talitha L; Hout, Ben A van

2005-07-01

This paper addresses the problem of how to value health care programmes with different ratios of costs to effects, specifically when taking into account that these costs and effects are uncertain. First, the traditional framework of maximising health effects with a given health care budget is extended to a flexible budget using a value function over money and health effects. Second, uncertainty surrounding costs and effects is included in the model using expected utility. Other approaches to uncertainty that do not specify a utility function are discussed and it is argued that these also include implicit notions about risk attitude.

Application of cooperative and non-cooperative games in large-scale water quantity and quality management: a case study.

PubMed

Mahjouri, Najmeh; Ardestani, Mojtaba

2011-01-01

In this paper, two cooperative and non-cooperative methodologies are developed for a large-scale water allocation problem in Southern Iran. The water shares of the water users and their net benefits are determined using optimization models having economic objectives with respect to the physical and environmental constraints of the system. The results of the two methodologies are compared based on the total obtained economic benefit, and the role of cooperation in utilizing a shared water resource is demonstrated. In both cases, the water quality in rivers satisfies the standards. Comparing the results of the two mentioned approaches shows the importance of acting cooperatively to achieve maximum revenue in utilizing a surface water resource while the river water quantity and quality issues are addressed.

Development of the framework for a water quality monitoring system : controlling MoDOT's contribution to 303(d) listed streams in the state of Missouri, final report, February 2010.

DOT National Transportation Integrated Search

2010-02-01

By utilizing ArcGIS to quickly visualize the location of any impaired waterbody in relation to its projects/activities, MoDOT will : be able to allocate resources optimally. Additionally, the Water Quality Impact Database (WQID) will allow easy trans...

A note on the modelling of circular smallholder migration.

PubMed

Bigsten, A

1988-01-01

"It is argued that circular migration [in Africa] should be seen as an optimization problem, where the household allocates its labour resources across activities, including work which requires migration, so as to maximize the joint family utility function. The migration problem is illustrated in a simple diagram, which makes it possible to analyse economic aspects of migration." excerpt

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

NASA Astrophysics Data System (ADS)

Wang, Shengling; Cui, Yong; Koodli, Rajeev; Hou, Yibin; Huang, Zhangqin

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClean, Jarrod R.; Kimchi-Schwartz, Mollie E.; Carter, Jonathan

Using quantum devices supported by classical computational resources is a promising approach to quantum-enabled computation. One powerful example of such a hybrid quantum-classical approach optimized for classically intractable eigenvalue problems is the variational quantum eigensolver, built to utilize quantum resources for the solution of eigenvalue problems and optimizations with minimal coherence time requirements by leveraging classical computational resources. These algorithms have been placed as leaders among the candidates for the first to achieve supremacy over classical computation. Here, we provide evidence for the conjecture that variational approaches can automatically suppress even nonsystematic decoherence errors by introducing an exactly solvable channelmore » model of variational state preparation. Moreover, we develop a more general hierarchy of measurement and classical computation that allows one to obtain increasingly accurate solutions by leveraging additional measurements and classical resources. In conclusion, we demonstrate numerically on a sample electronic system that this method both allows for the accurate determination of excited electronic states as well as reduces the impact of decoherence, without using any additional quantum coherence time or formal error-correction codes.« less

Transportation or CT scanners: a theory and method of health resources allocation.

PubMed Central

Greenwald, H P; Woodward, J M; Berg, D H

1979-01-01

Cost containment and access to appropriate care are the two most frequently discussed issues in contemporary health policy. Conceiving of the health services available in specific regions as "packages" of diverse items, the authors of this article consider the economic trade-offs among the various resources needed for appropriate care. In the discussion that follows, we examine the trade-offs between two divergent offering of the health care system: high technology medicine and support services. Specifically, we examine several strategies designed to achieve an optimal mix of investments in CT scanners and transportation resources in the South Chicago region. Using linear programming as a method for examining these options, the authors found that 1) the proper location of CT scanners is as important for cost containment as optimal number, and 2) excess capacity in the utilization of a single resource--CT scanners--need not imply inefficiency in the overall delivery of the service. These findings help demonstrate the importance of viewing health care as a package of interrelated services, both for achieving cost containment and for providing access to appropriate care. PMID:391772

Priority setting in health care: disentangling risk aversion from inequality aversion.

PubMed

Echazu, Luciana; Nocetti, Diego

2013-06-01

In this paper, we introduce a tractable social welfare function that is rich enough to disentangle attitudes towards risk in health outcomes from attitudes towards health inequalities across individuals. Given this preference specification, we evaluate how the introduction of uncertainty over the severity of illness and over the effectiveness of treatments affects the optimal allocation of healthcare resources. We show that the way in which uncertainty affects the optimal allocation within our proposed specification may differ sharply from that in the standard expected utility framework. Copyright © 2012 John Wiley & Sons, Ltd.

Improving Shipboard Decision Making in the CBR-D (Chemical/Biological Radiological Defense) Environment: Concepts of Use for and Functional Description of a Decision Aid/Training System (DECAID)

DTIC Science & Technology

1988-08-19

take place over the period of several days. Decisions regarding MOPP level or resource allocation made on day I may have no immediate impact, but a...present -- conditions, and manage a resource library to assist the DCA in making decisions under conditions of uncertainty. Several areas of utilization are...students work through a scenario, the device couid then display the consequences of those decisions or provide optimal decision recommendations

A Sampling-Based Bayesian Approach for Cooperative Multiagent Online Search With Resource Constraints.

PubMed

Xiao, Hu; Cui, Rongxin; Xu, Demin

2018-06-01

This paper presents a cooperative multiagent search algorithm to solve the problem of searching for a target on a 2-D plane under multiple constraints. A Bayesian framework is used to update the local probability density functions (PDFs) of the target when the agents obtain observation information. To obtain the global PDF used for decision making, a sampling-based logarithmic opinion pool algorithm is proposed to fuse the local PDFs, and a particle sampling approach is used to represent the continuous PDF. Then the Gaussian mixture model (GMM) is applied to reconstitute the global PDF from the particles, and a weighted expectation maximization algorithm is presented to estimate the parameters of the GMM. Furthermore, we propose an optimization objective which aims to guide agents to find the target with less resource consumptions, and to keep the resource consumption of each agent balanced simultaneously. To this end, a utility function-based optimization problem is put forward, and it is solved by a gradient-based approach. Several contrastive simulations demonstrate that compared with other existing approaches, the proposed one uses less overall resources and shows a better performance of balancing the resource consumption.

Influencing Busy People in a Social Network

PubMed Central

Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach. PMID:27711127

Influencing Busy People in a Social Network.

PubMed

Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach.

Layout design-based research on optimization and assessment method for shipbuilding workshop

NASA Astrophysics Data System (ADS)

Liu, Yang; Meng, Mei; Liu, Shuang

2013-06-01

The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance.

Network efficient power control for wireless communication systems.

PubMed

Campos-Delgado, Daniel U; Luna-Rivera, Jose Martin; Martinez-Sánchez, C J; Gutierrez, Carlos A; Tecpanecatl-Xihuitl, J L

2014-01-01

We introduce a two-loop power control that allows an efficient use of the overall power resources for commercial wireless networks based on cross-layer optimization. This approach maximizes the network's utility in the outer-loop as a function of the averaged signal to interference-plus-noise ratio (SINR) by considering adaptively the changes in the network characteristics. For this purpose, the concavity property of the utility function was verified with respect to the SINR, and an iterative search was proposed with guaranteed convergence. In addition, the outer-loop is in charge of selecting the detector that minimizes the overall power consumption (transmission and detection). Next the inner-loop implements a feedback power control in order to achieve the optimal SINR in the transmissions despite channel variations and roundtrip delays. In our proposal, the utility maximization process and detector selection and feedback power control are decoupled problems, and as a result, these strategies are implemented at two different time scales in the two-loop framework. Simulation results show that substantial utility gains may be achieved by improving the power management in the wireless network.

Network Efficient Power Control for Wireless Communication Systems

PubMed Central

Campos-Delgado, Daniel U.; Luna-Rivera, Jose Martin; Martinez-Sánchez, C. J.; Gutierrez, Carlos A.; Tecpanecatl-Xihuitl, J. L.

2014-01-01

We introduce a two-loop power control that allows an efficient use of the overall power resources for commercial wireless networks based on cross-layer optimization. This approach maximizes the network's utility in the outer-loop as a function of the averaged signal to interference-plus-noise ratio (SINR) by considering adaptively the changes in the network characteristics. For this purpose, the concavity property of the utility function was verified with respect to the SINR, and an iterative search was proposed with guaranteed convergence. In addition, the outer-loop is in charge of selecting the detector that minimizes the overall power consumption (transmission and detection). Next the inner-loop implements a feedback power control in order to achieve the optimal SINR in the transmissions despite channel variations and roundtrip delays. In our proposal, the utility maximization process and detector selection and feedback power control are decoupled problems, and as a result, these strategies are implemented at two different time scales in the two-loop framework. Simulation results show that substantial utility gains may be achieved by improving the power management in the wireless network. PMID:24683350

Research on agricultural ecology and environment analysis and modeling based on RS and GIS

NASA Astrophysics Data System (ADS)

Zhang, Wensheng; Chen, Hongfu; Wang, Mingsheng

2009-07-01

Analysis of agricultural ecology and environment is based on the data of agricultural resources, which are obtained by RS monitoring. The over-exploitation of farmlands will cause structural changes of the soil composition, and damage the planting environment and the agro-ecosystem. Through the research on the dynamic monitoring methods of multitemporal RS images and GIS technology, the crop growth status, crop acreage and other relevant information in agricultural production are extracted based on the monitor and analysis of the conditions of the fields and crop growth. The agro-ecological GIS platform is developed with the establishment of the agricultural resources management database, which manages spatial data, RS data and attribute data of agricultural resources. Using the RS, GIS analysis results, the reasons of agro-ecological destruction are analyzed and the evaluation methods are established. This paper puts forward the concept of utilization capacity of farmland, which describes farmland space for development and utilization that is influenced by the conditions of the land, water resources, climate, pesticides and chemical fertilizers and many other agricultural production factors. Assessment model of agricultural land use capacity is constructed with the help of Fuzzy. Assessing the utilization capacity of farmland can be helpful to agricultural production and ecological protection of farmland. This paper describes the application of the capacity evaluation model with simulated data in two aspects, namely, in evaluating the status of farmland development and utilization and in optimal planting.

Resource Utilization for Initial Hospitalization in Pediatric Heart Transplantation in the United States.

PubMed

Boucek, Dana M; Lal, Ashwin K; Eckhauser, Aaron W; Weng, Hsin-Yi Cindy; Sheng, Xiaoming; Wilkes, Jacob F; Pinto, Nelangi M; Menon, Shaji C

2018-04-15

Pediatric heart transplantation (HT) is resource intensive. Event-driven pediatric databases do not capture data on resource use. The objective of this study was to evaluate resource utilization and identify associated factors during initial hospitalization for pediatric HT. This multicenter retrospective cohort study utilized the Pediatric Health Information Systems database (43 children's hospitals in the United States) of children ≤19 years of age who underwent transplant between January 2007 and July 2013. Demographic variables including site, payer, distance and time to center, clinical pre- and post-transplant variables, mortality, cost, and charge were the data collected. Total length of stay (LOS) and charge for the initial hospitalization were used as surrogates for resource use. Charges were inflation adjusted to 2013 dollars. Of 1,629 subjects, 54% were male, and the median age at HT was 5 years (IQR [interquartile range] 0 to 13). The median total and intensive care unit LOS were 51 (IQR 23 to 98) and 23 (IQR 9 to 58) days, respectively. Total charge and cost for hospitalization were $852,713 ($464,900 to $1,609,300) and $383,600 ($214,900 to $681,000) respectively. Younger age, lower volume center, southern region, and co-morbidities before transplant were associated with higher resource use. In later years, charges increased despite shorter LOS. In conclusion, this large multicenter study provides novel insight into factors associated with resource use in pediatric patients having HT. Peritransplant morbidities are associated with increased cost and LOS. Reducing costs in line with LOS will improve health-care value. Regional and center volume differences need further investigation for optimizing value-based care and efficient use of scarce resources. Copyright © 2018 Elsevier Inc. All rights reserved.

Organizational attributes that assure optimal utilization of public health nurses.

PubMed

Meagher-Stewart, Donna; Underwood, Jane; MacDonald, Mary; Schoenfeld, Bonnie; Blythe, Jennifer; Knibbs, Kristin; Munroe, Val; Lavoie-Tremblay, Mélanie; Ehrlich, Anne; Ganann, Rebecca; Crea, Mary

2010-01-01

Optimal utilization of public health nurses (PHNs) is important for strengthening public health capacity and sustaining interest in public health nursing in the face of a global nursing shortage. To gain an insight into the organizational attributes that support PHNs to work effectively, 23 focus groups were held with PHNs, managers, and policymakers in diverse regions and urban and rural/remote settings across Canada. Participants identified attributes at all levels of the public health system: government and system-level action, local organizational culture of their employers, and supportive management practices. Effective leadership emerged as a strong message throughout all levels. Other organizational attributes included valuing and promoting public health nursing; having a shared vision, goals, and planning; building partnerships and collaboration; demonstrating flexibility and creativity; and supporting ongoing learning and knowledge sharing. The results of this study highlight opportunities for fostering organizational development and leadership in public health, influencing policies and programs to optimize public health nursing services and resources, and supporting PHNs to realize the full scope of their competencies.

Resource Utilization and Site Selection for a Self-Sufficient Martian Outpost

NASA Technical Reports Server (NTRS)

Barker, Donald; Chamitoff, Gregory; James, George

1998-01-01

As a planet with striking similarities to Earth, Mars is an important focus for scientific research aimed at understanding the processes of planetary evolution and the formation of our solar system. Fortunately, Mars is also a planet with abundant natural resources, including assessible materials that can be used to support human life and to sustain a self-sufficient martian outpost. Resources required include water, breathable air, food, shelter, energy, and fuel. Through a mission design based on in situ resource development, we can establish a permanent outpost on Mars beginning with the first manned mission. This paper examines the potential for supporting the first manned mission with the objective of achieving self-sufficiency through well-understood resource development and a program of rigorous scientific research aimed at extending that capability. We examine the potential for initially extracting critical resources from the martian environment, and discuss the scientific investigations required to identify additional resources in the atmosphere, on the surface, and within the subsurface. We also discuss our current state of knowledge of Mars, technical considerations of resource utilization, and using unmanned missions' data for selecting an optimal site. The primary goal of achieving self-sufficiency on Mars would accelerate the development of human colonization beyond Earth, while providing a robust and permanent martian base from which humans can explore and conduct long-term research on planetary evolution, the solar system, and life itself.

Mitigating Provider Uncertainty in Service Provision Contracts

NASA Astrophysics Data System (ADS)

Smith, Chris; van Moorsel, Aad

Uncertainty is an inherent property of open, distributed and multiparty systems. The viability of the mutually beneficial relationships which motivate these systems relies on rational decision-making by each constituent party under uncertainty. Service provision in distributed systems is one such relationship. Uncertainty is experienced by the service provider in his ability to deliver a service with selected quality level guarantees due to inherent non-determinism, such as load fluctuations and hardware failures. Statistical estimators utilized to model this non-determinism introduce additional uncertainty through sampling error. Inability of the provider to accurately model and analyze uncertainty in the quality level guarantees can result in the formation of sub-optimal service provision contracts. Emblematic consequences include loss of revenue, inefficient resource utilization and erosion of reputation and consumer trust. We propose a utility model for contract-based service provision to provide a systematic approach to optimal service provision contract formation under uncertainty. Performance prediction methods to enable the derivation of statistical estimators for quality level are introduced, with analysis of their resultant accuracy and cost.

Derivation of Optimal Cropping Pattern in Part of Hirakud Command using Cuckoo Search

NASA Astrophysics Data System (ADS)

Rath, Ashutosh; Biswal, Sudarsan; Samantaray, Sandeep; Swain, Prakash Chandra, PROF.

2017-08-01

The economicgrowth of a Nation depends on agriculture which relies on the obtainable water resources, available land and crops. The contribution of water in an appropriate quantity at appropriate time plays avitalrole to increase the agricultural production. Optimal utilization of available resources can be achieved by proper planning and management of water resources projects and adoption of appropriate technology. In the present work, the command area of Sambalpur distribrutary System is taken up for investigation. Further, adoption of a fixed cropping pattern causes the reduction of yield. The present study aims at developing different crop planning strategies to increase the net benefit from the command area with minimum investment. Optimization models are developed for Kharif season using LINDO and Cuckoo Search (CS) algorithm for maximization of the net benefits. In process of development of Optimization model the factors such as cultivable land, seeds, fertilizers, man power, water cost, etc. are taken as constraints. The irrigation water needs of major crops and the total available water through canals in the command of Sambalpur Distributary are estimated. LINDO and Cuckoo Search models are formulated and used to derive the optimal cropping pattern yielding maximum net benefits. The net benefits of Rs.585.0 lakhs in Kharif Season are obtained by adopting LINGO and 596.07 lakhs from Cuckoo Search, respectively, whereas the net benefits of 447.0 lakhs is received by the farmers of the locality with the adopting present cropping pattern.

Rational Exploitation and Utilizing of Groundwater in Jiangsu Coastal Area

NASA Astrophysics Data System (ADS)

Kang, B.; Lin, X.

2017-12-01

Jiangsu coastal area is located in the southeast coast of China, where is a new industrial base and an important coastal and Land Resources Development Zone of China. In the areas with strong human exploitation activities, regional groundwater evolution is obviously affected by human activities. In order to solve the environmental geological problems caused by groundwater exploitation fundamentally, we must find out the forming conditions of regional groundwater hydrodynamic field, and the impact of human activities on groundwater hydrodynamic field evolution and hydrogeochemical evolition. Based on these results, scientific management and reasonable exploitation of the regional groundwater resources can be provided for the utilization. Taking the coastal area of Jiangsu as the research area, we investigate and analyze of the regional hydrogeological conditions. The numerical simulation model of groundwater flow was established according to the water power, chemical and isotopic methods, the conditions of water flow and the influence of hydrodynamic field on the water chemical field. We predict the evolution of regional groundwater dynamics under the influence of human activities and climate change and evaluate the influence of groundwater dynamic field evolution on the environmental geological problems caused by groundwater exploitation under various conditions. We get the following conclusions: Three groundwater exploitation optimal schemes were established. The groundwater salinization was taken as the primary control condition. The substitution model was proposed to model groundwater exploitation and water level changes by BP network method.Then genetic algorithm was used to solve the optimization solution. Three groundwater exploitation optimal schemes were submit to local water resource management. The first sheme was used to solve the groundwater salinization problem. The second sheme focused on dual water supply. The third sheme concerned on emergency water supppy. This is the first time environment problem taken as water management objectinve in this coastal area.

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients.

PubMed

Head, Linden; Nessim, Carolyn; Usher Boyd, Kirsty

2017-02-01

Bilateral prophylactic mastectomy (BPM) has demonstrated breast cancer risk reduction in high-risk/ BRCA + patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. We retrospectively reviewed the cases of all high-risk/ BRCA + patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1-2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/ BRCA + status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model ( p = 0.003, p < 0.001 and p = 0.015, respectively). A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization.

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients

PubMed Central

Head, Linden; Nessim, Carolyn; Boyd, Kirsty Usher

2017-01-01

Background Bilateral prophylactic mastectomy (BPM) has shown breast cancer risk reduction in high-risk/BRCA+ patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. Methods We retrospectively reviewed the cases of all high-risk/BRCA+ patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1–2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/BRCA+ status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. Results There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model (p = 0.003, p < 0.001 and p = 0.015, respectively). Conclusion A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization. PMID:28234588

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients.

PubMed

Head, Linden; Nessim, Carolyn; Usher Boyd, Kirsty

2016-12-01

Bilateral prophylactic mastectomy (BPM) has demonstrated breast cancer risk reduction in high-risk/ BRCA + patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. We retrospectively reviewed the cases of all high-risk/ BRCA + patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1-2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/ BRCA + status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model ( p = 0.003, p < 0.001 and p = 0.015, respectively). A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization.

Patient-Provider Communication and Health Outcomes Among Individuals With Atherosclerotic Cardiovascular Disease in the United States: Medical Expenditure Panel Survey 2010 to 2013.

PubMed

Okunrintemi, Victor; Spatz, Erica S; Di Capua, Paul; Salami, Joseph A; Valero-Elizondo, Javier; Warraich, Haider; Virani, Salim S; Blaha, Michael J; Blankstein, Ron; Butt, Adeel A; Borden, William B; Dharmarajan, Kumar; Ting, Henry; Krumholz, Harlan M; Nasir, Khurram

2017-04-01

Consumer-reported patient-provider communication (PPC) assessed by Consumer Assessment of Health Plans Survey in ambulatory settings is incorporated as a complementary value metric for patient-centered care of chronic conditions in pay-for-performance programs. In this study, we examine the relationship of PPC with select indicators of patient-centered care in a nationally representative US adult population with established atherosclerotic cardiovascular disease. The study population consisted of a nationally representative sample of 6810 individuals (aged ≥18 years), representing 18.3 million adults with established atherosclerotic cardiovascular disease (self-reported or International Classification of Diseases, Ninth Edition diagnosis) reporting a usual source of care in the 2010 to 2013 pooled Medical Expenditure Panel Survey cohort. Participants responded to questions from Consumer Assessment of Health Plans Survey that assessed PPC, and we developed a weighted PPC composite score using their responses, categorized as 1 (poor), 2 (average), and 3 (optimal). Outcomes of interest were (1) patient-reported outcomes: 12-item Short Form physical/mental health status, (2) quality of care measures: statin and ASA use, (3) healthcare resource utilization: emergency room visits and hospital stays, and (4) total annual and out-of-pocket healthcare expenditures. Atherosclerotic cardiovascular disease patients reporting poor versus optimal were over 2-fold more likely to report poor outcomes; 52% and 26% more likely to report that they are not on statin and aspirin, respectively, had a significantly greater utilization of health resources (odds ratio≥2 emergency room visit, 1.41 [95% confidence interval, 1.09-1.81]; odds ratio≥2 hospitalization, 1.36 [95% confidence interval, 1.04-1.79]), as well as an estimated $1243 ($127-$2359) higher annual healthcare expenditure. This study reveals a strong relationship between PPC and patient-reported outcomes, utilization of evidence-based therapies, healthcare resource utilization, and expenditures among those with established atherosclerotic cardiovascular disease. © 2017 American Heart Association, Inc.

Resource allocation for error resilient video coding over AWGN using optimization approach.

PubMed

An, Cheolhong; Nguyen, Truong Q

2008-12-01

The number of slices for error resilient video coding is jointly optimized with 802.11a-like media access control and the physical layers with automatic repeat request and rate compatible punctured convolutional code over additive white gaussian noise channel as well as channel times allocation for time division multiple access. For error resilient video coding, the relation between the number of slices and coding efficiency is analyzed and formulated as a mathematical model. It is applied for the joint optimization problem, and the problem is solved by a convex optimization method such as the primal-dual decomposition method. We compare the performance of a video communication system which uses the optimal number of slices with one that codes a picture as one slice. From numerical examples, end-to-end distortion of utility functions can be significantly reduced with the optimal slices of a picture especially at low signal-to-noise ratio.

Capacity utilization study for aviation security cargo inspection queuing system

NASA Astrophysics Data System (ADS)

Allgood, Glenn O.; Olama, Mohammed M.; Lake, Joe E.; Brumback, Daryl

2010-04-01

In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization, subscribed resources capacity utilization, and number of cargo pieces (or pallets) in the different queues. These metrics are performance indicators of the system's ability to service current needs and response capacity to additional requests. We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet, number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.

Capacity Utilization Study for Aviation Security Cargo Inspection Queuing System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E

In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization, subscribed resources capacity utilization, and number ofmore » cargo pieces (or pallets) in the different queues. These metrics are performance indicators of the system s ability to service current needs and response capacity to additional requests. We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet, number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.« less

Optimal harvesting of fish stocks under a time-varying discount rate.

PubMed

Duncan, Stephen; Hepburn, Cameron; Papachristodoulou, Antonis

2011-01-21

Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. In such optimisations, it is common to maximise the discounted utility of harvesting over time, employing a constant time discount rate. However, evidence from human and animal behaviour suggests that we have evolved to employ discount rates which fall over time, often referred to as "hyperbolic discounting". This increases the weight on benefits in the distant future, which may appear to provide greater protection of resources for future generations, but also creates challenges of time-inconsistent plans. This paper examines harvesting plans when the discount rate declines over time. With a declining discount rate, the planner reduces stock levels in the early stages (when the discount rate is high) and intends to compensate by allowing the stock level to recover later (when the discount rate will be lower). Such a plan may be feasible and optimal, provided that the planner remains committed throughout. However, in practice there is a danger that such plans will be re-optimized and adjusted in the future. It is shown that repeatedly restarting the optimization can drive the stock level down to the point where the optimal policy is to harvest the stock to extinction. In short, a key contribution of this paper is to identify the surprising severity of the consequences flowing from incorporating a rather trivial, and widely prevalent, "non-rational" aspect of human behaviour into renewable resource management models. These ideas are related to the collapse of the Peruvian anchovy fishery in the 1970's. Copyright © 2010 Elsevier Ltd. All rights reserved.

A decision modeling for phasor measurement unit location selection in smart grid systems

NASA Astrophysics Data System (ADS)

Lee, Seung Yup

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

No Cost – Low Cost Compressed Air System Optimization in Industry

NASA Astrophysics Data System (ADS)

Dharma, A.; Budiarsa, N.; Watiniasih, N.; Antara, N. G.

2018-04-01

Energy conservation is a systematic, integrated of effort, in order to preserve energy sources and improve energy utilization efficiency. Utilization of energy in efficient manner without reducing the energy usage it must. Energy conservation efforts are applied at all stages of utilization, from utilization of energy resources to final, using efficient technology, and cultivating an energy-efficient lifestyle. The most common way is to promote energy efficiency in the industry on end use and overcome barriers to achieve such efficiency by using system energy optimization programs. The facts show that energy saving efforts in the process usually only focus on replacing tools and not an overall system improvement effort. In this research, a framework of sustainable energy reduction work in companies that have or have not implemented energy management system (EnMS) will be conducted a systematic technical approach in evaluating accurately a compressed-air system and potential optimization through observation, measurement and verification environmental conditions and processes, then processing the physical quantities of systems such as air flow, pressure and electrical power energy at any given time measured using comparative analysis methods in this industry, to provide the potential savings of energy saving is greater than the component approach, with no cost to the lowest cost (no cost - low cost). The process of evaluating energy utilization and energy saving opportunities will provide recommendations for increasing efficiency in the industry and reducing CO2 emissions and improving environmental quality.

Multi Blending Technology (MBT): mineral processing method for increasing added value of marginal reserve

NASA Astrophysics Data System (ADS)

Agustinus, E. T. S.

2018-02-01

Indonesia's position on the path of ring of fire makes it rich in mineral resources. Nevertheless, in the past, the exploitation of Indonesian mineral resources was uncontrolled resulting in environmental degradation and marginal reserves. Exploitation of excessive mineral resources is very detrimental to the state. Reflecting on the occasion, the management and utilization of Indonesia's mineral resources need to be good in mining practice. The problem is how to utilize the mineral reserve resources effectively and efficiently. Utilization of marginal reserves requires new technologies and processing methods because the old processing methods are inadequate. This paper gives a result of Multi Blending Technology (MBT) Method. The underlying concept is not to do the extraction or refinement but processing through the formulation of raw materials by adding an additive and produce a new material called functional materials. Application of this method becomes important to be summarized into a scientific paper in a book form, so that the information can spread across multiple print media and become focused on and optimized. This book is expected to be used as a reference for stakeholder providing added value to environmentally marginal reserves in Indonesia. The conclusions are that Multi Blending Technology (MBT) Method can be used as a strategy to increase added values effectively and efficiently to marginal reserve minerals and that Multi Blending Technology (MBT) method has been applied to forsterite, Atapulgite Synthesis, Zeoceramic, GEM, MPMO, SMAC and Geomaterial.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Hao; Ren, Shangping; Garzoglio, Gabriele

Cloud bursting is one of the key research topics in the cloud computing communities. A well designed cloud bursting module enables private clouds to automatically launch virtual machines (VMs) to public clouds when more resources are needed. One of the main challenges in developing a cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on system operational data obtained from FermiCloud, a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows, the VM launching overheadmore » is not a constant. It varies with physical resource utilization, such as CPU and I/O device utilizations, at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launching overhead reference model is needed. In this paper, we first develop a VM launching overhead reference model based on operational data we have obtained on FermiCloud. Second, we apply the developed reference model on FermiCloud and compare calculated VM launching overhead values based on the model with measured overhead values on FermiCloud. Our empirical results on FermiCloud indicate that the developed reference model is accurate. We believe, with the guidance of the developed reference model, efficient resource allocation algorithms can be developed for cloud bursting process to minimize the operational cost and resource waste.« less

A New Wavelength Optimization and Energy-Saving Scheme Based on Network Coding in Software-Defined WDM-PON Networks

NASA Astrophysics Data System (ADS)

Ren, Danping; Wu, Shanshan; Zhang, Lijing

2016-09-01

In view of the characteristics of the global control and flexible monitor of software-defined networks (SDN), we proposes a new optical access network architecture dedicated to Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) systems based on SDN. The network coding (NC) technology is also applied into this architecture to enhance the utilization of wavelength resource and reduce the costs of light source. Simulation results show that this scheme can optimize the throughput of the WDM-PON network, greatly reduce the system time delay and energy consumption.

Next generation communications satellites: multiple access and network studies

NASA Technical Reports Server (NTRS)

Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.

1982-01-01

Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.

Low-Cost, High-Performance Cryocoolers for In-Situ Propellant Production

NASA Technical Reports Server (NTRS)

Martin, J. L.; Corey, J. A.; Peters, T. A.

1999-01-01

A key feature of many In-Situ Resource Utilization (ISRU) schemes is the production of rocket fuel and oxidizer from the Martian atmosphere. Many of the fuels under consideration will require cryogenic cooling for efficient long-term storage. Although significant research has been focused on the techniques for producing the fuels from Martian resources, little effort has been expended on the development of cryocoolers to efficiently liquefy these fuels. This paper describes the design of a pulse tube liquefier optimized for liquefying oxygen produced by an In-Situ Propellant Production (ISPP) plant on Mars.

Low-Cost High-Performance Cryocoolers for In-Situ Propellant Production

NASA Technical Reports Server (NTRS)

Martin, J. L.; Corey, J. A.; Peters, T. A.

1999-01-01

A key feature of many In-Situ Resource Utilization (ISRU) schemes is the production of rocket fuel and oxidizer from the Martian atmosphere. Many of the fuels under consideration will require cryogenic cooling for efficient long-term storage. Although significant research has been focused on the techniques for producing the fuels from Martian resources, little effort has been expended on the development of cryocoolers to efficiently liquefy these fuels. This paper describes the design of a pulse tube liquefier optimized for liquefying oxygen produced by an In-Situ Propellant Production (ISPP) plant on Mars.

Assigning Resources to Health Care Use for Health Services Research: Options and Consequences

PubMed Central

Fishman, Paul A.; Hornbrook, Mark C.

2013-01-01

Aims Our goals are threefold: 1) to review the leading options for assigning resource coefficients to health services utilization; 2) to discuss the relative advantages of each option; and, 3) provide examples where the research question had marked implications for the choice of which resource measure to employ. Methods Three approaches have been used to establish relative resource weights in health services research: a) direct estimation of production costs through micro-costing or step down allocation methods; b) macro-costing/regression analysis; and, c) standardized resource assignment. We describe each of these methods and provide examples of how the study question drove the choice of resource use measure. Findings All empirical resource-intensity weighting systems contain distortions that limit their universal application. Hence, users must select the weighting system that matches the needs of their specific analysis. All systems require significant data resources and data processing. However, inattention to the distortions contained in a complex resource weighting system may undermine the validity and generalizability of an economic evaluation. Conclusions Direct estimation of production costs are useful for empirical analyses, but they contain distortions that undermine optimal resource allocation decisions. Researchers must ensure that the data being used meets both the study design and the question being addressed. They also should ensure that the choice of resource measure is the best fit for the analysis. Implications for Research and Policy Researchers should consider which of the available measures is the most appropriate for the question being addressed rather than take ‘cost’ or utilization as a variable over which they have no control PMID:19536002

A risk analysis approach applied to field surveillance in utility meters in legal metrology

NASA Astrophysics Data System (ADS)

Rodrigues Filho, B. A.; Nonato, N. S.; Carvalho, A. D.

2018-03-01

Field surveillance represents the level of control in metrological supervision responsible for checking the conformity of measuring instruments in-service. Utility meters represent the majority of measuring instruments produced by notified bodies due to self-verification in Brazil. They play a major role in the economy once electricity, gas and water are the main inputs to industries in their production processes. Then, to optimize the resources allocated to control these devices, the present study applied a risk analysis in order to identify among the 11 manufacturers notified to self-verification, the instruments that demand field surveillance.

A methodology for comprehensive strategic planning and program prioritization

NASA Astrophysics Data System (ADS)

Raczynski, Christopher Michael

2008-10-01

This process developed in this work, Strategy Optimization for the Allocation of Resources (SOAR), is a strategic planning methodology based off Integrated Product and Process Development and systems engineering techniques. Utilizing a top down approach, the process starts with the creation of the organization vision and its measures of effectiveness. These measures are prioritized based on their application to external world scenarios which will frame the future. The programs which will be used to accomplish this vision are identified by decomposing the problem. Information is gathered on the programs as to the application, cost, schedule, risk, and other pertinent information. The relationships between the levels of the hierarchy are mapped utilizing subject matter experts. These connections are then utilized to determine the overall benefit of the programs to the vision of the organization. Through a Multi-Objective Genetic Algorithm a tradespace of potential program portfolios can be created amongst which the decision maker can allocate resources. The information and portfolios are presented to the decision maker through the use of a Decision Support System which collects and visualizes all the data in a single location. This methodology was tested utilizing a science and technology planning exercise conducted by the United States Navy. A thorough decomposition was defined and technology programs identified which had the potential to provide benefit to the vision. The prioritization of the top level capabilities was performed through the use of a rank ordering scheme and a previous naval application was used to demonstrate a cumulative voting scheme. Voting was performed utilizing the Nominal Group Technique to capture the relationships between the levels of the hierarchy. Interrelationships between the technologies were identified and a MOGA was utilized to optimize portfolios with respect to these constraints and information was placed in a DSS. This formulation allowed the decision makers to assess which portfolio could provide the greatest benefit to the Navy while still fitting within the funding profile.

Optimal management of on-farm resources in small-scale dairy systems of Central Mexico: model development and evaluation.

PubMed

Castelán-Ortega, Octavio Alonso; Martínez-García, Carlos Galdino; Mould, Fergus L; Dorward, Peter; Rehman, Tahir; Rayas-Amor, Adolfo Armando

2016-06-01

This study evaluates the available on-farm resources of five case studies typified as small-scale dairy systems in central Mexico. A comprehensive mixed-integer linear programming model was developed and applied to two case studies. The optimal plan suggested the following: (1) instruction and utilization of maize silage, (2) alfalfa hay making that added US$140/ha/cut to the total net income, (3) allocation of land to cultivated pastures in a ratio of 27:41(cultivated pastures/maize crop) rather than at the current 14:69, and dairy cattle should graze 12 h/day, (4) to avoid grazing of communal pastures because this activity represented an opportunity cost of family labor that reduced the farm net income, and (5) that the highest farm net income was obtained when liquid milk and yogurt sales were included in the optimal plan. In the context of small-scale dairy systems of central Mexico, the optimal plan would need to be implemented gradually to enable farmers to develop required skills and to change management strategies from reliance on forage and purchased concentrate to pasture-based and conserved forage systems.

Building agribusiness model of LEISA to achieve sustainable agriculture in Surian Subdistrict of Sumedang Regency West Java Indonesia

NASA Astrophysics Data System (ADS)

Djuwendah, E.; Priyatna, T.; Kusno, K.; Deliana, Y.; Wulandari, E.

2018-03-01

Building agribusiness model of LEISA is needed as a prototype of sustainable regional and economic development (SRRED) in the watersheds (DAS) of West Java Province. Agribusiness model of LEISA is a sustainable agribusiness system applying low external input. The system was developed in the framework of optimizing local-based productive resources including soil, water, vegetation, microclimate, renewable energy, appropriate technology, social capital, environment and human resources by combining various subsystems including integrated production subsystems of crops, livestock and fish to provide a maximum synergy effect, post-harvest subsystem and processing of results, marketing subsystems and supporting subsystems. In this study, the ecological boundary of Cipunegara sub-watershed ecosystem, administrative boundaries are Surian Subdistricts in Sumedang. The purpose of this study are to identify the potency of natural resources and local agricultural technologies that could support the LEISA model in Surian and to identify the potency of internal and external inputs in the LEISA model. The research used qualitative descriptive method and technical action research. Data were obtained through interviews, documentation, and observation. The results showed that natural resources in the form of agricultural land, water resources, livestock resources, and human labor are sufficient to support agribusiness model of LEISA. LEISA agribusiness model that has been applied in the research location is the integration of beef cattle, agroforestry, and agrosilvopasture. By building LEISA model, agribusiness can optimize the utilization of locally based productive resources, reduce dependence on external resources, and support sustainable food security.

Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

PubMed

Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

2018-05-01

Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Optimization of Groundwater Abstraction in the Beijing Plain using a Fuzzy Pattern Recognition Approach

NASA Astrophysics Data System (ADS)

Guo, H.; Li, W.; Wang, L.; Cheng, G.; Zhu, J.; Wang, Y.; Chen, Y.

2016-12-01

Groundwater supply accounts for two-thirds of the water supply of the Beijing municipality, and groundwater resources play a fundamental role in assuring the security and sustainability of the regional economy in Beijing. In this report, ten groundwater abstraction scenarios were designed based on the water demand and the capacity of water supply in the Beijing plain, and the impacts of these scenarios on the groundwater storage and level were illustrated with a transient 3D groundwater model constructed with MODFLOW. In addition, a set of evaluation criteria was developed taking into account of a number of factors such as the amount of groundwater exploitation, the evaporation of unconfined groundwater, river outflow, regional average groundwater depth, drawdowns in depression cones and the ratio of storage to the total recharge. Based on this set of criteria, the ten proposed groundwater abstraction scenarios were compared using a multi-criteria fuzzy pattern recognition model, which is suitable for solving large-scale, transient groundwater management problems and also proven to be a useful scientific analysis tool to identify the optimal groundwater resource utilization scenario. The evaluation results show that the groundwater resources can be rationally and optimally used when multiple measures such as control of groundwater abstraction and increase of recharge are jointly implemented.

[Development of human resources and the Plan of Action].

PubMed

Vidal, C

1984-01-01

This article (whose first part was published in the previous issue of Educación Médica y Salud) concludes an exhaustive review of manpower development in the Americas. This part considers the specific measures in this field enunciated in the Plan of Action; these measures pertain to four main areas: planning and programming of human resources, training in priority areas, utilization of human resources, and educational technology. The author discusses the present and future possibilities and obstacles of each of these activities and the steps to be taken to bring needs into line with real situations. It is of paramount importance that the national health authorities clearly spell out their policies for the development of human resources in the health field within the framework of general development policies. Another point to be insisted upon is the multiprofessional and multidisciplinary training of the health team and the importance of the education-service-supervision function, which usually results in permanent and continuing education, which in turn optimizes the utilization of personnel. However, none of this will be possible without an appropriate education technology with which to innovate, analyze and refine the entire education process and so meet the needs of both society and the health services.

Strategy community development based on local resources

NASA Astrophysics Data System (ADS)

Meirinawati; Prabawati, I.; Pradana, G. W.

2018-01-01

The problem of progressing regions is not far from economic problems and is often caused by the inability of the regions in response to changes in economic conditions that occur, so the need for community development programs implemented to solve various problems. Improved community effort required with the real conditions and needs of each region. Community development based on local resources process is very important, because it is an increase in human resource capability in the optimal utilization of local resource potential. In this case a strategy is needed in community development based on local resources. The community development strategy are as follows:(1) “Eight Line Equalization Plus” which explains the urgency of rural industrialization, (2) the construction of the village will be more successful when combining strategies are tailored to regional conditions, (3) the escort are positioning themselves as the Planner, supervisor, information giver, motivator, facilitator, connecting at once evaluators.

Coastal management strategy for small island: ecotourism potency development in Karimata Island, West Kalimantan

NASA Astrophysics Data System (ADS)

Rudiastuti, A. W.; Munawaroh; Setyawan, I. E.; Pramono, G. H.

2018-04-01

Sustainable coastal management is playing an important role in coastal resources conservation, particularly on small islands. Karimata archipelago has unique characteristics and great potential to be developed as a tourism object, one of which is Karimata Island as the largest island and also reserve area. The concept of ecotourism focuses on the ecology conservation, economic benefits, and social life. Ecotourism aims to build sustainable tourism that provides economically viable and social benefits to the community. This study aims to develop coastal management strategy based on ecotourism at Karimata Island. Spatial approaching through coastal type was done. Qualitative descriptive analysis and SWOT are used to develop sustainable management strategies for the coast of Karimata Island, where the opportunities and challenges to the development of coastal ecotourism Karimata Island also included. If this potential is optimally utilized, it can be relied as an economic opportunity for local communities. Structurally shaped coast, marine depositional coast and coast build by organism are several of coastal types found at Karimata Island. Coastal ecosystems inhabited Karimata Island are mangroves, coral reefs, and macro-algae. Karimata Island have not been optimally utilized for tourist destinations. The biggest obstacle encountered is the accessibility from Kalimantan or other island at Karimata islands. Several problems related to the utilization of coastal resources were found such as mangrove and coral reef damage, also regulation that less supportive. The results of this study are expected to provide an overview of solutions for the development of coastal tourism potentials in Karimata Island.

Surgery scheduling optimization considering real life constraints and comprehensive operation cost of operating room.

PubMed

Xiang, Wei; Li, Chong

2015-01-01

Operating Room (OR) is the core sector in hospital expenditure, the operation management of which involves a complete three-stage surgery flow, multiple resources, prioritization of the various surgeries, and several real-life OR constraints. As such reasonable surgery scheduling is crucial to OR management. To optimize OR management and reduce operation cost, a short-term surgery scheduling problem is proposed and defined based on the survey of the OR operation in a typical hospital in China. The comprehensive operation cost is clearly defined considering both under-utilization and overutilization. A nested Ant Colony Optimization (nested-ACO) incorporated with several real-life OR constraints is proposed to solve such a combinatorial optimization problem. The 10-day manual surgery schedules from a hospital in China are compared with the optimized schedules solved by the nested-ACO. Comparison results show the advantage using the nested-ACO in several measurements: OR-related time, nurse-related time, variation in resources' working time, and the end time. The nested-ACO considering real-life operation constraints such as the difference between first and following case, surgeries priority, and fixed nurses in pre/post-operative stage is proposed to solve the surgery scheduling optimization problem. The results clearly show the benefit of using the nested-ACO in enhancing the OR management efficiency and minimizing the comprehensive overall operation cost.

RTDS-Based Design and Simulation of Distributed P-Q Power Resources in Smart Grid

NASA Astrophysics Data System (ADS)

Taylor, Zachariah David

In this Thesis, we propose to utilize a battery system together with its power electronics interfaces and bidirectional charger as a distributed P-Q resource in power distribution networks. First, we present an optimization-based approach to operate such distributed P-Q resources based on the characteristics of the battery and charger system as well as the features and needs of the power distribution network. Then, we use the RTDS Simulator, which is an industry-standard simulation tool of power systems, to develop two RTDS-based design approaches. The first design is based on an ideal four-quadrant distributed P-Q power resource. The second design is based on a detailed four-quadrant distributed P-Q power resource that is developed using power electronics components. The hardware and power electronics circuitry as well as the control units are explained for the second design. After that, given the two-RTDS designs, we conducted extensive RTDS simulations to assess the performance of the designed distributed P-Q Power Resource in an IEEE 13 bus test system. We observed that the proposed design can noticeably improve the operational performance of the power distribution grid in at least four key aspects: reducing power loss, active power peak load shaving at substation, reactive power peak load shaving at substation, and voltage regulation. We examine these performance measures across three design cases: Case 1: There is no P-Q Power Resource available on the power distribution network. Case 2: The installed P-Q Power Resource only supports active power, i.e., it only utilizes its battery component. Case 3: The installed P-Q Power Resource supports both active and reactive power, i.e., it utilizes both its battery component and its power electronics charger component. In the end, we present insightful interpretations on the simulation results and suggest some future works.

Treatment patterns, resource utilization, and outcomes among hospitalized patients with methicillin-resistant Staphylococcus aureus complicated skin and soft tissue infections in Lebanon and Saudi Arabia.

PubMed

Matar, Madonna J; Moghnieh, Rima; Alothman, Adel F; Althaqafi, Abdulhakeem O; Alenazi, Thamer H; Farahat, Fayssal M; Corman, Shelby; Solem, Caitlyn T; Raghubir, Nirvana; Macahilig, Cynthia; Haider, Seema; Stephens, Jennifer M

2017-01-01

To describe treatment patterns and medical resource use for methicillin-resistant Staphylococcus aureus (MRSA) complicated skin and soft tissue infections (cSSTI) in Saudi Arabia and Lebanon in terms of drug selection against the infecting pathogen as well as hospital resource utilization and clinical outcomes among patients with these infections. This retrospective chart review study evaluated 2011-2012 data from five hospitals in Saudi Arabia and Lebanon. Patients were included if they had been discharged with a diagnosis of MRSA cSSTI, which was culture-proven or suspected based on clinical criteria. Hospital data were abstracted for a random sample of patients with each infection type to capture demographics, treatment patterns, hospital resource utilization, and clinical outcomes. Statistical analysis was descriptive. Data were abstracted from medical records of 87 patients with MRSA cSSTI; mean age 52.4±25.9 years and 61% male. Only 64% of patients received an MRSA active initial therapy, with 56% of first-line regimens containing older beta-lactams. The mean total length of stay was 26.3 days, with the majority (19.1 days) spent in general wards. Surgical procedures included incision and drainage (22% of patients), debridement (14%), and amputation (5%). Mechanical ventilation was required by 9% of patients, with a mean duration of 18 days per patient. Hemodialysis was required by four patients (5%), two of whom were reported to have moderate to severe renal disease on admission, for a mean of 5.5 days. Inpatient mortality was 8%. Thirty-nine percent were prescribed at least one antibiotic at discharge, with the most commonly prescribed discharge antibiotics being clindamycin (44%), ciprofloxacin (18%), trimethoprim/sulfamethoxazole (12%), and linezolid (9%). This Middle Eastern real-world study of resource use and treatment patterns in MRSA cSSTI indicates that management of this condition could be further optimized in terms of drug selection and resource utilization.

Surgical resource utilization in urban terrorist bombing: a computer simulation.

PubMed

Hirshberg, A; Stein, M; Walden, R

1999-09-01

The objective of this study was to analyze the utilization of surgical staff and facilities during an urban terrorist bombing incident. A discrete-event computer model of the emergency room and related hospital facilities was constructed and implemented, based on cumulated data from 12 urban terrorist bombing incidents in Israel. The simulation predicts that the admitting capacity of the hospital depends primarily on the number of available surgeons and defines an optimal staff profile for surgeons, residents, and trauma nurses. The major bottlenecks in the flow of critical casualties are the shock rooms and the computed tomographic scanner but not the operating rooms. The simulation also defines the number of reinforcement staff needed to treat noncritical casualties and shows that radiology is the major obstacle to the flow of these patients. Computer simulation is an important new tool for the optimization of surgical service elements for a multiple-casualty situation.

A Suboptimal Power-Saving Transmission Scheme in Multiple Component Carrier Networks

NASA Astrophysics Data System (ADS)

Chung, Yao-Liang; Tsai, Zsehong

Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

Optimized passive sonar placement to allow improved interdiction

NASA Astrophysics Data System (ADS)

Johnson, Bruce A.; Matthews, Cameron

2016-05-01

The Art Gallery Problem (AGP) is the name given to a constrained optimization problem meant to determine the maximum amount of sensor coverage while utilizing the minimum number of resources. The AGP is significant because a common issue among surveillance and interdiction systems is obtaining an understanding of the optimal position of sensors and weapons in advance of enemy combatant maneuvers. The implication that an optimal position for a sensor to observe an event or for a weapon to engage a target autonomously is usually very clear after the target has passed, but for autonomous systems the solution must at least be conjectured in advance for deployment purposes. This abstract applies the AGP as a means to solve where best to place underwater sensor nodes such that the amount of information acquired about a covered area is maximized while the number of resources used to gain that information is minimized. By phrasing the ISR/interdiction problem this way, the issue is addressed as an instance of the AGP. The AGP is a member of a set of computational problems designated as nondeterministic polynomial-time (NP)-hard. As a member of this set, the AGP shares its members' defining feature, namely that no one has proven that there exists a deterministic algorithm providing a computationally-tractable solution to the AGP within a finite amount of time. At best an algorithm meant to solve the AGP can asymptotically approach perfect coverage with minimal resource usage but providing perfect coverage would either break the minimal resource usage constraint or require an exponentially-growing amount of time. No perfectly-optimal solution yet exists to the AGP, however, approximately optimal solutions to the AGP can approach complete area or barrier coverage while simultaneously minimizing the number of sensors and weapons utilized. A minimal number of underwater sensor nodes deployed can greatly increase the Mean Time Between Operational Failure (MTBOF) and logistical footprint. The resulting coverage optimizes the likelihood of encounter given an arbitrary sensor profile and threat from a free field statistical model approach. The free field statistical model is particularly applicable to worst case scenario modeling in open ocean operational profiles where targets to do not follow a particular pattern in any of the modeled dimensions. We present an algorithmic testbed which shows how to achieve approximately optimal solutions to the AGP for a network of underwater sensor nodes with or without effector systems for engagement while operating under changing environmental circumstances. The means by which we accomplish this goal are three-fold: 1) Develop a 3D model for the sonar signal propagating through the underwater environment 2) Add rigorous physics-based modeling of environmental events which can affect sensor information acquisition 3) Provide innovative solutions to the AGP which account for the environmental circumstances affecting sensor performance.

Online stochastic optimization of radiotherapy patient scheduling.

PubMed

Legrain, Antoine; Fortin, Marie-Andrée; Lahrichi, Nadia; Rousseau, Louis-Martin

2015-06-01

The effective management of a cancer treatment facility for radiation therapy depends mainly on optimizing the use of the linear accelerators. In this project, we schedule patients on these machines taking into account their priority for treatment, the maximum waiting time before the first treatment, and the treatment duration. We collaborate with the Centre Intégré de Cancérologie de Laval to determine the best scheduling policy. Furthermore, we integrate the uncertainty related to the arrival of patients at the center. We develop a hybrid method combining stochastic optimization and online optimization to better meet the needs of central planning. We use information on the future arrivals of patients to provide an accurate picture of the expected utilization of resources. Results based on real data show that our method outperforms the policies typically used in treatment centers.

Hybrid Quantum-Classical Approach to Quantum Optimal Control.

PubMed

Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu

2017-04-14

A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.

Energy management of a university campus utilizing short-term load forecasting with an artificial neural network

NASA Astrophysics Data System (ADS)

Palchak, David

Electrical load forecasting is a tool that has been utilized by distribution designers and operators as a means for resource planning and generation dispatch. The techniques employed in these predictions are proving useful in the growing market of consumer, or end-user, participation in electrical energy consumption. These predictions are based on exogenous variables, such as weather, and time variables, such as day of week and time of day as well as prior energy consumption patterns. The participation of the end-user is a cornerstone of the Smart Grid initiative presented in the Energy Independence and Security Act of 2007, and is being made possible by the emergence of enabling technologies such as advanced metering infrastructure. The optimal application of the data provided by an advanced metering infrastructure is the primary motivation for the work done in this thesis. The methodology for using this data in an energy management scheme that utilizes a short-term load forecast is presented. The objective of this research is to quantify opportunities for a range of energy management and operation cost savings of a university campus through the use of a forecasted daily electrical load profile. The proposed algorithm for short-term load forecasting is optimized for Colorado State University's main campus, and utilizes an artificial neural network that accepts weather and time variables as inputs. The performance of the predicted daily electrical load is evaluated using a number of error measurements that seek to quantify the best application of the forecast. The energy management presented utilizes historical electrical load data from the local service provider to optimize the time of day that electrical loads are being managed. Finally, the utilization of forecasts in the presented energy management scenario is evaluated based on cost and energy savings.

Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

NASA Astrophysics Data System (ADS)

Chakravarthy, Srinivas R.; Rumyantsev, Alexander

2018-03-01

Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

Investigation of storage system designs and techniques for optimizing energy conservation in integrated utility systems. Volume 1: (Executive summary)

NASA Technical Reports Server (NTRS)

1976-01-01

Integrated Utility Systems (IUS) have been suggested as a means of reducing the cost and conserving the nonrenewable energy resources required to supply utility services (energy, water, and waste disposal) to developments of limited size. The potential for further improving the performance and reducing the cost of IUS installations through the use of energy storage devices is examined and the results are summarized. Candidate energy storage concepts in the general areas of thermal, inertial, superconducting magnetic, electrochemical, chemical, and compressed air energy storage are assessed and the storage of thermal energy as the sensible heat of water is selected as the primary candidate for near term application to IUS.

An Adaptive Priority Tuning System for Optimized Local CPU Scheduling using BOINC Clients

NASA Astrophysics Data System (ADS)

Mnaouer, Adel B.; Ragoonath, Colin

2010-11-01

Volunteer Computing (VC) is a Distributed Computing model which utilizes idle CPU cycles from computing resources donated by volunteers who are connected through the Internet to form a very large-scale, loosely coupled High Performance Computing environment. Distributed Volunteer Computing environments such as the BOINC framework is concerned mainly with the efficient scheduling of the available resources to the applications which require them. The BOINC framework thus contains a number of scheduling policies/algorithms both on the server-side and on the client which work together to maximize the available resources and to provide a degree of QoS in an environment which is highly volatile. This paper focuses on the BOINC client and introduces an adaptive priority tuning client side middleware application which improves the execution times of Work Units (WUs) while maintaining an acceptable Maximum Response Time (MRT) for the end user. We have conducted extensive experimentation of the proposed system and the results show clear speedup of BOINC applications using our optimized middleware as opposed to running using the original BOINC client.

Bio-mass utilization in high pressure cogeneration boiler

NASA Astrophysics Data System (ADS)

Koundinya, Sandeep; Maria Ambrose Raj, Y.; Sreeram, K.; Divakar Shetty A., S.

2017-07-01

Coal is widely used all over the world in almost all power plants. The dependence on coal has increased enormously as the demand for electricity has reached its peak. Coal being a non-renewable source is depleting fast. We being the engineers, it's our duty to conserve the natural resources and optimize the coal consumption. In this project, we have tried to optimize the bio-mass utilization in high pressure cogeneration boiler. The project was carried in Seshasayee Paper and Boards Limited, erode related to Boiler No:10 operating at steam pressure of 105 kscg and temperature of 510°C. Available bio-mass fuels in and around the mill premises are bagasse, bagasse pith, cane trash and chipper dust. In this project, we have found out the coal equivalent replacement by the above bio-mass fuel(s) to facilitate deciding on the optimized quantity of coal that can be replaced by biomass without modifying the existing design of the plant. The dominant fuel (coal) which could be displaced with the substitute biomass fuel had been individually (biomass) analyzed.

A bottom-up approach to identifying the maximum operational adaptive capacity of water resource systems to a changing climate

NASA Astrophysics Data System (ADS)

Culley, S.; Noble, S.; Yates, A.; Timbs, M.; Westra, S.; Maier, H. R.; Giuliani, M.; Castelletti, A.

2016-09-01

Many water resource systems have been designed assuming that the statistical characteristics of future inflows are similar to those of the historical record. This assumption is no longer valid due to large-scale changes in the global climate, potentially causing declines in water resource system performance, or even complete system failure. Upgrading system infrastructure to cope with climate change can require substantial financial outlay, so it might be preferable to optimize existing system performance when possible. This paper builds on decision scaling theory by proposing a bottom-up approach to designing optimal feedback control policies for a water system exposed to a changing climate. This approach not only describes optimal operational policies for a range of potential climatic changes but also enables an assessment of a system's upper limit of its operational adaptive capacity, beyond which upgrades to infrastructure become unavoidable. The approach is illustrated using the Lake Como system in Northern Italy—a regulated system with a complex relationship between climate and system performance. By optimizing system operation under different hydrometeorological states, it is shown that the system can continue to meet its minimum performance requirements for more than three times as many states as it can under current operations. Importantly, a single management policy, no matter how robust, cannot fully utilize existing infrastructure as effectively as an ensemble of flexible management policies that are updated as the climate changes.

Modeling the Virtual Machine Launching Overhead under Fermicloud

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garzoglio, Gabriele; Wu, Hao; Ren, Shangping

FermiCloud is a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows. The Cloud Bursting module of the FermiCloud enables the FermiCloud, when more computational resources are needed, to automatically launch virtual machines to available resources such as public clouds. One of the main challenges in developing the cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on FermiCloud’s system operational data, the VM launching overhead is not a constant. It varies with physical resourcemore » (CPU, memory, I/O device) utilization at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launch overhead reference model is needed. The paper is to develop a VM launch overhead reference model based on operational data we have obtained on FermiCloud and uses the reference model to guide the cloud bursting process.« less

JPRS Report, Near East & South Asia

DTIC Science & Technology

1988-02-17

Tunisia [THE EGYPTIAN GAZETTE, 4 Jan 88] 2 PALESTINIAN AFFAIRS PLO Affirms CW Intentions [JORDAN TIMES, 13 Jan 88] 2 Economic Effects of Bank...warheads but would only use them as a last resort. /9274 Economic Effects of Bank Reform Appraised 45190011 Algiers EL MOUDHAJID (SUPPLEMENT...resources that they will have to utilize and to optimize in order to successfully shoul- der the effects of economic reform. JPRS-NEA-88-008 17

Analyzing the Interdiction of Sea-Borne Threats Using Simulation Optimization

DTIC Science & Technology

2007-03-01

Low Threat Interdiction Operations................... 56 Table 4-4: Resource Utilization under Medium Threat Interdiction Operations...1.1.1 Emerging Concern “Over 90 percent of the nation’s $5.3 billion annual investment in the TSA goes to aviation—to fight the last war.… While...using varying mission ops tempos for the interdiction model and the competing mission model. Specifically, we look at low, medium , and high asset

Coherent-state information concentration and purification in atomic memory

NASA Astrophysics Data System (ADS)

Herec, Jiří; Filip, Radim

2006-12-01

We propose a feasible method of coherent-state information concentration and purification utilizing quantum memory. The method allows us to optimally concentrate and purify information carried by many noisy copies of an unknown coherent state (randomly distributed in time) to a single copy. Thus nonclassical resources and operations can be saved, if we compare information processing with many noisy copies and a single copy with concentrated and purified information.

Mechanical power efficiency of modified turbine blades

NASA Astrophysics Data System (ADS)

Mahmud, Syahir; Sampebatu, Limbran; Kwang, Suendy Ciayadi

2017-01-01

Abstract-The problem of energy crisis has become one of the unsolved issues until today. Indonesia has a lot of non-conventional energy sources that does not utilized effectively yet. For that the available resources must utilized efficiently due to the energy crisis and the growing energy needs. Among the abundant resources of energy, one potential source of energy is hydroelectric energy. This research compares the mechanical power efficiency generated by the Darrieus turbine, Savonius turbine and the Darrieus-Savonius turbine. The comparation of the mechanical power amongst the three turbine starts from the measurement of the water flow rate, water temperature, turbine rotation and force on the shaft on each type of turbine. The comparison will show the mechanical power efficiency of each turbine to find the most efficient turbine that can work optimally. The results show that with 0.637m/s flow velocity and 44.827 Watt of water flow power, the Darrieus-Savonius turbine can generate power equal to 29.927 Watt and shaft force around by 17 N. The Darrieus-Savonius turbine provides around 66.76% efficiency betwen the three turbines; Darrieus turbine, Savonius turbine and the Darrieus-Savonius turbine. Overall, the Darrieus Savonius turbine has the ability to work optimally at the research location.

Optimal urban water conservation strategies considering embedded energy: coupling end-use and utility water-energy models.

NASA Astrophysics Data System (ADS)

Escriva-Bou, A.; Lund, J. R.; Pulido-Velazquez, M.; Spang, E. S.; Loge, F. J.

2014-12-01

Although most freshwater resources are used in agriculture, a greater amount of energy is consumed per unit of water supply for urban areas. Therefore, efforts to reduce the carbon footprint of water in cities, including the energy embedded within household uses, can be an order of magnitude larger than for other water uses. This characteristic of urban water systems creates a promising opportunity to reduce global greenhouse gas emissions, particularly given rapidly growing urbanization worldwide. Based on a previous Water-Energy-CO2 emissions model for household water end uses, this research introduces a probabilistic two-stage optimization model considering technical and behavioral decision variables to obtain the most economical strategies to minimize household water and water-related energy bills given both water and energy price shocks. Results show that adoption rates to reduce energy intensive appliances increase significantly, resulting in an overall 20% growth in indoor water conservation if household dwellers include the energy cost of their water use. To analyze the consequences on a utility-scale, we develop an hourly water-energy model based on data from East Bay Municipal Utility District in California, including the residential consumption, obtaining that water end uses accounts for roughly 90% of total water-related energy, but the 10% that is managed by the utility is worth over 12 million annually. Once the entire end-use + utility model is completed, several demand-side management conservation strategies were simulated for the city of San Ramon. In this smaller water district, roughly 5% of total EBMUD water use, we found that the optimal household strategies can reduce total GHG emissions by 4% and utility's energy cost over 70,000/yr. Especially interesting from the utility perspective could be the "smoothing" of water use peaks by avoiding daytime irrigation that among other benefits might reduce utility energy costs by 0.5% according to our assessment.

Technologies for Decreasing Mining Losses

NASA Astrophysics Data System (ADS)

Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin

2013-12-01

In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.

Global Health: Pediatric Neurology.

PubMed

Bearden, David R; Ciccone, Ornella; Patel, Archana A

2018-04-01

Neurologic disorders contribute significantly to both morbidity and mortality among children in resource-limited settings, but there are a few succinct studies summarizing the epidemiology of neurologic disorders in these settings. A review of available literature was performed to identify data on the prevalence, etiology, outcomes, and treatment of neurologic disorders in children in resource-limited settings. The burden of neurologic disorders in children is high in resource-limited settings. Barriers to optimal care include lack of trained personnel, limited access to diagnostic technology, and limited availability of drugs used to treat common conditions. Several solutions have been suggested to deal with these challenges including increased collaborations to train neurologists willing to practice in resource-limited settings and increased training of physician extenders or community health workers. Further studies are necessary to improve our understanding of the epidemiology of neurologic disorders in resource-limited settings. Future epidemiologic studies should incorporate multiple countries in resource-limited settings and utilize standardized definitions and methodologies to enable comparison across regions. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 2: Resource allocation and smoothing model, programmer's manual

NASA Technical Reports Server (NTRS)

1971-01-01

Appendixes are presented that provide model input requirements, a sample case, flow charts, and a program listing. At the beginning of each appendix, descriptive details and technical comments are provided to indicate any special instructions applicable to the use of that appendix. In addition, the program listing includes comment cards that state the purpose of each subroutine in the complete program and describe operations performed within that subroutine. The input requirements includes details on the many options that adapt the program to the specific needs of the analyst for a particular problem.

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

Input/output behavior of supercomputing applications

NASA Technical Reports Server (NTRS)

Miller, Ethan L.

1991-01-01

The collection and analysis of supercomputer I/O traces and their use in a collection of buffering and caching simulations are described. This serves two purposes. First, it gives a model of how individual applications running on supercomputers request file system I/O, allowing system designer to optimize I/O hardware and file system algorithms to that model. Second, the buffering simulations show what resources are needed to maximize the CPU utilization of a supercomputer given a very bursty I/O request rate. By using read-ahead and write-behind in a large solid stated disk, one or two applications were sufficient to fully utilize a Cray Y-MP CPU.

Optimal Regulation of Virtual Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall Anese, Emiliano; Guggilam, Swaroop S.; Simonetto, Andrea

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence andmore » tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.« less

Development of Optimization method about Capital Structure and Senior-Sub Structure by considering Project-Risk

NASA Astrophysics Data System (ADS)

Kawamoto, Shigeru; Ikeda, Yuichi; Fukui, Chihiro; Tateshita, Fumihiko

Private finance initiative is a business scheme that materializes social infrastructure and public services by utilizing private-sector resources. In this paper we propose a new method to optimize capital structure, which is the ratio of capital to debt, and senior-sub structure, which is the ratio of senior loan to subordinated loan, for private finance initiative. We make the quantitative analysis of a private finance initiative's project using the proposed method. We analyze trade-off structure between risk and return in the project, and optimize capital structure and senior-sub structure. The method we propose helps to improve financial stability of the project, and to make a fund raising plan that is expected to be reasonable for project sponsor and moneylender.

Feasibility of Stochastic Voltage/VAr Optimization Considering Renewable Energy Resources for Smart Grid

NASA Astrophysics Data System (ADS)

Momoh, James A.; Salkuti, Surender Reddy

2016-06-01

This paper proposes a stochastic optimization technique for solving the Voltage/VAr control problem including the load demand and Renewable Energy Resources (RERs) variation. The RERs often take along some inputs like stochastic behavior. One of the important challenges i. e., Voltage/VAr control is a prime source for handling power system complexity and reliability, hence it is the fundamental requirement for all the utility companies. There is a need for the robust and efficient Voltage/VAr optimization technique to meet the peak demand and reduction of system losses. The voltages beyond the limit may damage costly sub-station devices and equipments at consumer end as well. Especially, the RERs introduces more disturbances and some of the RERs are not even capable enough to meet the VAr demand. Therefore, there is a strong need for the Voltage/VAr control in RERs environment. This paper aims at the development of optimal scheme for Voltage/VAr control involving RERs. In this paper, Latin Hypercube Sampling (LHS) method is used to cover full range of variables by maximally satisfying the marginal distribution. Here, backward scenario reduction technique is used to reduce the number of scenarios effectively and maximally retain the fitting accuracy of samples. The developed optimization scheme is tested on IEEE 24 bus Reliability Test System (RTS) considering the load demand and RERs variation.

Hybrid PV/Wind Power Systems Incorporating Battery Storage and Considering the Stochastic Nature of Renewable Resources

NASA Astrophysics Data System (ADS)

Barnawi, Abdulwasa Bakr

Hybrid power generation system and distributed generation technology are attracting more investments due to the growing demand for energy nowadays and the increasing awareness regarding emissions and their environmental impacts such as global warming and pollution. The price fluctuation of crude oil is an additional reason for the leading oil producing countries to consider renewable resources as an alternative. Saudi Arabia as the top oil exporter country in the word announced the "Saudi Arabia Vision 2030" which is targeting to generate 9.5 GW of electricity from renewable resources. Two of the most promising renewable technologies are wind turbines (WT) and photovoltaic cells (PV). The integration or hybridization of photovoltaics and wind turbines with battery storage leads to higher adequacy and redundancy for both autonomous and grid connected systems. This study presents a method for optimal generation unit planning by installing a proper number of solar cells, wind turbines, and batteries in such a way that the net present value (NPV) is minimized while the overall system redundancy and adequacy is maximized. A new renewable fraction technique (RFT) is used to perform the generation unit planning. RFT was tested and validated with particle swarm optimization and HOMER Pro under the same conditions and environment. Renewable resources and load randomness and uncertainties are considered. Both autonomous and grid-connected system designs were adopted in the optimal generation units planning process. An uncertainty factor was designed and incorporated in both autonomous and grid connected system designs. In the autonomous hybrid system design model, the strategy including an additional amount of operation reserve as a percent of the hourly load was considered to deal with resource uncertainty since the battery storage system is the only backup. While in the grid-connected hybrid system design model, demand response was incorporated to overcome the impact of uncertainty and perform energy trading between the hybrid grid utility and main grid utility in addition to the designed uncertainty factor. After the generation unit planning was carried out and component sizing was determined, adequacy evaluation was conducted by calculating the loss of load expectation adequacy index for different contingency criteria considering probability of equipment failure. Finally, a microgrid planning was conducted by finding the proper size and location to install distributed generation units in a radial distribution network.

A Modeling Framework for Optimal Computational Resource Allocation Estimation: Considering the Trade-offs between Physical Resolutions, Uncertainty and Computational Costs

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.; Rajagopal, R.

2014-12-01

Hydrogeological models that represent flow and transport in subsurface domains are usually large-scale with excessive computational complexity and uncertain characteristics. Uncertainty quantification for predicting flow and transport in heterogeneous formations often entails utilizing a numerical Monte Carlo framework, which repeatedly simulates the model according to a random field representing hydrogeological characteristics of the field. The physical resolution (e.g. grid resolution associated with the physical space) for the simulation is customarily chosen based on recommendations in the literature, independent of the number of Monte Carlo realizations. This practice may lead to either excessive computational burden or inaccurate solutions. We propose an optimization-based methodology that considers the trade-off between the following conflicting objectives: time associated with computational costs, statistical convergence of the model predictions and physical errors corresponding to numerical grid resolution. In this research, we optimally allocate computational resources by developing a modeling framework for the overall error based on a joint statistical and numerical analysis and optimizing the error model subject to a given computational constraint. The derived expression for the overall error explicitly takes into account the joint dependence between the discretization error of the physical space and the statistical error associated with Monte Carlo realizations. The accuracy of the proposed framework is verified in this study by applying it to several computationally extensive examples. Having this framework at hand aims hydrogeologists to achieve the optimum physical and statistical resolutions to minimize the error with a given computational budget. Moreover, the influence of the available computational resources and the geometric properties of the contaminant source zone on the optimum resolutions are investigated. We conclude that the computational cost associated with optimal allocation can be substantially reduced compared with prevalent recommendations in the literature.

Parallelizing ATLAS Reconstruction and Simulation: Issues and Optimization Solutions for Scaling on Multi- and Many-CPU Platforms

NASA Astrophysics Data System (ADS)

Leggett, C.; Binet, S.; Jackson, K.; Levinthal, D.; Tatarkhanov, M.; Yao, Y.

2011-12-01

Thermal limitations have forced CPU manufacturers to shift from simply increasing clock speeds to improve processor performance, to producing chip designs with multi- and many-core architectures. Further the cores themselves can run multiple threads as a zero overhead context switch allowing low level resource sharing (Intel Hyperthreading). To maximize bandwidth and minimize memory latency, memory access has become non uniform (NUMA). As manufacturers add more cores to each chip, a careful understanding of the underlying architecture is required in order to fully utilize the available resources. We present AthenaMP and the Atlas event loop manager, the driver of the simulation and reconstruction engines, which have been rewritten to make use of multiple cores, by means of event based parallelism, and final stage I/O synchronization. However, initial studies on 8 andl6 core Intel architectures have shown marked non-linearities as parallel process counts increase, with as much as 30% reductions in event throughput in some scenarios. Since the Intel Nehalem architecture (both Gainestown and Westmere) will be the most common choice for the next round of hardware procurements, an understanding of these scaling issues is essential. Using hardware based event counters and Intel's Performance Tuning Utility, we have studied the performance bottlenecks at the hardware level, and discovered optimization schemes to maximize processor throughput. We have also produced optimization mechanisms, common to all large experiments, that address the extreme nature of today's HEP code, which due to it's size, places huge burdens on the memory infrastructure of today's processors.

A method to evaluate process performance by integrating time and resources

NASA Astrophysics Data System (ADS)

Wang, Yu; Wei, Qingjie; Jin, Shuang

2017-06-01

The purpose of process mining is to improve the existing process of the enterprise, so how to measure the performance of the process is particularly important. However, the current research on the performance evaluation method is still insufficient. The main methods of evaluation are mainly using time or resource. These basic statistics cannot evaluate process performance very well. In this paper, a method of evaluating the performance of the process based on time dimension and resource dimension is proposed. This method can be used to measure the utilization and redundancy of resources in the process. This paper will introduce the design principle and formula of the evaluation algorithm. Then, the design and the implementation of the evaluation method will be introduced. Finally, we will use the evaluating method to analyse the event log from a telephone maintenance process and propose an optimization plan.

Management of multiple myeloma in resource-constrained settings.

PubMed

Kumar, Lalit; Kumar Sahoo, Ranjit

2016-12-01

The prognosis of patients with multiple myeloma (MM) has improved significantly in the past two decades. This is attributed to use of novel agents for induction, high-dose chemotherapy and autologous stem cell transplantation (ASCT), maintenance therapy, and improved supportive care. Currently, evidence-based management guidelines/recommendations developed by International societies/groups are being followed partially in low-resource settings. Lack of quality diagnostics (eg, cytogenetics/fluorescence in situ hybridization (FISH), serum free light chains), novel therapeutics, and trained manpower, and limited financial resources are key challanges. An optimal utilization of available resources with continued educational activities of treating physicians focused on improving knowledge in the management of such patients may be a way forward to improve the outcome of myeloma patients in these countries. Our current approach to the management of this disease is presented here through a discussion of clinical vignettes. Copyright © 2016 Elsevier Inc. All rights reserved.

Aligning with physicians to regionalize services.

PubMed

Fink, John

2014-11-01

When effectively designed and implemented, regionalization allows a health system to coordinate care, eliminate redundancies, reduce costs, optimize resource utilization, and improve outcomes. The preferred model to manage service lines regionally will depend on each facility's capabilities and the willingness of physicians to accept changes in clinical delivery. Health systems can overcome physicians' objections to regionalization by implementing a hospital-physician alignment structure that gives a measure of shared control in the management of the organization.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

PubMed

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon; Cho, Sungrae

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform

PubMed Central

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively. PMID:28796804

Optimizing Biorefinery Design and Operations via Linear Programming Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Talmadge, Michael; Batan, Liaw; Lamers, Patrick

The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LPmore » models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for maximizing the potential benefits of biomass utilization for production of fuels, chemicals and power.« less

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

Suggestions to ameliorate the inequity in urban/rural allocation of healthcare resources in China.

PubMed

Chen, Yiyi; Yin, Zhou; Xie, Qiong

2014-05-01

The imbalance in the allocation in healthcare resources between urban and rural areas has become a main focus of the recent medical reforms adopted in China. However, systematic analysis has identified wide differences in the allocation of healthcare resources between urban and rural areas, including healthcare expenditures and the number of healthcare facilities, available beds, and personnel. Therefore, the aim of this report was to identify ethical considerations in current governmental policies to rectify existing problems in the distribution of healthcare resources. Our findings indicate that the inequality in the distribution of healthcare resources does not adhere to ethical standards and the policies are flawed because they give rise to differences in the availability of medical care to urban and rural communities. To optimize the allocation of medical healthcare resources, countermeasures are proposed to formulate policies to urge the flow of public healthcare resources to rural areas, strengthen the responsibilities of both governmental and public financial investments, increase the construction of public healthcare facilities in rural areas, promote the quality of healthcare resources, adjust resource allocations to rural public healthcare facilities, and improve resource utilization efficiency by establishing two-way referral mechanisms.

Novel optimization technique of isolated microgrid with hydrogen energy storage.

PubMed

Beshr, Eman Hassan; Abdelghany, Hazem; Eteiba, Mahmoud

2018-01-01

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.

Novel optimization technique of isolated microgrid with hydrogen energy storage

PubMed Central

Abdelghany, Hazem; Eteiba, Mahmoud

2018-01-01

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm. PMID:29466433

Pervious concrete mix optimization for sustainable pavement solution

NASA Astrophysics Data System (ADS)

Barišić, Ivana; Galić, Mario; Netinger Grubeša, Ivanka

2017-10-01

In order to fulfill requirements of sustainable road construction, new materials for pavement construction are investigated with the main goal to preserve natural resources and achieve energy savings. One of such sustainable pavement material is pervious concrete as a new solution for low volume pavements. To accommodate required strength and porosity as the measure of appropriate drainage capability, four mixtures of pervious concrete are investigated and results of laboratory tests of compressive and flexural strength and porosity are presented. For defining the optimal pervious concrete mixture in a view of aggregate and financial savings, optimization model is utilized and optimal mixtures defined according to required strength and porosity characteristics. Results of laboratory research showed that comparing single-sized aggregate pervious concrete mixtures, coarse aggregate mixture result in increased porosity but reduced strengths. The optimal share of the coarse aggregate turn to be 40.21%, the share of fine aggregate is 49.79% for achieving required compressive strength of 25 MPa, flexural strength of 4.31 MPa and porosity of 21.66%.

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

NASA Astrophysics Data System (ADS)

Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

2017-07-01

Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

Two-phase strategy of controlling motor coordination determined by task performance optimality.

PubMed

Shimansky, Yury P; Rand, Miya K

2013-02-01

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model's utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.

Optimizing Land and Water Use at the Local Level to Enhance Global Food Security through Virtual Resources Trade in the World

NASA Astrophysics Data System (ADS)

Cai, X.; Zhang, X.; Zhu, T.

2014-12-01

Global food security is constrained by local and regional land and water availability, as well as other agricultural input limitations and inappropriate national and global regulations. In a theoretical context, this study assumes that optimal water and land uses in local food production to maximize food security and social welfare at the global level can be driven by global trade. It follows the context of "virtual resources trade", i.e., utilizing international trade of agricultural commodities to reduce dependency on local resources, and achieves land and water savings in the world. An optimization model based on the partial equilibrium of agriculture is developed for the analysis, including local commodity production and land and water resources constraints, demand by country, and global food market. Through the model, the marginal values (MVs) of social welfare for water and land at the level of so-called food production units (i.e., sub-basins with similar agricultural production conditions) are derived and mapped in the world. In this personation, we will introduce the model structure, explain the meaning of MVs at the local level and their distribution around the world, and discuss the policy implications for global communities to enhance global food security. In particular, we will examine the economic values of water and land under different world targets of food security (e.g., number of malnourished population or children in a future year). In addition, we will also discuss the opportunities on data to improve such global modeling exercises.

Developing Intelligent System Dynamic Management Instruments on Water-Food-Energy Nexus in Response to Urbanization

NASA Astrophysics Data System (ADS)

Tsai, W. P.; Chang, F. J.; Lur, H. S.; Fan, C. H.; Hu, M. C.; Huang, T. L.

2016-12-01

Water, food and energy are the most essential natural resources needed to sustain life. Water-Food-Energy Nexus (WFE Nexus) has nowadays caught global attention upon natural resources scarcity and their interdependency. In the past decades, Taiwan's integrative development has undergone drastic changes due to population growth, urbanization and excessive utilization of natural resources. The research intends to carry out interdisciplinary studies on WFE Nexus based on data collection and analysis as well as technology innovation, with a mission to develop a comprehensive solution to configure the synergistic utilization of WFE resources in an equal and secure manner for building intelligent dynamic green cities. This study aims to establish the WFE Nexus through interdisciplinary research. This study will probe the appropriate and secure resources distribution and coopetition relationship by applying and developing techniques of artificial intelligence, system dynamics, life cycle assessment, and synergy management under data mining, system analysis and scenario analysis. The issues of synergy effects, economic benefits and sustainable social development will be evaluated as well. First, we will apply the system dynamics to identify the interdependency indicators of WFE Nexus in response to urbanization and build the dynamic relationship among food production, irrigation water resource and energy consumption. Then, we conduct comparative studies of WFE Nexus between the urbanization and the un-urbanization area (basin) to provide a referential guide for optimal resource-policy nexus management. We expect to the proposed solutions can help achieve the main goals of the research, which is the promotion of human well-being and moving toward sustainable green economy and prosperous society.

Data mining to support simulation modeling of patient flow in hospitals.

PubMed

Isken, Mark W; Rajagopalan, Balaji

2002-04-01

Spiraling health care costs in the United States are driving institutions to continually address the challenge of optimizing the use of scarce resources. One of the first steps towards optimizing resources is to utilize capacity effectively. For hospital capacity planning problems such as allocation of inpatient beds, computer simulation is often the method of choice. One of the more difficult aspects of using simulation models for such studies is the creation of a manageable set of patient types to include in the model. The objective of this paper is to demonstrate the potential of using data mining techniques, specifically clustering techniques such as K-means, to help guide the development of patient type definitions for purposes of building computer simulation or analytical models of patient flow in hospitals. Using data from a hospital in the Midwest this study brings forth several important issues that researchers need to address when applying clustering techniques in general and specifically to hospital data.

The degradation of wheat straw lignin

NASA Astrophysics Data System (ADS)

Liang, Jiaqi

2017-03-01

Lignin is a kind of formed by polymerization of aromatic alcohol, prices are lower and sources of renewable resources. Using lignin as raw material, through the push to resolve together preparation phenolic high value-added fine chemicals alkanes and aromatic hydrocarbons, such as the high grade biofuels, can partly replace fossil fuels as raw material to the production process, biomass resources is an important part of the comprehensive utilization of effective components. In lignin push solve clustering method, catalytic hydrogenolysis can directly to the lignin into liquid fuels, low oxygen content in the use of biofuels shows great potential. In this paper, through the optimization of the reaction time, reaction temperature, catalyst type and solvent type, dosage of catalyst, etc factors, determines the alcoholysis - hydrogen solution two-step degradation of lignin, the optimal process conditions: lignin alcoholysis under 50% methanol and NaOH catalyst in the solution, the lignin in methanol solution and 50% hydrogen solution under the Pd/C catalyst. In this process, the degradation of lignin yield can reach 42%.

What's wrong with hazard-ranking systems? An expository note.

PubMed

Cox, Louis Anthony Tony

2009-07-01

Two commonly recommended principles for allocating risk management resources to remediate uncertain hazards are: (1) select a subset to maximize risk-reduction benefits (e.g., maximize the von Neumann-Morgenstern expected utility of the selected risk-reducing activities), and (2) assign priorities to risk-reducing opportunities and then select activities from the top of the priority list down until no more can be afforded. When different activities create uncertain but correlated risk reductions, as is often the case in practice, then these principles are inconsistent: priority scoring and ranking fails to maximize risk-reduction benefits. Real-world risk priority scoring systems used in homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, business risk matrices, and many other important applications do not exploit correlations among risk-reducing opportunities or optimally diversify risk-reducing investments. As a result, they generally make suboptimal risk management recommendations. Applying portfolio optimization methods instead of risk prioritization ranking, rating, or scoring methods can achieve greater risk-reduction value for resources spent.

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2012-01-01

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things.

PubMed

Yi, Meng; Chen, Qingkui; Xiong, Neal N

2016-11-03

This paper considers the distributed access and control problem of massive wireless sensor networks' data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

PubMed Central

Niu, Liyong; Zhang, Di

2015-01-01

Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly. PMID:26236770

What Works for You? Using Teacher Feedback to Inform Adaptations of Pivotal Response Training for Classroom Use

PubMed Central

Stahmer, Aubyn C.; Suhrheinrich, Jessica; Reed, Sarah; Schreibman, Laura

2012-01-01

Several evidence-based practices (EBPs) have been identified as efficacious for the education of students with autism spectrum disorders (ASD). However, effectiveness research has rarely been conducted in schools and teachers express skepticism about the clinical utility of EBPs for the classroom. Innovative methods are needed to optimally adapt EBPs for community use. This study utilizes qualitative methods to identify perceived benefits and barriers of classroom implementation of a specific EBP for ASD, Pivotal Response Training (PRT). Teachers' perspectives on the components of PRT, use of PRT as a classroom intervention strategy, and barriers to the use of PRT were identified through guided discussion. Teachers found PRT valuable; however, they also found some components challenging. Specific teacher recommendations for adaptation and resource development are discussed. This process of obtaining qualitative feedback from frontline practitioners provides a generalizable model for researchers to collaborate with teachers to optimally promote EBPs for classroom use. PMID:23209896

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization.

PubMed

Niu, Liyong; Zhang, Di

2015-01-01

Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.

What works for you? Using teacher feedback to inform adaptations of pivotal response training for classroom use.

PubMed

Stahmer, Aubyn C; Suhrheinrich, Jessica; Reed, Sarah; Schreibman, Laura

2012-01-01

Several evidence-based practices (EBPs) have been identified as efficacious for the education of students with autism spectrum disorders (ASD). However, effectiveness research has rarely been conducted in schools and teachers express skepticism about the clinical utility of EBPs for the classroom. Innovative methods are needed to optimally adapt EBPs for community use. This study utilizes qualitative methods to identify perceived benefits and barriers of classroom implementation of a specific EBP for ASD, Pivotal Response Training (PRT). Teachers' perspectives on the components of PRT, use of PRT as a classroom intervention strategy, and barriers to the use of PRT were identified through guided discussion. Teachers found PRT valuable; however, they also found some components challenging. Specific teacher recommendations for adaptation and resource development are discussed. This process of obtaining qualitative feedback from frontline practitioners provides a generalizable model for researchers to collaborate with teachers to optimally promote EBPs for classroom use.

Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions

NASA Astrophysics Data System (ADS)

Liu, Dedi; Guo, Shenglian; Shao, Quanxi; Liu, Pan; Xiong, Lihua; Wang, Le; Hong, Xingjun; Xu, Yao; Wang, Zhaoli

2018-01-01

Human activities and climate change have altered the spatial and temporal distribution of water availability which is a principal prerequisite for allocation of different water resources. In order to quantify the impacts of climate change and human activities on water availability and optimal allocation of water resources, hydrological models and optimal water resource allocation models should be integrated. Given that increasing human water demand and varying water availability conditions necessitate adaptation measures, we propose a framework to assess the effects of these measures on optimal allocation of water resources. The proposed model and framework were applied to a case study of the middle and lower reaches of the Hanjiang River Basin in China. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) were employed to project future climate, and the Variable Infiltration Capacity (VIC) hydrological model was used to simulate the variability of flows under historical (1956-2011) and future (2012-2099) conditions. The water availability determined by simulating flow with the VIC hydrological model was used to establish the optimal water resources allocation model. The allocation results were derived under an extremely dry year (with an annual average water flow frequency of 95%), a very dry year (with an annual average water flow frequency of 90%), a dry year (with an annual average water flow frequency of 75%), and a normal year (with an annual average water flow frequency of 50%) during historical and future periods. The results show that the total available water resources in the study area and the inflow of the Danjiangkou Reservoir will increase in the future. However, the uneven distribution of water availability will cause water shortage problems, especially in the boundary areas. The effects of adaptation measures, including water saving, and dynamic control of flood limiting water levels (FLWLs) for reservoir operation, were assessed and implemented to alleviate water shortages. The negative impacts from the South-to-North Water Transfer Project (Middle Route) in the mid-lower reaches of the Hanjiang River Basin can be avoided through the dynamic control of FLWLs in Danjiangkou Reservoir, under the historical and future RCP2.6 and RCP4.5 scenarios. However, the effects of adaptation measures are limited due to their own constraints, such as the characteristics of the reservoirs influencing the FLWLs. The utilization of storm water appears necessary to meet future water demand. Overall, the results indicate that the framework for assessing the effects of adaptation measures on water resources allocation might aid water resources management, not only in the study area but also in other places where water availability conditions vary due to climate change and human activities.

Renewable Energy Optimization Report for Naval Station Newport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robichaud, R.; Mosey, G.; Olis, D.

2012-02-01

In 2008, the U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage the development of renewable energy (RE) on potentially contaminated land and mine sites. As part of this effort, EPA is collaborating with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) to evaluate RE options at Naval Station (NAVSTA) Newport in Newport, Rhode Island. NREL's Renewable Energy Optimization (REO) tool was utilized to identify RE technologies that present the best opportunity for life-cycle cost-effective implementation while also serving to reduce energy-related carbon dioxide emissions and increase the percentage of RE used atmore » NAVSTA Newport. The technologies included in REO are daylighting, wind, solar ventilation preheating (SVP), solar water heating, photovoltaics (PV), solar thermal (heating and electric), and biomass (gasification and cogeneration). The optimal mix of RE technologies depends on several factors including RE resources; technology cost and performance; state, utility, and federal incentives; and economic parameters (discount and inflation rates). Each of these factors was considered in this analysis. Technologies not included in REO that were investigated separately per NAVSTA Newport request include biofuels from algae, tidal power, and ground source heat pumps (GSHP).« less

Intranet and village community: optimization of public service based on electronic government at the local level

NASA Astrophysics Data System (ADS)

Pradana, G. W.; Fanida, E. H.; Niswah, F.

2018-01-01

The demand for good governance is directed towards the realization of efficiency, effectiveness, and clean government. The move is demonstrated through national and regional levels to develop and implement electronic government concepts. Through the development of electronic government is done structuring management systems and work processes in the government environment by optimizing the utilization of information technology. One of the real forms of electronic government (e-Gov) implementation at the local level is the Intranet Sub-District program in Sukodono Sub-District, Sidoarjo. Intranet Sub-District is an innovation whose purpose is to realize the availability of information on the utilization of management, distribution, and storage of official scripts, and also the optimal delivery of information and communication in the implementation of guidance and supervision of local administration. The type of this paper is descriptive with a qualitative approach and focus on the implementation of the Intranet District Program in Sukodono District, Sidoarjo. The findings of the study are the limited number of human resources who have mastered ICT, the uneven network, the adequacy of institutional needs and the existence of budget support from the authorized institution and the information system has not accommodated all the service needs.

Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

NASA Astrophysics Data System (ADS)

Xu, Xiao-Feng

2018-03-01

Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

SVM classifier on chip for melanoma detection.

PubMed

Afifi, Shereen; GholamHosseini, Hamid; Sinha, Roopak

2017-07-01

Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.

Assessment of future crop yield and agricultural sustainable water use in north china plain using multiple crop models

NASA Astrophysics Data System (ADS)

Huang, G.

2016-12-01

Currently, studying crop-water response mechanism has become an important part in the development of new irrigation technology and optimal water allocation in water-scarce regions, which is of great significance to crop growth guidance, sustainable utilization of agricultural water, as well as the sustainable development of regional agriculture. Using multiple crop models(AquaCrop,SWAP,DNDC), this paper presents the results of simulating crop growth and agricultural water consumption of the winter-wheat and maize cropping system in north china plain. These areas are short of water resources, but generates about 23% of grain production for China. By analyzing the crop yields and the water consumption of the traditional flooding irrigation, the paper demonstrates quantitative evaluation of the potential amount of water use that can be reduced by using high-efficient irrigation approaches, such as drip irrigation. To maintain food supply and conserve water resources, the research concludes sustainable irrigation methods for the three provinces for sustainable utilization of agricultural water.

Ultrafiltration for acute decompensated heart failure: cost, reimbursement, and financial impact.

PubMed

Ross, Edward A; Bellamy, Frank B; Hawig, Scott; Kazory, Amir

2011-05-01

In addition to the proposed pathophysiologic mechanisms whereby ultrafiltration (UF) can be advantageous over diuretics in the treatment of heart failure, there can also be financial and resource-utilization reasons for pursuing this extracorporeal strategy. In those cases in which the clinical outcomes would be equivalent, however, the decision whether to pursue UF will depend greatly on the anticipated hospitalization length of stay (LOS), the patient population's pay or mix, the needs and costs for high-acuity (eg, intensive care unit) care, and widely varying expenses for the equipment and disposable supplies. From a fiscal perspective, the financial viability of UF programs revolves around how improvements in LOS, resource utilization, and readmissions relate to the typical diagnosis-driven (eg, diagnosis-related group) reimbursement. We analyzed the impact of these various factors so as to better understand how the intensity (and expense) of pharmaceutical and extracorporeal therapies impacts a single admission, as well as to serve as the basis for developing strategies for optimizing long-term care. 2011 Wiley Periodicals, Inc.

Improving diabetes population management efficiency with an informatics solution.

PubMed

Zai, Adrian; Grant, Richard; Andrews, Carl; Yee, Ronnie; Chueh, Henry

2007-10-11

Despite intensive resource use for diabetes management in the U.S., our care continues to fall short of evidence-based goals, partly due to system inefficiencies. Diabetes registries are increasingly being utilized as a critical tool for population level disease management by providing real-time data. Since the successful adoption of a diabetes registry depends on how well it integrates with disease management workflows, we optimized our current diabetes management workflow and designed our registry application around it.

Determining the Optimal Inventory Management Policy for Naval Medical Center San Diego’s Pharmacy

DTIC Science & Technology

2016-12-01

electronic or other system that the pharmacy’s staff can use to determine the actual on hand inventory of any items. If a pharmacist , technician or...pharmacy’s inventory: price, utilization, mix, and innovation (American Society for Health-System Pharmacists [ASHP], 2008). (1) Price Price is the cost...or the Pareto Principle can determine the best way to allocate resources and help plan inventory (American Society for Health-System Pharmacists

Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeForest, Nicholas; Mendes, Goncalo; Stadler, Michael

2013-06-02

In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a buildingmore » to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.« less

Comprehensive Study on Small and Low Cost Satellite Technology for Earth Observation with Case Study for Indonesia: Projection for 2002-2022

NASA Astrophysics Data System (ADS)

Djojodihardjo, Harijono

and economic progress, while facing global competitiveness locally as opportunities and challenges. Of particular importance is the utilization and development of earth observation capabilities for environmental natural resources imperatives to this end is quite significant. On one hand there may appear challenges to achieve unique and high quality requirements on many of the elements of social and economic progress, i.e. natural resources, human resources, market opportunities and geographical advantage; on the other hand one may face constraints in the financial system, cultural inertia and paradigm, and the need to carry forward large momentum that may pull back technological and economic progress that may be characterized by a "roller coaster" dynamics. Satellite Technology for Earth Observation, its Utilization and Development is carried out with Indonesian Development Interest in mind. Space System Services and Players are identified. Mission objectives associated with Urban and Rural Areas as well as Satellite-Based Multimedia Technology Applications For Promoting Rural Development will be identified. System design analysis and synthesis will be elaborated and some alternatives will be presented following a unified system outlook. Ground Segment and Space Segment Architecture will be elaborated by carrying out Architecture Optimization.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

PubMed

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level. The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved. Copyright © 2014 Elsevier B.V. All rights reserved.

Design and implementation of online automatic judging system

NASA Astrophysics Data System (ADS)

Liang, Haohui; Chen, Chaojie; Zhong, Xiuyu; Chen, Yuefeng

2017-06-01

For lower efficiency and poorer reliability in programming training and competition by currently artificial judgment, design an Online Automatic Judging (referred to as OAJ) System. The OAJ system including the sandbox judging side and Web side, realizes functions of automatically compiling and running the tested codes, and generating evaluation scores and corresponding reports. To prevent malicious codes from damaging system, the OAJ system utilizes sandbox, ensuring the safety of the system. The OAJ system uses thread pools to achieve parallel test, and adopt database optimization mechanism, such as horizontal split table, to improve the system performance and resources utilization rate. The test results show that the system has high performance, high reliability, high stability and excellent extensibility.

Economic challenges of hybrid microgrid: An analysis and approaches for rural electrification

NASA Astrophysics Data System (ADS)

Habibullah, Mohammad; Mahmud, Khizir; Koçar, Günnur; Islam, A. K. M. Sadrul; Salehin, Sayedus

2017-06-01

This paper focuses on the integration of three renewable resources: biogas, wind energy and solar energy, utilizing solar PV panels, a biogas generator, and a wind turbine, respectively, to analyze the technical and economic challenges of a hybrid micro-gird. The integration of these sources has been analyzed and optimized based on realistic data for a real location. Different combinations of these sources have been analyzed to find out the optimized combination based on the efficiency and the minimum cost of electricity (COE). Wind and solar energy are considered as the primary sources of power generation during off-peak hours, and any excess power is used to charge a battery bank. During peak hours, biogas generators produce power to support the additional demand. A business strategy to implement the integrated optimized system in rural areas is discussed.

Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors

NASA Astrophysics Data System (ADS)

Habibi Davijani, M.; Banihabib, M. E.; Nadjafzadeh Anvar, A.; Hashemi, S. R.

2016-02-01

In many discussions, work force is mentioned as the most important factor of production. Principally, work force is a factor which can compensate for the physical and material limitations and shortcomings of other factors to a large extent which can help increase the production level. On the other hand, employment is considered as an effective factor in social issues. The goal of the present research is the allocation of water resources so as to maximize the number of jobs created in the industry and agriculture sectors. An objective that has attracted the attention of policy makers involved in water supply and distribution is the maximization of the interests of beneficiaries and consumers in case of certain policies adopted. The present model applies the particle swarm optimization (PSO) algorithm in order to determine the optimum amount of water allocated to each water-demanding sector, area under cultivation, agricultural production, employment in the agriculture sector, industrial production and employment in the industry sector. Based on the results obtained from this research, by optimally allocating water resources in the central desert region of Iran, 1096 jobs can be created in the industry and agriculture sectors, which constitutes an improvement of about 13% relative to the previous situation (non-optimal water utilization). It is also worth mentioning that by optimizing the employment factor as a social parameter, the other areas such as the economic sector are influenced as well. For example, in this investigation, the resulting economic benefits (incomes) have improved from 73 billion Rials at baseline employment figures to 112 billion Rials in the case of optimized employment condition. Therefore, it is necessary to change the inter-sector and intra-sector water allocation models in this region, because this change not only leads to more jobs in this area, but also causes an improvement in the region's economic conditions.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Assessing the sustainability of lead utilization in China.

PubMed

Sun, Lingyu; Zhang, Chen; Li, Jinhui; Zeng, Xianlai

2016-12-01

Lead is not only one of heavy metals imposing environment and health risk, but also critical resource to maintain sustainable development of many industries. Recently, due to the shortage of fossil fuels, clean energy vehicles, including electric bicycle, have emerged and are widely adopted soon in the world. China became the world's largest producer of primary lead and a very significant consumer in the past decade, which has strained the supplies of China's lead deposits from lithosphere and boost the anthropogenic consumption of metallic lead and lead products. Here we summarize that China's lead demand will continually increase due to the rapid growth of electric vehicle, resulting in a short carrying duration of lead even with full lead recycling. With these applications increasing at an annual rate of 2%, the carrying duration of lead resource until 2030 will oblige that recycling rate should be not less than 90%. To sustain lead utilization in China, one approach would be to improve the utilization technology, collection system and recycling technology towards closed-loop supply chain. Other future endeavors should include optimizing lead industrial structure and development of new energy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

PubMed

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

An Optimization and Assessment on DG adoption in JapanesePrototype Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2005-11-30

This research investigates a method of choosing economicallyoptimal DER, expanding on prior studies at the Berkeley Lab using the DERdesign optimization program, the Distributed Energy Resources CustomerAdoption Model (DER-CAM). DER-CAM finds the optimal combination ofinstalled equipment from available DER technologies, given prevailingutility tariffs, site electrical and thermal loads, and a menu ofavailable equipment. It provides a global optimization, albeit idealized,that shows how the site energy load scan be served at minimum cost byselection and operation of on-site generation, heat recovery, andcooling. Five prototype Japanese commercial buildings are examined andDER-CAM applied to select thee conomically optimal DER system for each.The fivemore » building types are office, hospital, hotel, retail, and sportsfacility. Based on the optimization results, energy and emissionreductions are evaluated. Furthermore, a Japan-U.S. comparison study ofpolicy, technology, and utility tariffs relevant to DER installation ispresented. Significant decreases in fuel consumption, carbon emissions,and energy costs were seen in the DER-CAM results. Savings were mostnoticeable in the sports facility, followed by the hospital, hotel, andoffice building.« less

Optimization of the transmission of observable expectation values and observable statistics in continuous-variable teleportation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albano Farias, L.; Stephany, J.

2010-12-15

We analyze the statistics of observables in continuous-variable (CV) quantum teleportation in the formalism of the characteristic function. We derive expressions for average values of output-state observables, in particular, cumulants which are additive in terms of the input state and the resource of teleportation. Working with a general class of teleportation resources, the squeezed-bell-like states, which may be optimized in a free parameter for better teleportation performance, we discuss the relation between resources optimal for fidelity and those optimal for different observable averages. We obtain the values of the free parameter of the squeezed-bell-like states which optimize the central momentamore » and cumulants up to fourth order. For the cumulants the distortion between in and out states due to teleportation depends only on the resource. We obtain optimal parameters {Delta}{sub (2)}{sup opt} and {Delta}{sub (4)}{sup opt} for the second- and fourth-order cumulants, which do not depend on the squeezing of the resource. The second-order central momenta, which are equal to the second-order cumulants, and the photon number average are also optimized by the resource with {Delta}{sub (2)}{sup opt}. We show that the optimal fidelity resource, which has been found previously to depend on the characteristics of input, approaches for high squeezing to the resource that optimizes the second-order momenta. A similar behavior is obtained for the resource that optimizes the photon statistics, which is treated here using the sum of the squared differences in photon probabilities of input versus output states as the distortion measure. This is interpreted naturally to mean that the distortions associated with second-order momenta dominate the behavior of the output state for large squeezing of the resource. Optimal fidelity resources and optimal photon statistics resources are compared, and it is shown that for mixtures of Fock states both resources are equivalent.« less

Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework.

PubMed

Parenreng, Jumadi Mabe; Kitagawa, Akio

2018-05-17

Wireless Sensor Networks (WSNs) with limited battery, central processing units (CPUs), and memory resources are a widely implemented technology for early warning detection systems. The main advantage of WSNs is their ability to be deployed in areas that are difficult to access by humans. In such areas, regular maintenance may be impossible; therefore, WSN devices must utilize their limited resources to operate for as long as possible, but longer operations require maintenance. One method of maintenance is to apply a resource adaptation policy when a system reaches a critical threshold. This study discusses the application of a security level adaptation model, such as an ARSy Framework, for using resources more efficiently. A single node comprising a Raspberry Pi 3 Model B and a DS18B20 temperature sensor were tested in a laboratory under normal and stressful conditions. The result shows that under normal conditions, the system operates approximately three times longer than under stressful conditions. Maintaining the stability of the resources also enables the security level of a network's data output to stay at a high or medium level.

Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework

PubMed Central

Kitagawa, Akio

2018-01-01

Wireless Sensor Networks (WSNs) with limited battery, central processing units (CPUs), and memory resources are a widely implemented technology for early warning detection systems. The main advantage of WSNs is their ability to be deployed in areas that are difficult to access by humans. In such areas, regular maintenance may be impossible; therefore, WSN devices must utilize their limited resources to operate for as long as possible, but longer operations require maintenance. One method of maintenance is to apply a resource adaptation policy when a system reaches a critical threshold. This study discusses the application of a security level adaptation model, such as an ARSy Framework, for using resources more efficiently. A single node comprising a Raspberry Pi 3 Model B and a DS18B20 temperature sensor were tested in a laboratory under normal and stressful conditions. The result shows that under normal conditions, the system operates approximately three times longer than under stressful conditions. Maintaining the stability of the resources also enables the security level of a network’s data output to stay at a high or medium level. PMID:29772773

Analysis and Research on the Optimal Allocation of Regional Water Resources

NASA Astrophysics Data System (ADS)

rui-chao, Xi; yu-jie, Gu

2018-06-01

Starting from the basic concept of optimal allocation of water resources, taking the allocation of water resources in Tianjin as an example, the present situation of water resources in Tianjin is analyzed, and the multi-objective optimal allocation model of water resources is used to optimize the allocation of water resources. We use LINGO to solve the model, get the optimal allocation plan that meets the economic and social benefits, and put forward relevant policies and regulations, so as to provide theoretical which is basis for alleviating and solving the problem of water shortage.

Association of comorbidities with home care service utilization of patients with heart failure while receiving telehealth.

PubMed

Radhakrishnan, Kavita; Jacelon, Cynthia S; Bigelow, Carol; Roche, Joan P; Marquard, Jenna L; Bowles, Kathryn H

2013-01-01

Comorbidities adversely impact heart failure (HF) outcomes. Telehealth can assist healthcare providers, especially nurses, in guiding their patients to follow the HF regimen. However, factors, including comorbidity patterns, that act in combination with telehealth to reduce home care nursing utilization are still unclear. The purpose of this article was to examine the association of the comorbidity characteristics of HF patients with nursing utilization along with withdrawal from telehealth service during an episode of tele-home care. A descriptive, correlational study design using retrospective chart review was used. The sample comprised Medicare patients admitted to a New England home care agency who had HF as a diagnosis and had used telehealth from 2008 to 2010. The electronic documentation at the home care agency served as the data source, which included Outcome and Assessment Information Set data of patients with HF. Logistic and multiple regression analyses were used to analyze data. The sample consisted of 403 participants, of whom 70% were older than 75 years, 55% were female, and 94% were white. Comorbidities averaged 5.19 (SD, 1.92), ranging from 1 to 11, and nearly 40% of the participants had 5 or more comorbidities. The mean (SD) nursing contacts in the sample was 9.9 (4.7), ranging from 1 to 26, and 52 (12.7%) patients withdrew from telehealth service. For patients with HF on telehealth, comorbidity characteristics of anemia, anxiety, musculoskeletal, and depression were significantly associated with nursing utilization patterns, and renal failure, cancer, and depression comorbidities were significantly associated with withdrawal from telehealth service. Knowledge of the association of comorbidity characteristics with the home care service utilization patterns of patients with HF on telehealth can assist the home health nurse to develop a tailored care plan that attains optimal patient outcomes. Knowledge of such associations would also focus home care resources, avoiding redundancy of resource utilization in this era of strained healthcare resources.

Utilization of Supercapacitors in Adaptive Protection Applications for Resiliency against Communication Failures: A Size and Cost Optimization Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habib, Hany F; El Hariri, Mohamad; Elsayed, Ahmed

Microgrids’ adaptive protection techniques rely on communication signals from the point of common coupling to ad- just the corresponding relays’ settings for either grid-connected or islanded modes of operation. However, during communication out- ages or in the event of a cyberattack, relays settings are not changed. Thus adaptive protection schemes are rendered unsuc- cessful. Due to their fast response, supercapacitors, which are pre- sent in the microgrid to feed pulse loads, could also be utilized to enhance the resiliency of adaptive protection schemes to communi- cation outages. Proper sizing of the supercapacitors is therefore im- portant in order to maintainmore » a stable system operation and also reg- ulate the protection scheme’s cost. This paper presents a two-level optimization scheme for minimizing the supercapacitor size along with optimizing its controllers’ parameters. The latter will lead to a reduction of the supercapacitor fault current contribution and an increase in that of other AC resources in the microgrid in the ex- treme case of having a fault occurring simultaneously with a pulse load. It was also shown that the size of the supercapacitor can be reduced if the pulse load is temporary disconnected during the transient fault period. Simulations showed that the resulting super- capacitor size and the optimized controller parameters from the proposed two-level optimization scheme were feeding enough fault currents for different types of faults and minimizing the cost of the protection scheme.« less

Microgrid to enable optimal distributed energy retail and end-user demand response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ming; Feng, Wei; Marnay, Chris

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

Microgrid to enable optimal distributed energy retail and end-user demand response

DOE PAGES

Jin, Ming; Feng, Wei; Marnay, Chris; ...

2018-06-07

In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

PubMed

Abdullahi, Mohammed; Ngadi, Md Asri

2016-01-01

Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment

PubMed Central

Abdullahi, Mohammed; Ngadi, Md Asri

2016-01-01

Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan. PMID:27348127

Steps Toward Optimal Competitive Scheduling

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Crawford, James; Khatib, Lina; Brafman, Ronen

2006-01-01

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum of users preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum ofsers preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.

Lean principles to optimize instrument utilization for spine surgery in an academic medical center: an opportunity to standardize, cut costs, and build a culture of improvement.

PubMed

Lunardini, David; Arington, Richard; Canacari, Elena G; Gamboa, Kelly; Wagner, Katiri; McGuire, Kevin J

2014-09-15

Case study OBJECTIVE.: To optimize the utilization of operating room instruments for orthopedic and neurosurgical spine cases in an urban level 1 academic medical center through application of Lean principles. Process improvement systems such as Lean have been adapted to health care and offer an opportunity for frank assessment of surgical routines to increase efficiency and enhance value. The goal has been to safely reduce the financial burden to the health care system without compromising care and if possible reallocate these resources or gains in efficiency to further improve the value to the patient. The investigators identified instruments as a source of waste in the operating room and proposed a Lean process assessment. The instruments and the instrument processing workflow were described. An audit documented the utilization of each instrument by orthopedic surgeons and neurosurgeons through observation of spine cases. The data were then presented to the stakeholders, including surgeons, the perioperative director, and representatives from nursing, central processing, and the surgical technicians. Of the 38 cases audited, only 89 (58%) of the instruments were used at least once. On the basis of the data and stakeholder consensus, 63 (41%) of the instruments were removed, resulting in a weight reduction of 17.5 lb and consolidation of 2 instrument sets into 1. Projected cost savings were approximately $41,000 annually. Although new instruments were purchased to standardize sets, the return on investment was estimated to be 2 years. Inefficient surgical routines may comprise significant resource waste in an institution. Process assessment is an important tool in decreasing health care costs, with objectivity provided by Lean or similar principles, and essential impetus to change provided by stakeholders. 4.

[Research on resources chemistry of Chinese medicinal materials and resources recycling utilization ways and goals and tasks].

PubMed

Duan, Jin-ao; Su, Shu-lan; Guo, Sheng; Jiang, Shu; Liu, Pei; Yan, Hui; Qian, Da-wei; Zhu, Hua-xu; Tang, Yu-ping; Wu, Qi-nan

2015-09-01

The objects of research on the resources chemistry of Chinese medicinal materials (RCCMM) are promotion of efficient production, rational utilization and improving quality of CMM and natural products. The development of TCM cause depends on the efficient utilization and sustainable development of CMM, hinges on the technologies and methods for using and discovering medicinal biological resources, stand or fall on the extension of industy chains, detailed utilizaion of resource chemical components by multi-way, multi-level. All of these may help to the recycling utilization and sound development of RCMM. In this article, five respects were discussed to the RCCMM researches and resources recycling utilization ways and goals and tasks. First, based on the principle of resource scarcity, discovering or replacing CMM resources, protecting the rare or endangered species or resources. Second, based on the multifunctionality of CMM, realizing the value-added and value compensation, and promoting the utilization efficiency through systermatic and detailed exploitation and utilization. Third, based on the resource conservation and environment-friendly, reducing raw material consumption, lowering cost, promoting recycling utilization and elevating utilization efficiency. Fourth, based on the stratege of turning harm into good, using the invasive alien biological resources by multi-ways and enriching the medicial resources. Fifth, based on the method of structure modification of chemical components, exploring and enhancing the utility value of resouces chemical substances. These data should provide references and attention for improving the utilization efficiency, promoting the development of recycling economy, and changing the mode of economic growth of agriculture and industry of CMM fundamentally.

Unification theory of optimal life histories and linear demographic models in internal stochasticity.

PubMed

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of "Stochastic Control Theory" in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path-integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models.

Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity

PubMed Central

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258

Power Allocation Based on Data Classification in Wireless Sensor Networks

PubMed Central

Wang, Houlian; Zhou, Gongbo

2017-01-01

Limited node energy in wireless sensor networks is a crucial factor which affects the monitoring of equipment operation and working conditions in coal mines. In addition, due to heterogeneous nodes and different data acquisition rates, the number of arriving packets in a queue network can differ, which may lead to some queue lengths reaching the maximum value earlier compared with others. In order to tackle these two problems, an optimal power allocation strategy based on classified data is proposed in this paper. Arriving data is classified into dissimilar classes depending on the number of arriving packets. The problem is formulated as a Lyapunov drift optimization with the objective of minimizing the weight sum of average power consumption and average data class. As a result, a suboptimal distributed algorithm without any knowledge of system statistics is presented. The simulations, conducted in the perfect channel state information (CSI) case and the imperfect CSI case, reveal that the utility can be pushed arbitrarily close to optimal by increasing the parameter V, but with a corresponding growth in the average delay, and that other tunable parameters W and the classification method in the interior of utility function can trade power optimality for increased average data class. The above results show that data in a high class has priorities to be processed than data in a low class, and energy consumption can be minimized in this resource allocation strategy. PMID:28498346

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel

PubMed Central

Sakin, Sayef Azad; Alamri, Atif; Tran, Nguyen H.

2017-01-01

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies. PMID:29215591

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel.

PubMed

Sakin, Sayef Azad; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Alamri, Atif; Tran, Nguyen H; Fortino, Giancarlo

2017-12-07

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

Natural Environmental Service Support to NASA Vehicle, Technology, and Sensor Development Programs

NASA Technical Reports Server (NTRS)

1993-01-01

The research performed under this contract involved definition of the natural environmental parameters affecting the design, development, and operation of space and launch vehicles. The Universities Space Research Association (USRA) provided the manpower and resources to accomplish the following tasks: defining environmental parameters critical for design, development, and operation of launch vehicles; defining environmental forecasts required to assure optimal utilization of launch vehicles; and defining orbital environments of operation and developing models on environmental parameters affecting launch vehicle operations.

Clean fuels from biomass

NASA Technical Reports Server (NTRS)

Hsu, Y.-Y.

1976-01-01

The paper discusses the U.S. resources to provide fuels from agricultural products, the present status of conversion technology of clean fuels from biomass, and a system study directed to determine the energy budget, and environmental and socioeconomic impacts. Conversion processes are discussed relative to pyrolysis and anaerobic fermentation. Pyrolysis breaks the cellulose molecules to smaller molecules under high temperature in the absence of oxygen, wheras anaerobic fermentation is used to convert biomass to methane by means of bacteria. Cost optimization and energy utilization are also discussed.

A multiple-objective optimal exploration strategy

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1988-01-01

Exploration for natural resources is accomplished through partial sampling of extensive domains. Such imperfect knowledge is subject to sampling error. Complex systems of equations resulting from modelling based on the theory of correlated random fields are reduced to simple analytical expressions providing global indices of estimation variance. The indices are utilized by multiple objective decision criteria to find the best sampling strategies. The approach is not limited by geometric nature of the sampling, covers a wide range in spatial continuity and leads to a step-by-step procedure. ?? 1988.

Co-Optimization of Electricity Transmission and Generation Resources for Planning and Policy Analysis: Review of Concepts and Modeling Approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Venkat; Ho, Jonathan; Hobbs, Benjamin F.

2016-05-01

The recognition of transmission's interaction with other resources has motivated the development of co-optimization methods to optimize transmission investment while simultaneously considering tradeoffs with investments in electricity supply, demand, and storage resources. For a given set of constraints, co-optimized planning models provide solutions that have lower costs than solutions obtained from decoupled optimization (transmission-only, generation-only, or iterations between them). This paper describes co-optimization and provides an overview of approaches to co-optimizing transmission options, supply-side resources, demand-side resources, and natural gas pipelines. In particular, the paper provides an up-to-date assessment of the present and potential capabilities of existing co-optimization tools, andmore » it discusses needs and challenges for developing advanced co-optimization models.« less

Analysis of Water Resource Utilization Potential for Jiangsu Coastal Area ' in Nantong City

NASA Astrophysics Data System (ADS)

Ren, Li; Liu, Jin-Tao; Ni, Jian-Jun

2015-04-01

Along with the advance of the growth of population and social economy, requirements for water quality and quantity in coastal areas is getting higher and higher, but due to the uneven distribution of rainfall years and water exploitation, use and management level, the influence of the shortage of water resources is increasingly prominent, seriously restricting the social and economic sustainable development in this region. Accordingly, water resource utilization potential in Jiangsu coastal region is vital for water security in the region. Taking Nantong City as the study area, the regional water resources development and utilization status were evaluated. In this paper, the meaning of water resources, water resources development and utilization, and water resources development and utilization of the three stages of concepts such as system were discussed. Then the development and utilization of regional water resource evaluation were carried out, and the significance of regional society, economy, resources and environment and its development status quo of water resources were exploited. According to conditions and area source, an evaluation index system for development and utilization of water resources of Nantong was built up. The index layer was composed of 16 indicators. In this study, analytic hierarchy process (AHP) was used to determine of weights of indicators at all levels in the index system. Multistage fuzzy comprehensive evaluation model was selected to evaluate the water resources development and utilization status of Nantong, and then water resource utilization potential of Nantong was analyzed.

Efficient Graph-Based Resource Allocation Scheme Using Maximal Independent Set for Randomly- Deployed Small Star Networks

PubMed Central

Zhou, Jian; Wang, Lusheng; Wang, Weidong; Zhou, Qingfeng

2017-01-01

In future scenarios of heterogeneous and dense networks, randomly-deployed small star networks (SSNs) become a key paradigm, whose system performance is restricted to inter-SSN interference and requires an efficient resource allocation scheme for interference coordination. Traditional resource allocation schemes do not specifically focus on this paradigm and are usually too time consuming in dense networks. In this article, a very efficient graph-based scheme is proposed, which applies the maximal independent set (MIS) concept in graph theory to help divide SSNs into almost interference-free groups. We first construct an interference graph for the system based on a derived distance threshold indicating for any pair of SSNs whether there is intolerable inter-SSN interference or not. Then, SSNs are divided into MISs, and the same resource can be repetitively used by all the SSNs in each MIS. Empirical parameters and equations are set in the scheme to guarantee high performance. Finally, extensive scenarios both dense and nondense are randomly generated and simulated to demonstrate the performance of our scheme, indicating that it outperforms the classical max K-cut-based scheme in terms of system capacity, utility and especially time cost. Its achieved system capacity, utility and fairness can be close to the near-optimal strategy obtained by a time-consuming simulated annealing search. PMID:29113109

The laboratory-clinician team: a professional call to action to improve communication and collaboration for optimal patient care in chromosomal microarray testing.

PubMed

Wain, Karen E; Riggs, Erin; Hanson, Karen; Savage, Melissa; Riethmaier, Darlene; Muirhead, Andrea; Mitchell, Elyse; Packard, Bethanny Smith; Faucett, W Andrew

2012-10-01

The International Standards for Cytogenomic Arrays (ISCA) Consortium is a worldwide collaborative effort dedicated to optimizing patient care by improving the quality of chromosomal microarray testing. The primary effort of the ISCA Consortium has been the development of a database of copy number variants (CNVs) identified during the course of clinical microarray testing. This database is a powerful resource for clinicians, laboratories, and researchers, and can be utilized for a variety of applications, such as facilitating standardized interpretations of certain CNVs across laboratories or providing phenotypic information for counseling purposes when published data is sparse. A recognized limitation to the clinical utility of this database, however, is the quality of clinical information available for each patient. Clinical genetic counselors are uniquely suited to facilitate the communication of this information to the laboratory by virtue of their existing clinical responsibilities, case management skills, and appreciation of the evolving nature of scientific knowledge. We intend to highlight the critical role that genetic counselors play in ensuring optimal patient care through contributing to the clinical utility of the ISCA Consortium's database, as well as the quality of individual patient microarray reports provided by contributing laboratories. Current tools, paper and electronic forms, created to maximize this collaboration are shared. In addition to making a professional commitment to providing complete clinical information, genetic counselors are invited to become ISCA members and to become involved in the discussions and initiatives within the Consortium.

Improving Navy Recruiting with the New Planned Resource Optimization Model With Experimental Design (PROM-WED)

DTIC Science & Technology

2017-03-01

RECRUITING WITH THE NEW PLANNED RESOURCE OPTIMIZATION MODEL WITH EXPERIMENTAL DESIGN (PROM-WED) by Allison R. Hogarth March 2017 Thesis...with the New Planned Resource Optimization Model With Experimental Design (PROM-WED) 5. FUNDING NUMBERS 6. AUTHOR(S) Allison R. Hogarth 7. PERFORMING...has historically used a non -linear optimization model, the Planned Resource Optimization (PRO) model, to help inform decisions on the allocation of

Synergistic Utilization of Microwave Satellite Data and GRACE-Total Water Storage Anomaly for Improving Available Water Capacity Prediction in Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Gupta, M.; Bolten, J. D.; Lakshmi, V.

2015-12-01

The Mekong River is the longest river in Southeast Asia and the world's eighth largest in discharge with draining an area of 795,000 km² from the eastern watershed of the Tibetan Plateau to the Mekong Delta including three provinces of China, Myanmar, Lao PDR, Thailand, Cambodia and Viet Nam. This makes the life of people highly vulnerable to availability of the water resources as soil moisture is one of the major fundamental variables in global hydrological cycles. The day-to-day variability in soil moisture on field to global scales is an important quantity for early warning systems for events like flooding and drought. In addition to the extreme situations the accurate soil moisture retrieval are important for agricultural irrigation scheduling and water resource management. The present study proposes a method to determine the effective soil hydraulic parameters directly from information available for the soil moisture state from the recently launched SMAP (L-band) microwave remote sensing observations. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the physically based land surface model. This work addresses the improvement of available water capacity as the soil hydraulic parameters are optimized through the utilization of satellite-retrieved near surface soil moisture. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on FAO. The optimization process is divided into two steps: the state variable are optimized and the optimal parameter values are then transferred for retrieving soil moisture and streamflow. A homogeneous soil system is considered as the soil moisture from sensors such as AMSR-E/SMAP can only be retrieved for the top few centimeters of soil. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Study on the Inference Factors of Huangling Coking Coal Pyrolysis

NASA Astrophysics Data System (ADS)

Du, Meili; Yang, Zongyi; Fan, Jinwen

2018-01-01

In order to reasonably and efficiently utilize Huangling coking coal resource, coal particle, heating rate, holding time, pyrolysis temperature and others factors were dicussed for the influence of those factor on Huangling coking coal pyrolysis products. Several kinds of coal blending for coking experiments were carried out with different kinds of coal such as Huangling coking coal, Xida coal with high ash low sufur, Xinghuo fat coal with hign sulfur, Zhongxingyi coking coal with high sulfur, Hucun lean coal, mixed meager and lean coal. The results shown that the optimal coal particle size distribution was 0.5~1.5mm, the optimal heating rate was 8°C/min, the optimal holding time was 15min, the optimal pyrolysis temperature was 800°C for Huangling coking coal pyrolysis, the tar yield increased from 4.7% to 11.2%. The maximum tar yield of coal blending for coking under the best single factor experiment condition was 10.65% when the proportio of Huangling coking coal was 52%.

Influences of landscape heterogeneity on home-range sizes of brown bears

USGS Publications Warehouse

Mangipane, Lindsey S.; Belant, Jerrold L.; Hiller, Tim L.; Colvin, Michael E.; Gustine, David; Mangipane, Buck A.; Hilderbrand, Grant V.

2018-01-01

Animal space use is influenced by many factors and can affect individual survival and fitness. Under optimal foraging theory, individuals use landscapes to optimize high-quality resources while minimizing the amount of energy used to acquire them. The spatial resource variability hypothesis states that as patchiness of resources increases, individuals use larger areas to obtain the resources necessary to meet energetic requirements. Additionally, under the temporal resource variability hypothesis, seasonal variation in available resources can reduce distances moved while providing a variety of food sources. Our objective was to determine if seasonal home ranges of brown bears (Ursus arctos) were influenced by temporal availability and spatial distribution of resources and whether individual reproductive status, sex, or size (i.e., body mass) mediated space use. To test our hypotheses, we radio collared brown bears (n = 32 [9 male, 23 female]) in 2014–2016 and used 18 a prioriselected linear models to evaluate seasonal utilization distributions (UD) in relation to our hypotheses. Our top-ranked model by AICc, supported the spatial resource variability hypothesis and included percentage of like adjacency (PLADJ) of all cover types (P < 0.01), reproductive class (P > 0.17 for males, solitary females, and females with dependent young), and body mass (kg; P = 0.66). Based on this model, for every percentage increase in PLADJ, UD area was predicted to increase 1.16 times for all sex and reproductive classes. Our results suggest that landscape heterogeneity influences brown bear space use; however, we found that bears used larger areas when landscape homogeneity increased, presumably to gain a diversity of food resources. Our results did not support the temporal resource variability hypothesis, suggesting that the spatial distribution of food was more important than seasonal availability in relation to brown bear home range size.

Building from within: pastoral insights into community resources and assets.

PubMed

Ford, Cassandra D

2013-01-01

To explore perceptions of community pastors regarding the extent of community resources and assets in a rural, Southern, African American community. Utilizing a qualitative, descriptive design, interviews were conducted with six African American pastors. Interviews were conducted using a semi-structured interview guide based on an assets-oriented approach. Pastors discussed various resources and assets, probable within the community that may be considered as support for program development. Key themes included: (1) community strengths, (2) community support, and (3) resources for a healthy lifestyle. The church was identified, throughout the interviews, as a primary source of strength and support for community members. In this study of African American pastors, various perceptions of community resources were identified. Findings indicate that a sample, rural, Southern, African American community has a wealth of resources and assets, but additional resources related to health promotion are still necessary to produce optimal results. Specific programs to prevent chronic conditions such as cardiovascular disease can provide an effective means for addressing related health disparities. Programs implemented through churches can reach large numbers of individuals in the community and provide an important source of sustainable efforts to improve the health of African Americans. © 2013 Wiley Periodicals, Inc.

Optimal Utilization of Donor Grafts With Extended Criteria

PubMed Central

Cameron, Andrew M.; Ghobrial, R Mark; Yersiz, Hasan; Farmer, Douglas G.; Lipshutz, Gerald S.; Gordon, Sherilyn A.; Zimmerman, Michael; Hong, Johnny; Collins, Thomas E.; Gornbein, Jeffery; Amersi, Farin; Weaver, Michael; Cao, Carlos; Chen, Tony; Hiatt, Jonathan R.; Busuttil, Ronald W.

2006-01-01

Objective: Severely limited organ resources mandate maximum utilization of donor allografts for orthotopic liver transplantation (OLT). This work aimed to identify factors that impact survival outcomes for extended criteria donors (ECD) and developed an ECD scoring system to facilitate graft-recipient matching and optimize utilization of ECDs. Methods: Retrospective analysis of over 1000 primary adult OLTs at UCLA. Extended criteria (EC) considered included donor age (>55 years), donor hospital stay (>5 days), cold ischemia time (>10 hours), and warm ischemia time (>40 minutes). One point was assigned for each extended criterion. Cox proportional hazard regression model was used for multivariate analysis. Results: Of 1153 allografts considered in the study, 568 organs exhibited no extended criteria (0 score), while 429, 135 and 21 donor allografts exhibited an EC score of 1, 2 and 3, respectively. Overall 1-year patient survival rates were 88%, 82%, 77% and 48% for recipients with EC scores of 0, 1, 2 and 3 respectively (P < 0.001). Adjusting for recipient age and urgency at the time of transplantation, multivariate analysis identified an ascending mortality risk ratio of 1.4 and 1.8 compared to a score of 0 for an EC score of 1, and 2 (P < 0.01) respectively. In contrast, an EC score of 3 was associated with a mortality risk ratio of 4.5 (P < 0.001). Further, advanced recipient age linearly increased the death hazard ratio, while an urgent recipient status increased the risk ratio of death by 50%. Conclusions: Extended criteria donors can be scored using readily available parameters. Optimizing perioperative variables and matching ECD allografts to appropriately selected recipients are crucial to maintain acceptable outcomes and represent a preferable alternative to both high waiting list mortality and to a potentially futile transplant that utilizes an ECD for a critically ill recipient. PMID:16772778

Availability analysis of mechanical systems with condition-based maintenance using semi-Markov and evaluation of optimal condition monitoring interval

NASA Astrophysics Data System (ADS)

Kumar, Girish; Jain, Vipul; Gandhi, O. P.

2018-03-01

Maintenance helps to extend equipment life by improving its condition and avoiding catastrophic failures. Appropriate model or mechanism is, thus, needed to quantify system availability vis-a-vis a given maintenance strategy, which will assist in decision-making for optimal utilization of maintenance resources. This paper deals with semi-Markov process (SMP) modeling for steady state availability analysis of mechanical systems that follow condition-based maintenance (CBM) and evaluation of optimal condition monitoring interval. The developed SMP model is solved using two-stage analytical approach for steady-state availability analysis of the system. Also, CBM interval is decided for maximizing system availability using Genetic Algorithm approach. The main contribution of the paper is in the form of a predictive tool for system availability that will help in deciding the optimum CBM policy. The proposed methodology is demonstrated for a centrifugal pump.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S. PMID:23766551

Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort.

PubMed

Jeschek, Markus; Gerngross, Daniel; Panke, Sven

2016-03-31

Rational flux design in metabolic engineering approaches remains difficult since important pathway information is frequently not available. Therefore empirical methods are applied that randomly change absolute and relative pathway enzyme levels and subsequently screen for variants with improved performance. However, screening is often limited on the analytical side, generating a strong incentive to construct small but smart libraries. Here we introduce RedLibs (Reduced Libraries), an algorithm that allows for the rational design of smart combinatorial libraries for pathway optimization thereby minimizing the use of experimental resources. We demonstrate the utility of RedLibs for the design of ribosome-binding site libraries by in silico and in vivo screening with fluorescent proteins and perform a simple two-step optimization of the product selectivity in the branched multistep pathway for violacein biosynthesis, indicating a general applicability for the algorithm and the proposed heuristics. We expect that RedLibs will substantially simplify the refactoring of synthetic metabolic pathways.

The impact of short-term stochastic variability in solar irradiance on optimal microgrid design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schittekatte, Tim; Stadler, Michael; Cardoso, Gonçalo

2016-07-01

This paper proposes a new methodology to capture the impact of fast moving clouds on utility power demand charges observed in microgrids with photovoltaic (PV) arrays, generators, and electrochemical energy storage. It consists of a statistical approach to introduce sub-hourly events in the hourly economic accounting process. The methodology is implemented in the Distributed Energy Resources Customer Adoption Model (DER-CAM), a state of the art mixed integer linear model used to optimally size DER in decentralized energy systems. Results suggest that previous iterations of DER-CAM could undersize battery capacities. The improved model depicts more accurately the economic value of PVmore » as well as the synergistic benefits of pairing PV with storage.« less

Strategic planning for disaster recovery with stochastic last mile distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Russell Whitford; Van Hentenryck, Pascal; Coffrin, Carleton

2010-01-01

This paper considers the single commodity allocation problem (SCAP) for disaster recovery, a fundamental problem faced by all populated areas. SCAPs are complex stochastic optimization problems that combine resource allocation, warehouse routing, and parallel fleet routing. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This paper formalizes the specification of SCAPs and introduces a novel multi-stage hybrid-optimization algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. The algorithm was validated on hurricane disaster scenarios generated by Los Alamos National Laboratory using state-of-the-art disaster simulation toolsmore » and is deployed to aid federal organizations in the US.« less

Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty

NASA Astrophysics Data System (ADS)

Herman, Jonathan D.; Zeff, Harrison B.; Reed, Patrick M.; Characklis, Gregory W.

2014-10-01

While optimality is a foundational mathematical concept in water resources planning and management, "optimal" solutions may be vulnerable to failure if deeply uncertain future conditions deviate from those assumed during optimization. These vulnerabilities may produce severely asymmetric impacts across a region, making it vital to evaluate the robustness of management strategies as well as their impacts for regional stakeholders. In this study, we contribute a multistakeholder many-objective robust decision making (MORDM) framework that blends many-objective search and uncertainty analysis tools to discover key tradeoffs between water supply alternatives and their robustness to deep uncertainties (e.g., population pressures, climate change, and financial risks). The proposed framework is demonstrated for four interconnected water utilities representing major stakeholders in the "Research Triangle" region of North Carolina, U.S. The utilities supply well over one million customers and have the ability to collectively manage drought via transfer agreements and shared infrastructure. We show that water portfolios for this region that compose optimal tradeoffs (i.e., Pareto-approximate solutions) under expected future conditions may suffer significantly degraded performance with only modest changes in deeply uncertain hydrologic and economic factors. We then use the Patient Rule Induction Method (PRIM) to identify which uncertain factors drive the individual and collective vulnerabilities for the four cooperating utilities. Our framework identifies key stakeholder dependencies and robustness tradeoffs associated with cooperative regional planning, which are critical to understanding the tensions between individual versus regional water supply goals. Cooperative demand management was found to be the key factor controlling the robustness of regional water supply planning, dominating other hydroclimatic and economic uncertainties through the 2025 planning horizon. Results suggest that a modest reduction in the projected rate of demand growth (from approximately 3% per year to 2.4%) will substantially improve the utilities' robustness to future uncertainty and reduce the potential for regional tensions. The proposed multistakeholder MORDM framework offers critical insights into the risks and challenges posed by rising water demands and hydrological uncertainties, providing a planning template for regions now forced to confront rapidly evolving water scarcity risks.

Unified Performance and Power Modeling of Scientific Workloads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Shuaiwen; Barker, Kevin J.; Kerbyson, Darren J.

2013-11-17

It is expected that scientific applications executing on future large-scale HPC must be optimized not only in terms of performance, but also in terms of power consumption. As power and energy become increasingly constrained resources, researchers and developers must have access to tools that will allow for accurate prediction of both performance and power consumption. Reasoning about performance and power consumption in concert will be critical for achieving maximum utilization of limited resources on future HPC systems. To this end, we present a unified performance and power model for the Nek-Bone mini-application developed as part of the DOE's CESAR Exascalemore » Co-Design Center. Our models consider the impact of computation, point-to-point communication, and collective communication« less

Obtaining the Greatest Scientific Benefit from Observational Platforms by Consideration of the Relative Benefit of Observations

NASA Technical Reports Server (NTRS)

Chelberg, David; Drews, Frank; Fleeman, David; Welch, Lonnie; Marquart, Jane; Pfarr, Barbara

2003-01-01

One of the current trends in spacecraft software design is to increase the autonomy of onboard flight and science software. This is especially true when real-time observations may affect the observation schedule of a mission. For many science missions, such as those conducted by the Swift Burst Alert Telescope, the ability of the spacecraft to autonomously respond in real-time to unpredicted science events is crucial for mission success. We apply utility theory within resource management middleware to optimize the real-time performance of application software and achieve maximum system level benefit. We then explore how this methodology can be extended to manage both software and observational resources onboard a spacecraft to achieve the best possible observations.

Public health services and systems research: current state of finance research.

PubMed

Ingram, Richard C; Bernet, Patrick M; Costich, Julia F

2012-11-01

There is a growing recognition that the US public health system should strive for efficiency-that it should determine the optimal ways to utilize limited resources to improve and protect public health. The field of public health finance research is a critical part of efforts to understand the most efficient ways to use resources. This article discusses the current state of public health finance research through a review of public health finance literature, chronicles important lessons learned from public health finance research to date, discusses the challenges faced by those seeking to conduct financial research on the public health system, and discusses the role of public health finance research in relation to the broader endeavor of Public Health Services and Systems Research.

Review of dynamic optimization methods in renewable natural resource management

USGS Publications Warehouse

Williams, B.K.

1989-01-01

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

Energy optimization system

DOEpatents

Zhou, Zhi; de Bedout, Juan Manuel; Kern, John Michael; Biyik, Emrah; Chandra, Ramu Sharat

2013-01-22

A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

Protecting core networks with dual-homing: A study on enhanced network availability, resource efficiency, and energy-savings

NASA Astrophysics Data System (ADS)

Abeywickrama, Sandu; Furdek, Marija; Monti, Paolo; Wosinska, Lena; Wong, Elaine

2016-12-01

Core network survivability affects the reliability performance of telecommunication networks and remains one of the most important network design considerations. This paper critically examines the benefits arising from utilizing dual-homing in the optical access networks to provide resource-efficient protection against link and node failures in the optical core segment. Four novel, heuristic-based RWA algorithms that provide dedicated path protection in networks with dual-homing are proposed and studied. These algorithms protect against different failure scenarios (i.e. single link or node failures) and are implemented with different optimization objectives (i.e., minimization of wavelength usage and path length). Results obtained through simulations and comparison with baseline architectures indicate that exploiting dual-homed architecture in the access segment can bring significant improvements in terms of core network resource usage, connection availability, and power consumption.

Designing of cardanol based polyol and its curing kinetics with melamine formaldehyde resin

PubMed Central

Balgude, Dinesh Bapurao; Sabnis, Anagha Shyamsunder; Ghosh, Swapan Kumar

2017-01-01

Abstract Commercially used industrial baking enamels consist of alkyd or polyester resin with melamine formaldehyde. These resins are mainly derived from fossil resources. Considering growing environmental legislation regarding use of petroleum based raw materials, utilization of renewable resources to synthesize various chemistries can be the only obvious option as far as academia and industries are concerns. The present work deals with exploration of one of the natural resources (Cardanol) for polyol synthesis, its characterization (FTIR and NMR) and its curing behavior with melamine formaldehyde resin by differential scanning calorimetry (DSC). The optimized formulations from DSC study were further evaluated for general coating properties to study the suitability of developed polyol for industrial coating application. The experimental studies revealed that melamine content in the curing mixtures and thereby developed crosslinking density played an important role in deciding the coatings properties. PMID:29491791

IpexT: Integrated Planning and Execution for Military Satellite Tele-Communications

NASA Technical Reports Server (NTRS)

Plaunt, Christian; Rajan, Kanna

2004-01-01

The next generation of military communications satellites may be designed as a fast packet-switched constellation of spacecraft able to withstand substantial bandwidth capacity fluctuation in the face of dynamic resource utilization and rapid environmental changes including jamming of communication frequencies and unstable weather phenomena. We are in the process of designing an integrated scheduling and execution tool which will aid in the analysis of the design parameters needed for building such a distributed system for nominal and battlefield communications. This paper discusses the design of such a system based on a temporal constraint posting planner/scheduler and a smart executive which can cope with a dynamic environment to make a more optimal utilization of bandwidth than the current circuit switched based approach.

Optimizing health information technology's role in enabling comparative effectiveness research.

PubMed

Navathe, Amol S; Conway, Patrick H

2010-12-01

Health information technology (IT) is a key enabler of comparative effectiveness research (CER). Health IT standards for data sharing are essential to advancing the research data infrastructure, and health IT is critical to the next step of incorporating clinical data into data sources. Four key principles for advancement of CER are (1) utilization of data as a strategic asset, (2) leveraging public-private partnerships, (3) building robust, scalable technology platforms, and (4) coordination of activities across government agencies. To maximize the value of the resources, payers and providers must contribute data to initiatives, engage with government agencies on lessons learned, continue to develop new technologies that address key challenges, and utilize the data to improve patient outcomes and conduct research.

Health economic evaluation: important principles and methodology.

PubMed

Rudmik, Luke; Drummond, Michael

2013-06-01

To discuss health economic evaluation and improve the understanding of common methodology. This article discusses the methodology for the following types of economic evaluations: cost-minimization, cost-effectiveness, cost-utility, cost-benefit, and economic modeling. Topics include health-state utility measures, the quality-adjusted life year (QALY), uncertainty analysis, discounting, decision tree analysis, and Markov modeling. Economic evaluation is the comparative analysis of alternative courses of action in terms of both their costs and consequences. With increasing health care expenditure and limited resources, it is important for physicians to consider the economic impact of their interventions. Understanding common methodology involved in health economic evaluation will improve critical appraisal of the literature and optimize future economic evaluations. Copyright © 2012 The American Laryngological, Rhinological and Otological Society, Inc.

Addressing Climate Change in Long-Term Water Planning Using Robust Decisionmaking

NASA Astrophysics Data System (ADS)

Groves, D. G.; Lempert, R.

2008-12-01

Addressing climate change in long-term natural resource planning is difficult because future management conditions are deeply uncertain and the range of possible adaptation options are so extensive. These conditions pose challenges to standard optimization decision-support techniques. This talk will describe a methodology called Robust Decisionmaking (RDM) that can complement more traditional analytic approaches by utilizing screening-level water management models to evaluate large numbers of strategies against a wide range of plausible future scenarios. The presentation will describe a recent application of the methodology to evaluate climate adaptation strategies for the Inland Empire Utilities Agency in Southern California. This project found that RDM can provide a useful way for addressing climate change uncertainty and identify robust adaptation strategies.

Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

NASA Technical Reports Server (NTRS)

Newman, Perry A.; Hou, Gene J. W.; Taylor, Arthur C., III

1996-01-01

Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

Exploiting on-node heterogeneity for in-situ analytics of climate simulations via a functional partitioning framework

NASA Astrophysics Data System (ADS)

Sapra, Karan; Gupta, Saurabh; Atchley, Scott; Anantharaj, Valentine; Miller, Ross; Vazhkudai, Sudharshan

2016-04-01

Efficient resource utilization is critical for improved end-to-end computing and workflow of scientific applications. Heterogeneous node architectures, such as the GPU-enabled Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), present us with further challenges. In many HPC applications on Titan, the accelerators are the primary compute engines while the CPUs orchestrate the offloading of work onto the accelerators, and moving the output back to the main memory. On the other hand, applications that do not exploit GPUs, the CPU usage is dominant while the GPUs idle. We utilized Heterogenous Functional Partitioning (HFP) runtime framework that can optimize usage of resources on a compute node to expedite an application's end-to-end workflow. This approach is different from existing techniques for in-situ analyses in that it provides a framework for on-the-fly analysis on-node by dynamically exploiting under-utilized resources therein. We have implemented in the Community Earth System Model (CESM) a new concurrent diagnostic processing capability enabled by the HFP framework. Various single variate statistics, such as means and distributions, are computed in-situ by launching HFP tasks on the GPU via the node local HFP daemon. Since our current configuration of CESM does not use GPU resources heavily, we can move these tasks to GPU using the HFP framework. Each rank running the atmospheric model in CESM pushes the variables of of interest via HFP function calls to the HFP daemon. This node local daemon is responsible for receiving the data from main program and launching the designated analytics tasks on the GPU. We have implemented these analytics tasks in C and use OpenACC directives to enable GPU acceleration. This methodology is also advantageous while executing GPU-enabled configurations of CESM when the CPUs will be idle during portions of the runtime. In our implementation results, we demonstrate that it is more efficient to use HFP framework to offload the tasks to GPUs instead of doing it in the main application. We observe increased resource utilization and overall productivity in this approach by using HFP framework for end-to-end workflow.

Predictors of health-related quality of life and costs in adults with epilepsy: a systematic review.

PubMed

Taylor, Rod S; Sander, Josemir W; Taylor, Rebecca J; Baker, Gus A

2011-12-01

Given the high burden of epilepsy on both health-related quality of life (HRQoL) and costs, identification of factors that are predictive of either reduced HRQoL or increased expenditure is central to the better future targeting and optimization of existing and emerging interventions and management strategies for epilepsy. Searches of Medline, Embase, and Cochrane Library (up to July 2010) to identify studies examining the association between demographic, psychosocial, and condition-related factors and HRQoL, resource utilization or costs in adults with epilepsy. For each study, predictor factor associations were summarized on the basis of statistical significance and direction; the results were then combined across studies. Ninety-three HRQoL and 16 resource utilization/cost studies were included. Increases in seizure frequency, seizure severity, level of depression, and level of anxiety and presence of comorbidity were strongly associated with reduced HRQoL. The majority of studies were cross-sectional in design and had an overall methodologic quality that was judged to be "moderate" for HRQoL studies and "poor" for health care resource or costs studies. In the 53 multivariate studies, age, gender, marital status, type of seizure, age at diagnosis, and duration of epilepsy did not appear to be associated with HRQoL, whereas the predictive influence of educational and employment status, number of antiepileptic drugs (AEDs) and AED side effects was unclear. The association between predictive factors and HRQoL appeared to be consistent across individuals whether refractory or seizures controlled or managed by AEDs. There were insufficient multivariate studies (five) to reliably comment on the predictors of resource utilization or cost in epilepsy. In addition to seizure control, effective epilepsy management requires the early detection of those most at risk of psychological dysfunction and comorbidity, and the targeting of appropriate interventions. There is need for more rigorous studies with appropriate multivariate statistical methods that prospectively investigate the predictors of HRQoL, resource utilization, and costs in epilepsy. Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.

SURE (Science User Resource Expert): A science planning and scheduling assistant for a resource based environment

NASA Technical Reports Server (NTRS)

Thalman, Nancy E.; Sparn, Thomas P.

1990-01-01

SURE (Science User Resource Expert) is one of three components that compose the SURPASS (Science User Resource Planning and Scheduling System). This system is a planning and scheduling tool which supports distributed planning and scheduling, based on resource allocation and optimization. Currently SURE is being used within the SURPASS by the UARS (Upper Atmospheric Research Satellite) SOLSTICE instrument to build a daily science plan and activity schedule and in a prototyping effort with NASA GSFC to demonstrate distributed planning and scheduling for the SOLSTICE II instrument on the EOS platform. For the SOLSTICE application the SURE utilizes a rule-based system. Development of a rule-based program using Ada CLIPS as opposed to using conventional programming, allows for capture of the science planning and scheduling heuristics in rules and provides flexibility in inserting or removing rules as the scientific objectives and mission constraints change. The SURE system's role as a component in the SURPASS, the purpose of the SURE planning and scheduling tool, the SURE knowledge base, and the software architecture of the SURE component are described.

Global Health Initiatives of the International Oncology Community.

PubMed

Al-Sukhun, Sana; de Lima Lopes, Gilberto; Gospodarowicz, Mary; Ginsburg, Ophira; Yu, Peter Paul

2017-01-01

Cancer has become one of the leading causes of morbidity and mortality in low- and middle-income countries (LMICs), where 60% of the world's total new cases are diagnosed. The challenge for effective control of cancer is multifaceted. It mandates integration of effective cancer prevention, encouraging early detection, and utilization of resource-adapted therapeutic and supportive interventions. In the resource-constrained setting, it becomes challenging to deliver each service optimally, and efficient allocation of resources is the best way to improve the outcome. This concept was translated into action through development of resource-stratified guidelines, pioneered by the Breast Health Global Initiative (BHGI), and later adopted by most oncology societies in an attempt to help physicians deliver the best possible care in a limited-resource setting. Improving outcome entails collaboration between key stakeholders, including the pharmaceutical industry, local and national health authorities, the World Health Organization (WHO), and other nonprofit, patient-oriented organizations. Therefore, we started to observe global health initiatives-led by ASCO, the Union for International Cancer Control (UICC), and the WHO-to address these challenges at the international level. This article discusses some of these initiatives.

Measuring Resource Utilization: A Systematic Review of Validated Self-Reported Questionnaires.

PubMed

Leggett, Laura E; Khadaroo, Rachel G; Holroyd-Leduc, Jayna; Lorenzetti, Diane L; Hanson, Heather; Wagg, Adrian; Padwal, Raj; Clement, Fiona

2016-03-01

A variety of methods may be used to obtain costing data. Although administrative data are most commonly used, the data available in these datasets are often limited. An alternative method of obtaining costing is through self-reported questionnaires. Currently, there are no systematic reviews that summarize self-reported resource utilization instruments from the published literature.The aim of the study was to identify validated self-report healthcare resource use instruments and to map their attributes.A systematic review was conducted. The search identified articles using terms like "healthcare utilization" and "questionnaire." All abstracts and full texts were considered in duplicate. For inclusion, studies had to assess the validity of a self-reported resource use questionnaire, to report original data, include adult populations, and the questionnaire had to be publically available. Data such as type of resource utilization assessed by each questionnaire, and validation findings were extracted from each study.In all, 2343 unique citations were retrieved; 2297 were excluded during abstract review. Forty-six studies were reviewed in full text, and 15 studies were included in this systematic review. Six assessed resource utilization of patients with chronic conditions; 5 assessed mental health service utilization; 3 assessed resource utilization by a general population; and 1 assessed utilization in older populations. The most frequently measured resources included visits to general practitioners and inpatient stays; nonmedical resources were least frequently measured. Self-reported questionnaires on resource utilization had good agreement with administrative data, although, visits to general practitioners, outpatient days, and nurse visits had poorer agreement.Self-reported questionnaires are a valid method of collecting data on healthcare resource utilization.

Provider cost analysis supports results-based contracting out of maternal and newborn health services: an evidence-based policy perspective.

PubMed

Hatcher, Peter; Shaikh, Shiraz; Fazli, Hassan; Zaidi, Shehla; Riaz, Atif

2014-11-13

There is dearth of evidence on provider cost of contracted out services particularly for Maternal and Newborn Health (MNH). The evidence base is weak for policy makers to estimate resources required for scaling up contracting. This paper ascertains provider unit costs and expenditure distribution at contracted out government primary health centers to inform the development of optimal resource envelopes for contracting out MNH services. This is a case study of provider costs of MNH services at two government Rural Health Centers (RHCs) contracted out to a non-governmental organization in Pakistan. It reports on four selected Basic Emergency Obstetrical and Newborn Care (BEmONC) services provided in one RHC and six Comprehensive Emergency Obstetrical and Newborn Care (CEmONC) services in the other. Data were collected using staff interviews and record review to compile resource inputs and service volumes, and analyzed using the CORE Plus tool. Unit costs are based on actual costs of MNH services and are calculated for actual volumes in 2011 and for volumes projected to meet need with optimal resource inputs. The unit costs per service for actual 2011 volumes at the BEmONC RHC were antenatal care (ANC) visit USD$ 18.78, normal delivery US$ 84.61, newborn care US$ 16.86 and a postnatal care (PNC) visit US$ 13.86; and at the CEmONC RHC were ANC visit US$ 45.50, Normal Delivery US$ 148.43, assisted delivery US$ 167.43, C-section US$ 183.34, Newborn Care US$ 41.07, and PNC visit US$ 27.34. The unit costs for the projected volumes needed were lower due to optimal utilization of resources. The percentage distribution of expenditures at both RHCs was largest for salaries of technical staff, followed by salaries of administrative staff, and then operating costs, medicines, medical and diagnostic supplies. The unit costs of MNH services at the two contracted out government rural facilities remain higher than is optimal, primarily due to underutilization. Provider cost analysis using standard treatment guideline (STG) based service costing frameworks should be applied across a number of health facilities to calculate the cost of services and guide development of evidence based resource envelopes and performance based contracting.

Structural degradation of Thar lignite using MW1 fungal isolate: optimization studies

USGS Publications Warehouse

Haider, Rizwan; Ghauri, Muhammad A.; Jones, Elizabeth J.; Orem, William H.; SanFilipo, John R.

2015-01-01

Biological degradation of low-rank coals, particularly degradation mediated by fungi, can play an important role in helping us to utilize neglected lignite resources for both fuel and non-fuel applications. Fungal degradation of low-rank coals has already been investigated for the extraction of soil-conditioning agents and the substrates, which could be subjected to subsequent processing for the generation of alternative fuel options, like methane. However, to achieve an efficient degradation process, the fungal isolates must originate from an appropriate coal environment and the degradation process must be optimized. With this in mind, a representative sample from the Thar coalfield (the largest lignite resource of Pakistan) was treated with a fungal strain, MW1, which was previously isolated from a drilled core coal sample. The treatment caused the liberation of organic fractions from the structural matrix of coal. Fungal degradation was optimized, and it showed significant release of organics, with 0.1% glucose concentration and 1% coal loading ratio after an incubation time of 7 days. Analytical investigations revealed the release of complex organic moieties, pertaining to polyaromatic hydrocarbons, and it also helped in predicting structural units present within structure of coal. Such isolates, with enhanced degradation capabilities, can definitely help in exploiting the chemical-feedstock-status of coal.

A DSS for sustainable development and environmental protection of agricultural regions.

PubMed

Manos, Basil D; Papathanasiou, Jason; Bournaris, Thomas; Voudouris, Kostas

2010-05-01

This paper presents a decision support system (DSS) for sustainable development and environmental protection of agricultural regions developed in the framework of the Interreg-Archimed project entitled WaterMap (development and utilization of vulnerability maps for the monitoring and management of groundwater resources in the ARCHIMED areas). Its aim is to optimize the production plan of an agricultural region taking in account the available resources, the environmental parameters, and the vulnerability map of the region. The DSS is based on an optimization multicriteria model. The spatial integration of vulnerability maps in the DSS enables regional authorities to design policies for optimal agricultural development and groundwater protection from the agricultural land uses. The DSS can further be used to simulate different scenarios and policies by the local stakeholders due to changes on different social, economic, and environmental parameters. In this way, they can achieve alternative production plans and agricultural land uses as well as to estimate economic, social, and environmental impacts of different policies. The DSS is computerized and supported by a set of relational databases. The corresponding software has been developed in a Microsoft Windows XP platform, using Microsoft Visual Basic, Microsoft Access, and the LINDO library. For demonstration reasons, the paper includes an application of the DSS in a region of Northern Greece.

Payments for Ecosystem Services for watershed water resource allocations

NASA Astrophysics Data System (ADS)

Fu, Yicheng; Zhang, Jian; Zhang, Chunling; Zang, Wenbin; Guo, Wenxian; Qian, Zhan; Liu, Laisheng; Zhao, Jinyong; Feng, Jian

2018-01-01

Watershed water resource allocation focuses on concrete aspects of the sustainable management of Ecosystem Services (ES) that are related to water and examines the possibility of implementing Payment for Ecosystem Services (PES) for water ES. PES can be executed to satisfy both economic and environmental objectives and demands. Considering the importance of calculating PES schemes at the social equity and cooperative game (CG) levels, to quantitatively solve multi-objective problems, a water resources allocation model and multi-objective optimization are provided. The model consists of three modules that address the following processes: ① social equity mechanisms used to study water consumer associations, ② an optimal decision-making process based on variable intervals and CG theory, and ③ the use of Shapley values of CGs for profit maximization. The effectiveness of the proposed methodology for realizing sustainable development was examined. First, an optimization model with water allocation objective was developed based on sustainable water resources allocation framework that maximizes the net benefit of water use. Then, to meet water quality requirements, PES cost was estimated using trade-off curves among different pollution emission concentration permissions. Finally, to achieve equity and supply sufficient incentives for water resources protection, CG theory approaches were utilized to reallocate PES benefits. The potential of the developed model was examined by its application to a case study in the Yongding River watershed of China. Approximately 128 Mm3 of water flowed from the upper reach (Shanxi and Hebei Provinces) sections of the Yongding River to the lower reach (Beijing) in 2013. According to the calculated results, Beijing should pay USD6.31 M (¥39.03 M) for water-related ES to Shanxi and Hebei Provinces. The results reveal that the proposed methodology is an available tool that can be used for sustainable development with resolving PES amounts among different regions under social and environmental constraints by considering the characteristics of social equity and CGs.

Energy Technology Allocation for Distributed Energy Resources: A Technology-Policy Framework

NASA Astrophysics Data System (ADS)

Mallikarjun, Sreekanth

Distributed energy resources (DER) are emerging rapidly. New engineering technologies, materials, and designs improve the performance and extend the range of locations for DER. In contrast, constructing new or modernizing existing high voltage transmission lines for centralized generation are expensive and challenging. In addition, customer demand for reliability has increased and concerns about climate change have created a pull for swift renewable energy penetration. In this context, DER policy makers, developers, and users are interested in determining which energy technologies to use to accommodate different end-use energy demands. We present a two-stage multi-objective strategic technology-policy framework for determining the optimal energy technology allocation for DER. The framework simultaneously considers economic, technical, and environmental objectives. The first stage utilizes a Data Envelopment Analysis model for each end-use to evaluate the performance of each energy technology based on the three objectives. The second stage incorporates factor efficiencies determined in the first stage, capacity limitations, dispatchability, and renewable penetration for each technology, and demand for each end-use into a bottleneck multi-criteria decision model which provides the Pareto-optimal energy resource allocation. We conduct several case studies to understand the roles of various distributed energy technologies in different scenarios. We construct some policy implications based on the model results of set of case studies.

Planning for distributed workflows: constraint-based coscheduling of computational jobs and data placement in distributed environments

NASA Astrophysics Data System (ADS)

Makatun, Dzmitry; Lauret, Jérôme; Rudová, Hana; Šumbera, Michal

2015-05-01

When running data intensive applications on distributed computational resources long I/O overheads may be observed as access to remotely stored data is performed. Latencies and bandwidth can become the major limiting factor for the overall computation performance and can reduce the CPU/WallTime ratio to excessive IO wait. Reusing the knowledge of our previous research, we propose a constraint programming based planner that schedules computational jobs and data placements (transfers) in a distributed environment in order to optimize resource utilization and reduce the overall processing completion time. The optimization is achieved by ensuring that none of the resources (network links, data storages and CPUs) are oversaturated at any moment of time and either (a) that the data is pre-placed at the site where the job runs or (b) that the jobs are scheduled where the data is already present. Such an approach eliminates the idle CPU cycles occurring when the job is waiting for the I/O from a remote site and would have wide application in the community. Our planner was evaluated and simulated based on data extracted from log files of batch and data management systems of the STAR experiment. The results of evaluation and estimation of performance improvements are discussed in this paper.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

PubMed Central

Yi, Meng; Chen, Qingkui; Xiong, Neal N.

2016-01-01

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate. PMID:27827878

Spatial decision on allocating automated external defibrillators (AED) in communities by multi-criterion two-step floating catchment area (MC2SFCA).

PubMed

Lin, Bo-Cheng; Chen, Chao-Wen; Chen, Chien-Chou; Kuo, Chiao-Ling; Fan, I-Chun; Ho, Chi-Kung; Liu, I-Chuan; Chan, Ta-Chien

2016-05-25

The occurrence of out-of-hospital cardiac arrest (OHCA) is a critical life-threatening event which frequently warrants early defibrillation with an automated external defibrillator (AED). The optimization of allocating a limited number of AEDs in various types of communities is challenging. We aimed to propose a two-stage modeling framework including spatial accessibility evaluation and priority ranking to identify the highest gaps between demand and supply for allocating AEDs. In this study, a total of 6135 OHCA patients were defined as demand, and the existing 476 publicly available AEDs locations and 51 emergency medical service (EMS) stations were defined as supply. To identify the demand for AEDs, Bayesian spatial analysis with the integrated nested Laplace approximation (INLA) method is applied to estimate the composite spatial risks from multiple factors. The population density, proportion of elderly people, and land use classifications are identified as risk factors. Then, the multi-criterion two-step floating catchment area (MC2SFCA) method is used to measure spatial accessibility of AEDs between the spatial risks and the supply of AEDs. Priority ranking is utilized for prioritizing deployment of AEDs among communities because of limited resources. Among 6135 OHCA patients, 56.85 % were older than 65 years old, and 79.04 % were in a residential area. The spatial distribution of OHCA incidents was found to be concentrated in the metropolitan area of Kaohsiung City, Taiwan. According to the posterior mean estimated by INLA, the spatial effects including population density and proportion of elderly people, and land use classifications are positively associated with the OHCA incidence. Utilizing the MC2SFCA for spatial accessibility, we found that supply of AEDs is less than demand in most areas, especially in rural areas. Under limited resources, we identify priority places for deploying AEDs based on transportation time to the nearest hospital and population size of the communities. The proposed method will be beneficial for optimizing resource allocation while considering multiple local risks. The optimized deployment of AEDs can broaden EMS coverage and minimize the problems of the disparity in urban areas and the deficiency in rural areas.

Strategies towards an optimized use of the shallow geothermal potential

NASA Astrophysics Data System (ADS)

Schelenz, S.; Firmbach, L.; Kalbacher, T.; Goerke, U.; Kolditz, O.; Dietrich, P.; Vienken, T.

2013-12-01

Thermal use of the shallow subsurface for heat generation, cooling and thermal energy storage is increasingly gaining importance in reconsideration of future energy supplies, e.g. in the course of German energy transition, with application shifting from isolated to intensive use. The planning and dimensioning of (geo-)thermal applications is strongly influenced by the availability of exploration data. Hence, reliable site-specific dimensioning of systems for the thermal use of the shallow subsurface will contribute to an increase in resource efficiency, cost reduction during installation and operation, as well as reduction of environmental impacts and prevention of resource over-exploitation. Despite large cumulative investments that are being made for the utilization of the shallow thermal potential, thermal energy is in many cases exploited without prior on-site exploration and investigation of the local geothermal potential, due to the lack of adequate and cost-efficient exploration techniques. We will present new strategies for an optimized utilization of urban thermal potential, showcased at a currently developed residential neighborhood with high demand for shallow geothermal applications, based on a) enhanced site characterization and b) simulation of different site specific application scenarios. For enhanced site characterization, surface geophysics and vertical high resolution direct push-profiling were combined for reliable determination of aquifer structure and aquifer parameterization. Based on the site characterization, different site specific geothermal application scenarios, including different system types and system configurations, were simulated using OpenGeoSys to guarantee an environmental and economic sustainable thermal use of the shallow subsurface.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Stephen R., E-mail: stephen.thompson@sesiahs.health.nsw.gov.au; Department of Radiation Oncology, Prince of Wales Hospital, Sydney; University of New South Wales, Sydney

Purpose: We aimed to estimate the optimal proportion of all gynecological cancers that should be treated with brachytherapy (BT)-the optimal brachytherapy utilization rate (BTU)-to compare this with actual gynecological BTU and to assess the effects of nonmedical factors on access to BT. Methods and Materials: The previously constructed inter/multinational guideline-based peer-reviewed models of optimal BTU for cancers of the uterine cervix, uterine corpus, and vagina were combined to estimate optimal BTU for all gynecological cancers. The robustness of the model was tested by univariate and multivariate sensitivity analyses. The resulting model was applied to New South Wales (NSW), the Unitedmore » States, and Western Europe. Actual BTU was determined for NSW by a retrospective patterns-of-care study of BT; for Western Europe from published reports; and for the United States from Surveillance, Epidemiology, and End Results data. Differences between optimal and actual BTU were assessed. The effect of nonmedical factors on access to BT in NSW were analyzed. Results: Gynecological BTU was as follows: NSW 28% optimal (95% confidence interval [CI] 26%-33%) compared with 14% actual; United States 30% optimal (95% CI 26%-34%) and 10% actual; and Western Europe 27% optimal (95% CI 25%-32%) and 16% actual. On multivariate analysis, NSW patients were more likely to undergo gynecological BT if residing in Area Health Service equipped with BT (odds ratio 1.76, P=.008) and if residing in socioeconomically disadvantaged postcodes (odds ratio 1.12, P=.05), but remoteness of residence was not significant. Conclusions: Gynecological BT is underutilized in NSW, Western Europe, and the United States given evidence-based guidelines. Access to BT equipment in NSW was significantly associated with higher utilization rates. Causes of underutilization elsewhere were undetermined. Our model of optimal BTU can be used as a quality assurance tool, providing an evidence-based benchmark against which actual patterns of practice can be measured. It can also be used to assist in determining the adequacy of BT resource allocation.« less

Entropy production and optimization of geothermal power plants

NASA Astrophysics Data System (ADS)

Michaelides, Efstathios E.

2012-09-01

Geothermal power plants are currently producing reliable and low-cost, base load electricity. Three basic types of geothermal power plants are currently in operation: single-flashing, dual-flashing, and binary power plants. Typically, the single-flashing and dual-flashing geothermal power plants utilize geothermal water (brine) at temperatures in the range of 550-430 K. Binary units utilize geothermal resources at lower temperatures, typically 450-380 K. The entropy production in the various components of the three types of geothermal power plants determines the efficiency of the plants. It is axiomatic that a lower entropy production would improve significantly the energy utilization factor of the corresponding power plant. For this reason, the entropy production in the major components of the three types of geothermal power plants has been calculated. It was observed that binary power plants generate the lowest amount of entropy and, thus, convert the highest rate of geothermal energy into mechanical energy. The single-flashing units generate the highest amount of entropy, primarily because they re-inject fluid at relatively high temperature. The calculations for entropy production provide information on the equipment where the highest irreversibilities occur, and may be used to optimize the design of geothermal processes in future geothermal power plants and thermal cycles used for the harnessing of geothermal energy.

Optimization of power utilization in multimobile robot foraging behavior inspired by honeybees system.

PubMed

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work.

Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

PubMed Central

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work. PMID:24949491

An Ensemble-Based Forecasting Framework to Optimize Reservoir Releases

NASA Astrophysics Data System (ADS)

Ramaswamy, V.; Saleh, F.

2017-12-01

Increasing frequency of extreme precipitation events are stressing the need to manage water resources on shorter timescales. Short-term management of water resources becomes proactive when inflow forecasts are available and this information can be effectively used in the control strategy. This work investigates the utility of short term hydrological ensemble forecasts for operational decision making during extreme weather events. An advanced automated hydrologic prediction framework integrating a regional scale hydrologic model, GIS datasets and the meteorological ensemble predictions from the European Center for Medium Range Weather Forecasting (ECMWF) was coupled to an implicit multi-objective dynamic programming model to optimize releases from a water supply reservoir. The proposed methodology was evaluated by retrospectively forecasting the inflows to the Oradell reservoir in the Hackensack River basin in New Jersey during the extreme hydrologic event, Hurricane Irene. Additionally, the flexibility of the forecasting framework was investigated by forecasting the inflows from a moderate rainfall event to provide important perspectives on using the framework to assist reservoir operations during moderate events. The proposed forecasting framework seeks to provide a flexible, assistive tool to alleviate the complexity of operational decision-making.

Spacelab user implementation assessment study. Volume 1: Concept development and evaluation

NASA Technical Reports Server (NTRS)

1975-01-01

The total matrix of alternate Spacelab processing concepts and the rejection rationale utilized to reduce the matrix of 243 alternates to the final candidate processing concepts are developed. The work breakdown structure used for the systematic estimation and compilation of integration and checkout resources is presented along with descriptors of each element. Program models are provided of the space transportation system, the Spacelab, the orbiter, and the ATL that were used as the basis for the study trades, analyses, and optimizations. Resource requirements for all processing concepts are summarized along with the optimizations of the processing concepts. Concept evaluations including flight-rate sensitivities of the GSE, facilities, Spacelab hardware elements, and personnel are delineated. An analysis is presented of the applicability of the candidate concepts to potential spacelab users. The impact of the use of the western test range as an orbiter/spacelab launch site on the candidate processing concepts is evaluated. An assessment of the geographical co-location of experiment, Spacelab, and orbiter-cargo integration is included. Ownership options of the support module/system igloo are discussed.

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

PubMed

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

Handling Uncertain Gross Margin and Water Demand in Agricultural Water Resources Management using Robust Optimization

NASA Astrophysics Data System (ADS)

Chaerani, D.; Lesmana, E.; Tressiana, N.

2018-03-01

In this paper, an application of Robust Optimization in agricultural water resource management problem under gross margin and water demand uncertainty is presented. Water resource management is a series of activities that includes planning, developing, distributing and managing the use of water resource optimally. Water resource management for agriculture can be one of the efforts to optimize the benefits of agricultural output. The objective function of agricultural water resource management problem is to maximizing total benefits by water allocation to agricultural areas covered by the irrigation network in planning horizon. Due to gross margin and water demand uncertainty, we assume that the uncertain data lies within ellipsoidal uncertainty set. We employ robust counterpart methodology to get the robust optimal solution.

Recovery and Utilization of Extraterrestrial Resources

NASA Technical Reports Server (NTRS)

2004-01-01

This special bibliography includes the extraction, processing, and utilization of lunar, planetary, and asteroid resources; mining and excavation equipment, oxygen and propellant production; and in situ resource utilization.

Selective Iterative Waterfilling for Digital Subscriber Lines

NASA Astrophysics Data System (ADS)

Xu, Yang; Le-Ngoc, Tho; Panigrahi, Saswat

2007-12-01

This paper presents a high-performance, low-complexity, quasi-distributed dynamic spectrum management (DSM) algorithm suitable for DSL systems. We analytically demonstrate that the rate degradation of the distributed iterative waterfilling (IW) algorithm in near-far scenarios is caused by the insufficient utilization of all available frequency and power resources due to its nature of noncooperative game theoretic formulation. Inspired by this observation, we propose the selective IW (SIW) algorithm that can considerably alleviate the performance degradation of IW by applying IW selectively to different groups of users over different frequency bands so that all the available resources can be fully utilized. For [InlineEquation not available: see fulltext.] users, the proposed SIW algorithm needs at most [InlineEquation not available: see fulltext.] times the complexity of the IW algorithm, and is much simpler than the centralized optimal spectrum balancing (OSB), while it can offer a rate performance much better than that of the IW and close to the maximum possible rate region computed by the OSB in realistic near-far DSL scenarios. Furthermore, its predominantly distributed structure makes it suitable for DSL implementation.

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

USGS Publications Warehouse

Kavelaars, Alicia; Barnoy, Assaf M.; Gregory, Shawna; Garcia, Gonzalo; Talon, Cesar; Greer, Gregory; Williams, Jason; Dulski, Vicki

2014-01-01

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Spaceport Command and Control System Software Development

NASA Technical Reports Server (NTRS)

Mahlin, Jonathan Nicholas

2017-01-01

There is an immense challenge in organizing personnel across a large agency such as NASA, or even over a subset of that, like a center's Engineering directorate. Workforce inefficiencies and challenges are bound to grow over time without oversight and management. It is also not always possible to hire new employees to fill workforce gaps, therefore available resources must be utilized more efficiently. The goal of this internship was to develop software that improves organizational efficiency by aiding managers, making employee information viewable and editable in an intuitive manner. This semester I created an application for managers that aids in optimizing allocation of employee resources for a single division with the possibility of scaling upwards. My duties this semester consisted of developing frontend and backend software to complete this task. The application provides user-friendly information displays and documentation of the workforce to allow NASA to track diligently track the status and skills of its workforce. This tool should be able to prove that current employees are being effectively utilized and if new hires are necessary to fulfill skill gaps.

A IHE-Like Approach Method for Quantitative Analysis of PACS Usage.

PubMed

Calabrese, Raffaele; Beltrame, Marco; Accardo, Agostino

2016-12-01

Today, many hospitals have a running enterprise picture archiving and communication system (PACS) and their administrators should have the tools to measure the system activity and, in particular, how much it is used. The information would be valuable for decision-makers to address asset management and the development of policies for its correct utilization and eventually start training initiatives to get the best in resource utilization and operators' satisfaction. On the economic side, a quantitative method to measure the usage of the workstations would be desirable to better redistribute existing resources and plan the purchase of new ones. The paper exploits in an unconventional way the potential of the IHE Audit Trail and Node Authentication (ATNA) profile: it uses the data generated in order to safeguard the security of patient data and to retrieve information about the workload of each PACS workstation. The method uses the traces recorded, according to the profile, for each access to image data and to calculate how much each station is used. The results, constituted by measures of the frequency of PACS station usage suitably classified and presented according to a convenient format for decision-makers, are encouraging. In the time of the spending review, the careful management of available resources is the top priority for a healthcare organization. Thanks to our work, a common medium such as the ATNA profile appears a very useful resource for purposes other than those for which it was born. This avoids additional investments in management tools and allows optimization of resources at no cost.

Community preferences for health states associated with intimate partner violence.

PubMed

Wittenberg, Eve; Lichter, Erika L; Ganz, Michael L; McCloskey, Laura A

2006-08-01

One in 4 women is affected by intimate partner violence in her lifetime. This article reports on a cross-sectional survey to estimate community preferences for health states resulting from intimate partner violence. A secondary analysis was conducted of data from a convenience sample of 93 abused and 138 nonabused women (231 total) recruited for in-person interviews from hospital outpatient department waiting rooms in metropolitan Boston, Massachusetts. SF-12 data were converted to utilities to describe community-perspective preferences for health states associated with intimate partner violence. Linear regression analysis was used to explore the association between violence and utility while controlling for other health and demographic factors. Median utility for intimate partner violence was between 0.58 and 0.63 on a scale of 0 (equivalent to death) to 1.0 (equivalent to optimal health), with a range from 0.64 to 0.66 for less severe violence to 0.53 to 0.62 for more severe violence. The data do not reveal whether violence itself is responsible for lower utility or whether a constellation of factors contributes to disutility experienced by women victims of abuse. The utility of health states experienced by women exposed to intimate partner violence is substantially diminished compared with optimal health and even other health conditions. These values quantify the substantial negative health impact of the experience of intimate partner violence in terms that allow comparison across diseases. They can be used in cost-effectiveness analyses to identify the benefits and potential returns from resources allocated to violence prevention and intervention efforts.

Demand-Side Management and Integrated Resource Planning: Findings from a Survey of 24 Electric Utilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schweitzer, M.

1991-01-01

Integrated resource planning differs from traditional utility planning practices primarily in its increased attention to demand-side management (DSM) programs and its integration of supply- and demand-side resources into a combined resource portfolio. This report details the findings from an Oak Ridge National Laboratory (ORNL) survey of 24 electric utilities that have well-developed integrated planning processes. These utilities account for roughly one-third of total capacity, electricity generation, and DSM-program expenditures nationwide. The ORNL survey was designed to obtain descriptive data on a national sample of utilities and to test a number of hypothesized relationships between selected utility characteristics and the mixmore » of resources selected for the integrated plan, with an emphasis on the use of DSM resources and the processes by which they are chosen. The survey solicited information on each utility's current and projected resource mix, operating environment, procedures used to screen potential DSM resources, techniques used to obtain public input and to integrate supply- and demand-side options into a unified plan, and procedures used in the final selection of resources for the plan.« less

Radiotherapy utilization in developing countries: An IAEA study.

PubMed

Rosenblatt, Eduardo; Fidarova, Elena; Zubizarreta, Eduardo H; Barton, Michael B; Jones, Glenn W; Mackillop, William J; Cordero, Lisbeth; Yarney, Joel; Lim, Gerard; Gan, John V; Cernea, Valentin; Stojanovic-Rundic, Suzana; Strojan, Primoz; Kochbati, Lotfi; Quarneti, Aldo

2018-05-30

The planning of national radiotherapy (RT) services requires a thorough knowledge of the country's cancer epidemiology profile, the radiotherapy utilization (RTU) rates and a future projection of these data. Previous studies have established RTU rates in high-income countries. Optimal RTU (oRTU) rates were determined for nine middle-income countries, following the epidemiological evidence-based method. The actual RTU (aRTU) rates were calculated dividing the total number of new notifiable cancer patients treated with radiotherapy in 2012 by the total number of cancer patients diagnosed in the same year in each country. An analysis of the characteristics of patients and treatments in a series of 300 consecutive radiotherapy patients shed light on the particular patient and treatments profile in the participating countries. The median oRTU rate for the group of nine countries was 52% (47-56%). The median aRTU rate for the nine countries was 28% (9-46%). These results show that the real proportion of cancer patients receiving RT is lower than the optimal RTU with a rate difference between 10-42.7%. The median percent-unmet need was 47% (18-82.3%). The optimal RTU rate in middle-income countries did not differ significantly from that previously found in high-income countries. The actual RTU rates were consistently lower than the optimal, in particular in countries with limited resources and a large population. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Aether: leveraging linear programming for optimal cloud computing in genomics.

PubMed

Luber, Jacob M; Tierney, Braden T; Cofer, Evan M; Patel, Chirag J; Kostic, Aleksandar D

2018-05-01

Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.

Promoting the energy structure optimization around Chinese Beijing-Tianjin area by developing biomass energy

NASA Astrophysics Data System (ADS)

Zhao, Li; Sun, Du; Wang, Shi-Yu; Zhao, Feng-Qing

2017-06-01

In recent years, remarkable achievements in the utilization of biomass energy have been made in China. However, there are still some problems, such as irrational industry layout, immature existing market survival mechanism and lack of core competitiveness. On the basis of investigation and research, some recommendations and strategies are proposed for the development of biomass energy around Chinese Beijing-Tianjin area: scientific planning and precise laying out of biomass industry; rationalizing the relationship between government and enterprises and promoting the establishment of a market-oriented survival mechanism; combining ‘supply side’ with ‘demand side’ to optimize product structure; extending industrial chain to promote industry upgrading and sustainable development; and comprehensive co-ordinating various types of biomass resources and extending product chain to achieve better economic benefits.

Shaping an Optimal Soil by Root-Soil Interaction.

PubMed

Jin, Kemo; White, Philip J; Whalley, William R; Shen, Jianbo; Shi, Lei

2017-10-01

Crop production depends on the availability of water and mineral nutrients, and increased yields might be facilitated by a greater focus on roots-soil interactions. Soil properties affecting plant growth include drought, compaction, nutrient deficiency, mineral toxicity, salinity, and submergence. Plant roots respond to the soil environment both spatially and temporally by avoiding stressful soil environments and proliferating in more favorable environments. We observe that crops can be bred for specific root architectural and biochemical traits that facilitate soil exploration and resource acquisition, enabling greater crop yields. These root traits affect soil physical and chemical properties and might be utilized to improve the soil for subsequent crops. We argue that optimizing root-soil interactions is a prerequisite for future food security. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, C.

Almost every computer architect dreams of achieving high system performance with low implementation costs. A multigauge machine can reconfigure its data-path width, provide parallelism, achieve better resource utilization, and sometimes can trade computational precision for increased speed. A simple experimental method is used here to capture the main characteristics of multigauging. The measurements indicate evidence of near-optimal speedups. Adapting these ideas in designing parallel processors incurs low costs and provides flexibility. Several operational aspects of designing a multigauge machine are discussed as well. Thus, this research reports the technical, economical, and operational feasibility studies of multigauging.

Sustainable dual-use labs: neurovascular interventional capabilities within the cath lab.

PubMed

Lang, Stacey

2012-01-01

The inclusion of neurovascular interventional capabilities within the cath lab setting can be key to optimal utilization of resources, increased staff efficiency, and streamlined operations. When considering an expansion, look beyond the patient population traditionally associated with cardiac cath labs and consider the integration of programs outside cardiac alone--to create a true dual-use lab space. With proper planning, quality dual purpose equipment, appropriately trained staff, capable physicians, and strong leadership, an organization willing to embrace the challenge can build a truly extraordinary service.

Smart City Energy Interconnection Technology Framework Preliminary Research

NASA Astrophysics Data System (ADS)

Zheng, Guotai; Zhao, Baoguo; Zhao, Xin; Li, Hao; Huo, Xianxu; Li, Wen; Xia, Yu

2018-01-01

to improve urban energy efficiency, improve the absorptive ratio of new energy resources and renewable energy sources, and reduce environmental pollution and other energy supply and consumption technology framework matched with future energy restriction conditions and applied technology level are required to be studied. Relative to traditional energy supply system, advanced information technology-based “Energy Internet” technical framework may give play to energy integrated application and load side interactive technology advantages, as a whole optimize energy supply and consumption and improve the overall utilization efficiency of energy.

Thorium fueled reactor

NASA Astrophysics Data System (ADS)

Sipaun, S.

2017-01-01

Current development in thorium fueled reactors shows that they can be designed to operate in the fast or thermal spectrum. The thorium/uranium fuel cycle converts fertile thorium-232 into fissile uranium-233, which fissions and releases energy. This paper analyses the characteristics of thorium fueled reactors and discusses the thermal reactor option. It is found that thorium fuel can be utilized in molten salt reactors through many configurations and designs. A balanced assessment on the feasibility of adopting one reactor technology versus another could lead to optimized benefits of having thorium resource.

[Research on the Application of Lean Management in Medical Consumables Material Logistics Management].

PubMed

Yang, Chai; Zhang, Wei; Gu, Wei; Shen, Aizong

2016-11-01

Solve the problems of high cost, low utilization rate of resources, low medical care quality problem in medical consumables material logistics management for scientific of medical consumables management. Analysis of the problems existing in the domestic medical consumables material logistics management in hospital, based on lean management method, SPD(Supply, Processing, Distribution) for specific applications, combined HBOS(Hospital Business Operation System), HIS (Hospital Information System) system for medical consumables material management. Achieve the lean management in medical consumables material purchase, warehouse construction, push, clinical use and retrospect. Lean management in medical consumables material can effectively control the cost in logistics management, optimize the alocation of resources, liberate unnecessary time of medical staff, improve the quality of medical care. It is a scientific management method.

Developing a framework for energy technology portfolio selection

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Ashrafi, Maryam

2012-11-01

Today, the increased consumption of energy in world, in addition to the risk of quick exhaustion of fossil resources, has forced industrial firms and organizations to utilize energy technology portfolio management tools viewed both as a process of diversification of energy sources and optimal use of available energy sources. Furthermore, the rapid development of technologies, their increasing complexity and variety, and market dynamics have made the task of technology portfolio selection difficult. Considering high level of competitiveness, organizations need to strategically allocate their limited resources to the best subset of possible candidates. This paper presents the results of developing a mathematical model for energy technology portfolio selection at a R&D center maximizing support of the organization's strategy and values. The model balances the cost and benefit of the entire portfolio.

Lessons from Crew Resource Management for Cardiac Surgeons.

PubMed

Marvil, Patrick; Tribble, Curt

2017-04-30

Crew resource management (CRM) describes a system developed in the late 1970s in response to a series of deadly commercial aviation crashes. This system has been universally adopted in commercial and military aviation and is now an integral part of aviation culture. CRM is an error mitigation strategy developed to reduce human error in situations in which teams operate in complex, high-stakes environments. Over time, the principles of this system have been applied and utilized in other environments, particularly in medical areas dealing with high-stakes outcomes requiring optimal teamwork and communication. While the data from formal studies on the effectiveness of formal CRM training in medical environments have reported mixed results, it seems clear that some of these principles should have value in the practice of cardiovascular surgery.

Downstream resource utilization following hybrid cardiac imaging with an integrated cadmium-zinc-telluride/64-slice CT device.

PubMed

Fiechter, Michael; Ghadri, Jelena R; Wolfrum, Mathias; Kuest, Silke M; Pazhenkottil, Aju P; Nkoulou, Rene N; Herzog, Bernhard A; Gebhard, Cathérine; Fuchs, Tobias A; Gaemperli, Oliver; Kaufmann, Philipp A

2012-03-01

Low yield of invasive coronary angiography and unnecessary coronary interventions have been identified as key cost drivers in cardiology for evaluation of coronary artery disease (CAD). This has fuelled the search for noninvasive techniques providing comprehensive functional and anatomical information on coronary lesions. We have evaluated the impact of implementation of a novel hybrid cadmium-zinc-telluride (CZT)/64-slice CT camera into the daily clinical routine on downstream resource utilization. Sixty-two patients with known or suspected CAD were referred for same-day single-session hybrid evaluation with CZT myocardial perfusion imaging (MPI) and coronary CT angiography (CCTA). Hybrid MPI/CCTA images from the integrated CZT/CT camera served for decision-making towards conservative versus invasive management. Based on the hybrid images patients were classified into those with and those without matched findings. Matched findings were defined as the combination of MPI defect with a stenosis by CCTA in the coronary artery subtending the respective territory. All patients with normal MPI and CCTA as well as those with isolated MPI or CCTA finding or combined but unmatched findings were categorized as "no match". All 23 patients with a matched finding underwent invasive coronary angiography and 21 (91%) were revascularized. Of the 39 patients with no match, 5 (13%, p < 0.001 vs matched) underwent catheterization and 3 (8%, p < 0.001 vs matched) were revascularized. Cardiac hybrid imaging in CAD evaluation has a profound impact on patient management and may contribute to optimal downstream resource utilization.

Sequential quantum cloning under real-life conditions

NASA Astrophysics Data System (ADS)

Saberi, Hamed; Mardoukhi, Yousof

2012-05-01

We consider a sequential implementation of the optimal quantum cloning machine of Gisin and Massar and propose optimization protocols for experimental realization of such a quantum cloner subject to the real-life restrictions. We demonstrate how exploiting the matrix-product state (MPS) formalism and the ensuing variational optimization techniques reveals the intriguing algebraic structure of the Gisin-Massar output of the cloning procedure and brings about significant improvements to the optimality of the sequential cloning prescription of Delgado [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.98.150502 98, 150502 (2007)]. Our numerical results show that the orthodox paradigm of optimal quantum cloning can in practice be realized in a much more economical manner by utilizing a considerably lesser amount of informational and numerical resources than hitherto estimated. Instead of the previously predicted linear scaling of the required ancilla dimension D with the number of qubits n, our recipe allows a realization of such a sequential cloning setup with an experimentally manageable ancilla of dimension at most D=3 up to n=15 qubits. We also address satisfactorily the possibility of providing an optimal range of sequential ancilla-qubit interactions for optimal cloning of arbitrary states under realistic experimental circumstances when only a restricted class of such bipartite interactions can be engineered in practice.

Performance evaluation of multi-stratum resources integrated resilience for software defined inter-data center interconnect.

PubMed

Yang, Hui; Zhang, Jie; Zhao, Yongli; Ji, Yuefeng; Wu, Jialin; Lin, Yi; Han, Jianrui; Lee, Young

2015-05-18

Inter-data center interconnect with IP over elastic optical network (EON) is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented multi-stratum resources integration among IP networks, optical networks and application stratums resources that allows to accommodate data center services. In view of this, this study extends to consider the service resilience in case of edge optical node failure. We propose a novel multi-stratum resources integrated resilience (MSRIR) architecture for the services in software defined inter-data center interconnect based on IP over EON. A global resources integrated resilience (GRIR) algorithm is introduced based on the proposed architecture. The MSRIR can enable cross stratum optimization and provide resilience using the multiple stratums resources, and enhance the data center service resilience responsiveness to the dynamic end-to-end service demands. The overall feasibility and efficiency of the proposed architecture is experimentally verified on the control plane of our OpenFlow-based enhanced SDN (eSDN) testbed. The performance of GRIR algorithm under heavy traffic load scenario is also quantitatively evaluated based on MSRIR architecture in terms of path blocking probability, resilience latency and resource utilization, compared with other resilience algorithms.

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Pipe degradation investigations for optimization of flow-accelerated corrosion inspection location selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandra, S.; Habicht, P.; Chexal, B.

1995-12-01

A large amount of piping in a typical nuclear power plant is susceptible to Flow-Accelerated Corrosion (FAC) wall thinning to varying degrees. A typical PAC monitoring program includes the wall thickness measurement of a select number of components in order to judge the structural integrity of entire systems. In order to appropriately allocate resources and maintain an adequate FAC program, it is necessary to optimize the selection of components for inspection by focusing on those components which provide the best indication of system susceptibility to FAC. A better understanding of system FAC predictability and the types of FAC damage encounteredmore » can provide some of the insight needed to better focus and optimize the inspection plan for an upcoming refueling outage. Laboratory examination of FAC damaged components removed from service at Northeast Utilities` (NU) nuclear power plants provides a better understanding of the damage mechanisms involved and contributing causes. Selected results of this ongoing study are presented with specific conclusions which will help NU to better focus inspections and thus optimize the ongoing FAC inspection program.« less

Optimal Control Design Advantages Utilizing Two-Degree-of-Freedom Controllers

DTIC Science & Technology

1993-12-01

AFrTIGAE/ENYIV3D-27 AD--A273 839 D"TIC OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS THESIS Michael J. Stephens...AFIT/GAE/ENY/93D-27 OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS THESIS Presented to the Faculty of the Graduate...measurement noises compared to the I- DOF model. xvii OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS I. Introduction L1

Voltage scheduling for low power/energy

NASA Astrophysics Data System (ADS)

Manzak, Ali

2001-07-01

Power considerations have become an increasingly dominant factor in the design of both portable and desk-top systems. An effective way to reduce power consumption is to lower the supply voltage since voltage is quadratically related to power. This dissertation considers the problem of lowering the supply voltage at (i) the system level and at (ii) the behavioral level. At the system level, the voltage of the variable voltage processor is dynamically changed with the work load. Processors with limited sized buffers as well as those with very large buffers are considered. Given the task arrival times, deadline times, execution times, periods and switching activities, task scheduling algorithms that minimize energy or peak power are developed for the processors equipped with very large buffers. A relation between the operating voltages of the tasks for minimum energy/power is determined using the Lagrange multiplier method, and an iterative algorithm that utilizes this relation is developed. Experimental results show that the voltage assignment obtained by the proposed algorithm is very close (0.1% error) to that of the optimal energy assignment and the optimal peak power (1% error) assignment. Next, on-line and off-fine minimum energy task scheduling algorithms are developed for processors with limited sized buffers. These algorithms have polynomial time complexity and present optimal (off-line) and close-to-optimal (on-line) solutions. A procedure to calculate the minimum buffer size given information about the size of the task (maximum, minimum), execution time (best case, worst case) and deadlines is also presented. At the behavioral level, resources operating at multiple voltages are used to minimize power while maintaining the throughput. Such a scheme has the advantage of allowing modules on the critical paths to be assigned to the highest voltage levels (thus meeting the required timing constraints) while allowing modules on non-critical paths to be assigned to lower voltage levels (thus reducing the power consumption). A polynomial time resource and latency constrained scheduling algorithm is developed to distribute the available slack among the nodes such that power consumption is minimum. The algorithm is iterative and utilizes the slack based on the Lagrange multiplier method.

Utilization and Monetization of Healthcare Data in Developing Countries.

PubMed

Bram, Joshua T; Warwick-Clark, Boyd; Obeysekare, Eric; Mehta, Khanjan

2015-06-01

In developing countries with fledgling healthcare systems, the efficient deployment of scarce resources is paramount. Comprehensive community health data and machine learning techniques can optimize the allocation of resources to areas, epidemics, or populations most in need of medical aid or services. However, reliable data collection in low-resource settings is challenging due to a wide range of contextual, business-related, communication, and technological factors. Community health workers (CHWs) are trusted community members who deliver basic health education and services to their friends and neighbors. While an increasing number of programs leverage CHWs for last mile data collection, a fundamental challenge to such programs is the lack of tangible incentives for the CHWs. This article describes potential applications of health data in developing countries and reviews the challenges to reliable data collection. Four practical CHW-centric business models that provide incentive and accountability structures to facilitate data collection are presented. Creating and strengthening the data collection infrastructure is a prerequisite for big data scientists, machine learning experts, and public health administrators to ultimately elevate and transform healthcare systems in resource-poor settings.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Kenton, David L.; Khovayko, Oleg; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Sherry, Stephen T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Suzek, Tugba O.; Tatusov, Roman; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2006-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Retroviral Genotyping Tools, HIV-1, Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at: . PMID:16381840

Utilization and Monetization of Healthcare Data in Developing Countries

PubMed Central

Bram, Joshua T.; Warwick-Clark, Boyd; Obeysekare, Eric; Mehta, Khanjan

2015-01-01

Abstract In developing countries with fledgling healthcare systems, the efficient deployment of scarce resources is paramount. Comprehensive community health data and machine learning techniques can optimize the allocation of resources to areas, epidemics, or populations most in need of medical aid or services. However, reliable data collection in low-resource settings is challenging due to a wide range of contextual, business-related, communication, and technological factors. Community health workers (CHWs) are trusted community members who deliver basic health education and services to their friends and neighbors. While an increasing number of programs leverage CHWs for last mile data collection, a fundamental challenge to such programs is the lack of tangible incentives for the CHWs. This article describes potential applications of health data in developing countries and reviews the challenges to reliable data collection. Four practical CHW-centric business models that provide incentive and accountability structures to facilitate data collection are presented. Creating and strengthening the data collection infrastructure is a prerequisite for big data scientists, machine learning experts, and public health administrators to ultimately elevate and transform healthcare systems in resource-poor settings. PMID:26487984

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; Dicuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Meteorite as raw material for Direct Metal Printing: A proof of concept study

NASA Astrophysics Data System (ADS)

Lietaert, Karel; Thijs, Lore; Neirinck, Bram; Lapauw, Thomas; Morrison, Brian; Lewicki, Chris; Van Vaerenbergh, Jonas

2018-02-01

Asteroid mining as such is not a new concept, as it has been described in science fiction for more than a century and some of its aspects have been studied by academia for more than 30 years. Recently, there is a renewed interest in this subject due the more and more concrete plans for long-duration space missions and the need for resources to support industrial activity in space. The use of locally available resources would greatly improve the economics and sustainability of such missions. Due to its economy in material, use of additive manufacturing (AM) provides an interesting route to valorize these resources for the production of spare parts, tools and large-scale structures optimized for their local microgravity environment. Proof of concept has already been provided for AM of moon regolith. In this paper the concept of In-Situ Resource Utilization is extended towards the production of metallic objects using powdered iron meteorite as raw material. The meteorite-based powder was used to produce a structural part but further research is needed to obtain a high density part without microcracks.

Database resources of the National Center for Biotechnology Information

PubMed Central

Acland, Abigail; Agarwala, Richa; Barrett, Tanya; Beck, Jeff; Benson, Dennis A.; Bollin, Colleen; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Church, Deanna M.; Clark, Karen; DiCuccio, Michael; Dondoshansky, Ilya; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Gorelenkov, Viatcheslav; Hoeppner, Marilu; Johnson, Mark; Kelly, Christopher; Khotomlianski, Viatcheslav; Kimchi, Avi; Kimelman, Michael; Kitts, Paul; Krasnov, Sergey; Kuznetsov, Anatoliy; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Karsch-Mizrachi, Ilene; Murphy, Terence; Ostell, James; O'Sullivan, Christopher; Panchenko, Anna; Phan, Lon; Pruitt, Don Preussm Kim D.; Rubinstein, Wendy; Sayers, Eric W.; Schneider, Valerie; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Siyan, Karanjit; Slotta, Douglas; Soboleva, Alexandra; Soussov, Vladimir; Starchenko, Grigory; Tatusova, Tatiana A.; Trawick, Bart W.; Vakatov, Denis; Wang, Yanli; Ward, Minghong; John Wilbur, W.; Yaschenko, Eugene; Zbicz, Kerry

2014-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, PubReader, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Primer-BLAST, COBALT, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, ClinVar, MedGen, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page. PMID:24259429

Simulation-optimization of large agro-hydrosystems using a decomposition approach

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grundmann, Jens

2014-05-01

In this contribution a stochastic simulation-optimization framework for decision support for optimal planning and operation of water supply of large agro-hydrosystems is presented. It is based on a decomposition solution strategy which allows for (i) the usage of numerical process models together with efficient Monte Carlo simulations for a reliable estimation of higher quantiles of the minimum agricultural water demand for full and deficit irrigation strategies at small scale (farm level), and (ii) the utilization of the optimization results at small scale for solving water resources management problems at regional scale. As a secondary result of several simulation-optimization runs at the smaller scale stochastic crop-water production functions (SCWPF) for different crops are derived which can be used as a basic tool for assessing the impact of climate variability on risk for potential yield. In addition, microeconomic impacts of climate change and the vulnerability of the agro-ecological systems are evaluated. The developed methodology is demonstrated through its application on a real-world case study for the South Al-Batinah region in the Sultanate of Oman where a coastal aquifer is affected by saltwater intrusion due to excessive groundwater withdrawal for irrigated agriculture.

[Application of synthetic biology to sustainable utilization of Chinese materia medica resources].

PubMed

Huang, Lu-Qi; Gao, Wei; Zhou, Yong-Jin

2014-01-01

Bioactive natural products are the material bases of Chinese materia medica resources. With successful applications of synthetic biology strategies to the researches and productions of taxol, artemisinin and tanshinone, etc, the potential ability of synthetic biology in the sustainable utilization of Chinese materia medica resources has been attracted by many researchers. This paper reviews the development of synthetic biology, the opportunities of sustainable utilization of Chinese materia medica resources, and the progress of synthetic biology applied to the researches of bioactive natural products. Furthermore, this paper also analyzes how to apply synthetic biology to sustainable utilization of Chinese materia medica resources and what the crucial factors are. Production of bioactive natural products with synthetic biology strategies will become a significant approach for the sustainable utilization of Chinese materia medica resources.

Scoping study of integrated resource planning needs in the public utility sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garrick, C J; Garrick, J M; Rue, D R

Integrated resource planning (IRP) is an approach to utility resource planning that integrates the evaluation of supply- and demand-site options for providing energy services at the least cost. Many utilities practice IRP; however, most studies about IRP focus on investor-owned utilities (IOUs). This scoping study investigates the IRP activities and needs of public utilities (not-for-profit utilities, including federal, state, municipal, and cooperative utilities). This study (1) profiles IRP-related characteristics of the public utility sector, (2) articulates the needs of public utilities in understanding and implementing IRP, and (3) identifies strategies to advance IRP principles in public utility planning.

DOMe: A deduplication optimization method for the NewSQL database backups

PubMed Central

Wang, Longxiang; Zhu, Zhengdong; Zhang, Xingjun; Wang, Yinfeng

2017-01-01

Reducing duplicated data of database backups is an important application scenario for data deduplication technology. NewSQL is an emerging database system and is now being used more and more widely. NewSQL systems need to improve data reliability by periodically backing up in-memory data, resulting in a lot of duplicated data. The traditional deduplication method is not optimized for the NewSQL server system and cannot take full advantage of hardware resources to optimize deduplication performance. A recent research pointed out that the future NewSQL server will have thousands of CPU cores, large DRAM and huge NVRAM. Therefore, how to utilize these hardware resources to optimize the performance of data deduplication is an important issue. To solve this problem, we propose a deduplication optimization method (DOMe) for NewSQL system backup. To take advantage of the large number of CPU cores in the NewSQL server to optimize deduplication performance, DOMe parallelizes the deduplication method based on the fork-join framework. The fingerprint index, which is the key data structure in the deduplication process, is implemented as pure in-memory hash table, which makes full use of the large DRAM in NewSQL system, eliminating the performance bottleneck problem of fingerprint index existing in traditional deduplication method. The H-store is used as a typical NewSQL database system to implement DOMe method. DOMe is experimentally analyzed by two representative backup data. The experimental results show that: 1) DOMe can reduce the duplicated NewSQL backup data. 2) DOMe significantly improves deduplication performance by parallelizing CDC algorithms. In the case of the theoretical speedup ratio of the server is 20.8, the speedup ratio of DOMe can achieve up to 18; 3) DOMe improved the deduplication throughput by 1.5 times through the pure in-memory index optimization method. PMID:29049307

Database resources of the National Center for Biotechnology Information.

PubMed

Wheeler, David L; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Ostell, James; Miller, Vadim; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Steven T; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene

2007-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link(BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace and Assembly Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Viral Genotyping Tools, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Miller, Vadim; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Shumway, Martin; Sequeira, Edwin; Sherry, Steven T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L.; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2008-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data available through NCBI's web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace, Assembly, and Short Read Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Database of Genotype and Phenotype, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting the web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:18045790

Managing simulation-based training: A framework for optimizing learning, cost, and time

NASA Astrophysics Data System (ADS)

Richmond, Noah Joseph

This study provides a management framework for optimizing training programs for learning, cost, and time when using simulation based training (SBT) and reality based training (RBT) as resources. Simulation is shown to be an effective means for implementing activity substitution as a way to reduce risk. The risk profile of 22 US Air Force vehicles are calculated, and the potential risk reduction is calculated under the assumption of perfect substitutability of RBT and SBT. Methods are subsequently developed to relax the assumption of perfect substitutability. The transfer effectiveness ratio (TER) concept is defined and modeled as a function of the quality of the simulator used, and the requirements of the activity trained. The Navy F/A-18 is then analyzed in a case study illustrating how learning can be maximized subject to constraints in cost and time, and also subject to the decision maker's preferences for the proportional and absolute use of simulation. Solution methods for optimizing multiple activities across shared resources are next provided. Finally, a simulation strategy including an operations planning program (OPP), an implementation program (IP), an acquisition program (AP), and a pedagogical research program (PRP) is detailed. The study provides the theoretical tools to understand how to leverage SBT, a case study demonstrating these tools' efficacy, and a set of policy recommendations to enable the US military to better utilize SBT in the future.

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Alternative Outpatient Chemotherapy Scheduling Method to Improve Patient Service Quality and Nurse Satisfaction.

PubMed

Huang, Yu-Li; Bryce, Alan H; Culbertson, Tracy; Connor, Sarah L; Looker, Sherry A; Altman, Kristin M; Collins, James G; Stellner, Winston; McWilliams, Robert R; Moreno-Aspitia, Alvaro; Ailawadhi, Sikander; Mesa, Ruben A

2018-02-01

Optimal scheduling and calendar management in an outpatient chemotherapy unit is a complex process that is driven by a need to focus on safety while accommodating a high degree of variability. Primary constraints are infusion times, staffing resources, chair availability, and unit hours. We undertook a process to analyze our existing management models across multiple practice settings in our health care system, then developed a model to optimize safety and efficiency. The model was tested in one of the community chemotherapy units. We assessed staffing violations as measured by nurse-to-patient ratios throughout the workday and at key points during treatment. Staffing violations were tracked before and after the implementation of the new model. The new model reduced staffing violations by nearly 50% and required fewer chairs to treat the same number of patients for the selected clinic day. Actual implementation results indicated that the new model leveled the distribution of patients across the workday with an 18% reduction in maximum chair utilization and a 27% reduction in staffing violations. Subsequently, a positive impact on peak pharmacy workload reduced delays by as much as 35 minutes. Nursing staff satisfaction with the new model was positive. We conclude that the proposed optimization approach with regard to nursing resource assignment and workload balance throughout a day effectively improves patient service quality and staff satisfaction.

Using mobile technology to optimize disease surveillance and healthcare delivery at mass gatherings: a case study from India's Kumbh Mela

PubMed Central

Kazi, Dhruv S.; Greenough, P. Gregg; Madhok, Rishi; Heerboth, Aaron; Shaikh, Ahmed; Leaning, Jennifer; Balsari, Satchit

2017-01-01

Abstract Background Planning for mass gatherings often includes temporary healthcare systems to address the needs of attendees. However, paper-based record keeping has traditionally precluded the timely application of collected clinical data for epidemic surveillance or optimization of healthcare delivery. We evaluated the feasibility of harnessing ubiquitous mobile technologies for conducting disease surveillance and monitoring resource utilization at the Allahabad Kumbh Mela in India, a 55-day festival attended by over 70 million people. Methods We developed an inexpensive, tablet-based customized disease surveillance system with real-time analytic capabilities, and piloted it at five field hospitals. Results The system captured 49 131 outpatient encounters over the 3-week study period. The most common presenting complaints were musculoskeletal pain (19%), fever (17%), cough (17%), coryza (16%) and diarrhoea (5%). The majority of patients received at least one prescription. The most common prescriptions were for antimicrobials, acetaminophen and non-steroidal anti-inflammatory drugs. There was great inter-site variability in caseload with the busiest hospital seeing 650% more patients than the least busy hospital, despite identical staffing. Conclusions Mobile-based health information solutions developed with a focus on user-centred design can be successfully deployed at mass gatherings in resource-scarce settings to optimize care delivery by providing real-time access to field data. PMID:27694349

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Using mobile technology to optimize disease surveillance and healthcare delivery at mass gatherings: a case study from India's Kumbh Mela.

PubMed

Kazi, Dhruv S; Greenough, P Gregg; Madhok, Rishi; Heerboth, Aaron; Shaikh, Ahmed; Leaning, Jennifer; Balsari, Satchit

2017-09-01

Planning for mass gatherings often includes temporary healthcare systems to address the needs of attendees. However, paper-based record keeping has traditionally precluded the timely application of collected clinical data for epidemic surveillance or optimization of healthcare delivery. We evaluated the feasibility of harnessing ubiquitous mobile technologies for conducting disease surveillance and monitoring resource utilization at the Allahabad Kumbh Mela in India, a 55-day festival attended by over 70 million people. We developed an inexpensive, tablet-based customized disease surveillance system with real-time analytic capabilities, and piloted it at five field hospitals. The system captured 49 131 outpatient encounters over the 3-week study period. The most common presenting complaints were musculoskeletal pain (19%), fever (17%), cough (17%), coryza (16%) and diarrhoea (5%). The majority of patients received at least one prescription. The most common prescriptions were for antimicrobials, acetaminophen and non-steroidal anti-inflammatory drugs. There was great inter-site variability in caseload with the busiest hospital seeing 650% more patients than the least busy hospital, despite identical staffing. Mobile-based health information solutions developed with a focus on user-centred design can be successfully deployed at mass gatherings in resource-scarce settings to optimize care delivery by providing real-time access to field data. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health.

Multi-time Scale Coordination of Distributed Energy Resources in Isolated Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony; Xie, Le; Butler-Purry, Karen

2016-03-31

In isolated power systems, including microgrids, distributed assets, such as renewable energy resources (e.g. wind, solar) and energy storage, can be actively coordinated to reduce dependency on fossil fuel generation. The key challenge of such coordination arises from significant uncertainty and variability occurring at small time scales associated with increased penetration of renewables. Specifically, the problem is with ensuring economic and efficient utilization of DERs, while also meeting operational objectives such as adequate frequency performance. One possible solution is to reduce the time step at which tertiary controls are implemented and to ensure feedback and look-ahead capability are incorporated tomore » handle variability and uncertainty. However, reducing the time step of tertiary controls necessitates investigating time-scale coupling with primary controls so as not to exacerbate system stability issues. In this paper, an optimal coordination (OC) strategy, which considers multiple time-scales, is proposed for isolated microgrid systems with a mix of DERs. This coordination strategy is based on an online moving horizon optimization approach. The effectiveness of the strategy was evaluated in terms of economics, technical performance, and computation time by varying key parameters that significantly impact performance. The illustrative example with realistic scenarios on a simulated isolated microgrid test system suggests that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems.« less

[Optimization of a cake formulation with functional characteristics using resistant starch, Sphagnum magellanicum moss and deffated hazel nut flour (Gevuina avellana, Mol)].

PubMed

Villarroel, Mario; Reyes, Carla; Hazbun, Julia; Karmelic, Julia

2007-03-01

Resistant starch (RS) Hi Maize 260, Sphagnum magellanicum Moss (SM) both natural resources rich in total dietary fiber, and defatted hazel nut flour (DHN) as protein resource were used in the development of a pastry product (queque) with functional characteristics. Taguchi methodology was utilized in the optimization process using the orthogonal array L934 with four control factors: RS, SM. DHN and Master Gluten 4000 (MG), 3 factor levels and 9 experimental trials. The best result of Sensory Quality (SQ) and signal to noise ratio (S/N) was obtained combining the minor levels of the independent variables. Main effect (average effects of factor) analysis and anova analysis showed that SM and DHN were the control factors with a significant influence (p<0.05) on the CS with a relative contribution of 83%. It is important to emphasize the total dietary fiber (8.7%) and protein (7.2%) values, the formers due to the presence of RS and SM. Shelf life study showed that the sensory characteristics flavour, appearance and texture were not affected when samples were stored at refrigerated temperatures but not at 20 degrees C, specifically flavour always kept a good preference during the whole period of time. Samples of optimized cakes showed very good results when they were submitted to hedonic test with 100% of favorable consumer's opinions.

Determinants of resource needs and utilization among refugees over time.

PubMed

Wright, A Michelle; Aldhalimi, Abir; Lumley, Mark A; Jamil, Hikmet; Pole, Nnamdi; Arnetz, Judith E; Arnetz, Bengt B

2016-04-01

This study examined refugees' resource needs and utilization over time, investigated the relationships between pre-displacement/socio-demographic variables and resource needs and utilization, and explored the role of resource needs and utilization on psychiatric symptom trajectories. Iraqi refugees to the United States (N = 298) were assessed upon arrival and at 1-year intervals for 2 years for socio-demographic variables and pre-displacement trauma experiences, their need for and utilization of 14 different resources, and PTSD and depressive symptoms. Although refugees reported reduction of some needs over time (e.g., need for cash assistance declined from 99 to 71 %), other needs remained high (e.g., 99 % of refugees reported a need for health care at the 2-year interview). Generally, the lowest needs were reported after 2 years, and the highest utilization occurred during the first year post-arrival. Pre-displacement trauma exposure predicted high health care needs but not high health care utilization. Both high need for and use of health care predicted increasing PTSD and depressive symptoms. Specifically, increased use of psychological care across the three measurement waves predicted more PTSD and depression symptoms at the 2-year interview. Differences emerged between need for and actual use of resources, especially for highly trauma-exposed refugees. Resettlement agencies and assistance programs should consider the complex relationships between resource needs, resource utilization, and mental health during the early resettlement period.

Determinants of Resource Needs and Utilization Among Refugees Over Time

PubMed Central

Wright, A. Michelle; Aldhalimi, Abir; Lumley, Mark A.; Jamil, Hikmet; Pole, Nnamdi; Arnetz, Judith E.; Arnetz, Bengt B.

2015-01-01

Purpose This study examined refugees’ resource needs and utilization over time, investigated the relationships between pre-displacement/socio-demographic variables and resource needs and utilization, and explored the role of resource needs and utilization on psychiatric symptom trajectories. Methods Iraqi refugees to the United States (N=298) were assessed upon arrival and at 1-year intervals for two years for socio-demographic variables and pre-displacement trauma experiences, their need for and utilization of 14 different resources, and PTSD and depressive symptoms. Results Although refugees reported reduction of some needs over time (e.g., need for cash assistance declined from 99% to 71%), other needs remained high (e.g., 99% of refugees reported a need for health care at the 2-year interview). Generally, the lowest needs were reported after 2 years, and the highest utilization occurred during the first year post-arrival. Pre-displacement trauma exposure predicted high health care needs but not high health care utilization. Both high need for and use of health care predicted increasing PTSD and depressive symptoms. Specifically, increased use of psychological care across the three measurement waves predicted more PTSD and depression symptoms at the 2-year interview. Conclusions Differences emerged between need for and actual use of resources, especially for highly trauma-exposed refugees. Resettlement agencies and assistance programs should consider the complex relationships between resource needs, resource utilization, and mental health during the early resettlement period. PMID:26370213

Optical properties of II-VI structures for solar energy utilization

NASA Astrophysics Data System (ADS)

Schrier, Joshua; Demchenko, Denis; Wang, Lin-Wang

2007-03-01

Although II-VI semiconductor materials are abundant, stable, and have direct band gaps, the band gaps are too large for optimal photovoltaic efficiency. However, staggered band alignments of pairs of these materials, and also the formation of intermediate impurity levels in the band gap (which has been demonstrated to increase the efficiency as compared to both single-junction devices), could be utilized to improve the suitability of these materials for solar energy utilization. Previous theoretical studies of these materials are limited, due to the well-known band gap underestimation by density-functional theory. To calculate the absorption spectra, we utilize a band-corrected planewave pseudopotential approach, which gives agreements of within 0.1 eV of the bulk optical gaps values. In this talk, I will present our work on predicting the optical properties of ZnO/ZnS and ZnO/ZnTe heterostructures, nanostructures, and alloys. This work was supported by U.S. Department of Energy under Contract No.DE-AC02-05CH11231 and used the resources of the National Energy Research Scientific Computing Center.

Strategies for Energy Efficient Resource Management of Hybrid Programming Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Dong; Supinski, Bronis de; Schulz, Martin

2013-01-01

Many scientific applications are programmed using hybrid programming models that use both message-passing and shared-memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared-memory or message-passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoptionmore » of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74% on average and up to 13.8%) with some performance gain (up to 7.5%) or negligible performance loss.« less

Value versus Accuracy: application of seasonal forecasts to a hydro-economic optimization model for the Sudanese Blue Nile

NASA Astrophysics Data System (ADS)

Satti, S.; Zaitchik, B. F.; Siddiqui, S.; Badr, H. S.; Shukla, S.; Peters-Lidard, C. D.

2015-12-01

The unpredictable nature of precipitation within the East African (EA) region makes it one of the most vulnerable, food insecure regions in the world. There is a vital need for forecasts to inform decision makers, both local and regional, and to help formulate the region's climate change adaptation strategies. Here, we present a suite of different seasonal forecast models, both statistical and dynamical, for the EA region. Objective regionalization is performed for EA on the basis of interannual variability in precipitation in both observations and models. This regionalization is applied as the basis for calculating a number of standard skill scores to evaluate each model's forecast accuracy. A dynamically linked Land Surface Model (LSM) is then applied to determine forecasted flows, which drive the Sudanese Hydroeconomic Optimization Model (SHOM). SHOM combines hydrologic, agronomic and economic inputs to determine the optimal decisions that maximize economic benefits along the Sudanese Blue Nile. This modeling sequence is designed to derive the potential added value of information of each forecasting model to agriculture and hydropower management. A rank of each model's forecasting skill score along with its added value of information is analyzed in order compare the performance of each forecast. This research aims to improve understanding of how characteristics of accuracy, lead time, and uncertainty of seasonal forecasts influence their utility to water resources decision makers who utilize them.

Optimizing Resources for Trustworthiness and Scientific Impact of Domain Repositories

NASA Astrophysics Data System (ADS)

Lehnert, K.

2017-12-01

Domain repositories, i.e. data archives tied to specific scientific communities, are widely recognized and trusted by their user communities for ensuring a high level of data quality, enhancing data value, access, and reuse through a unique combination of disciplinary and digital curation expertise. Their data services are guided by the practices and values of the specific community they serve and designed to support the advancement of their science. Domain repositories need to meet user expectations for scientific utility in order to be successful, but they also need to fulfill the requirements for trustworthy repository services to be acknowledged by scientists, funders, and publishers as a reliable facility that curates and preserves data following international standards. Domain repositories therefore need to carefully plan and balance investments to optimize the scientific impact of their data services and user satisfaction on the one hand, while maintaining a reliable and robust operation of the repository infrastructure on the other hand. Staying abreast of evolving repository standards to certify as a trustworthy repository and conducting a regular self-assessment and certification alone requires resources that compete with the demands for improving data holdings or usability of systems. The Interdisciplinary Earth Data Alliance (IEDA), a data facility funded by the US National Science Foundation, operates repositories for geochemical, marine Geoscience, and Antarctic research data, while also maintaining data products (global syntheses) and data visualization and analysis tools that are of high value for the science community and have demonstrated considerable scientific impact. Balancing the investments in the growth and utility of the syntheses with resources required for certifcation of IEDA's repository services has been challenging, and a major self-assessment effort has been difficult to accommodate. IEDA is exploring a partnership model to share generic repository functions (e.g. metadata registration, long-term archiving) with other repositories. This could substantially reduce the effort of certification and allow effort to focus on the domain-specific data curation and value-added services.

Trade-offs drive resource specialization and the gradual establishment of ecotypes

PubMed Central

2014-01-01

Background Speciation is driven by many different factors. Among those are trade-offs between different ways an organism utilizes resources, and these trade-offs can constrain the manner in which selection can optimize traits. Limited migration among allopatric populations and species interactions can also drive speciation, but here we ask if trade-offs alone are sufficient to drive speciation in the absence of other factors. Results We present a model to study the effects of trade-offs on specialization and adaptive radiation in asexual organisms based solely on competition for limiting resources, where trade-offs are stronger the greater an organism’s ability to utilize resources. In this model resources are perfectly substitutable, and fitness is derived from the consumption of these resources. The model contains no spatial parameters, and is therefore strictly sympatric. We quantify the degree of specialization by the number of ecotypes evolved and the niche breadth of the population, and observe that these are sensitive to resource influx and trade-offs. Resource influx has a strong effect on the degree of specialization, with a clear transition between minimal diversification at high influx and multiple species evolving at low resource influx. At low resource influx the degree of specialization further depends on the strength of the trade-offs, with more ecotypes evolving the stronger trade-offs are. The specialized organisms persist through negative frequency-dependent selection. In addition, by analyzing one of the evolutionary radiations in greater detail we demonstrate that a single mutation alone is not enough to establish a new ecotype, even though phylogenetic reconstruction identifies that mutation as the branching point. Instead, it takes a series of additional mutations to ensure the stable coexistence of the new ecotype in the background of the existing ones. Conclusions Trade-offs are sufficient to drive the evolution of specialization in sympatric asexual populations. Without trade-offs to restrain traits, generalists evolve and diversity decreases. The observation that several mutations are required to complete speciation, even when a single mutation creates the new species, highlights the gradual nature of speciation and the importance of phyletic evolution. PMID:24885598

Usefulness of multiqubit W-type states in quantum information processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, P.; Adhikari, S.; Kumar, A., E-mail: atulk@iitj.ac.in

We analyze the efficiency of multiqubit W-type states as resources for quantum information. For this, we identify and generalize four-qubit W-type states. Our results show that these states can be used as resources for deterministic quantum information processing. The utility of results, however, is limited by the availability of experimental setups to perform and distinguish multiqubit measurements. We therefore emphasize protocols where two users want to establish an optimal bipartite entanglement using the partially entangled W-type states. We find that for such practical purposes, four-qubit W-type states can be a better resource in comparison to three-qubit W-type states. For amore » dense coding protocol, our states can be used deterministically to send two bits of classical message by locally manipulating a single qubit. In addition, we also propose a realistic experimental method to prepare the four-qubit W-type states using standard unitary operations and weak measurements.« less

Puerto Rico water resources planning model program description

USGS Publications Warehouse

Moody, D.W.; Maddock, Thomas; Karlinger, M.R.; Lloyd, J.J.

1973-01-01

Because the use of the Mathematical Programming System -Extended (MPSX) to solve large linear and mixed integer programs requires the preparation of many input data cards, a matrix generator program to produce the MPSX input data from a much more limited set of data may expedite the use of the mixed integer programming optimization technique. The Model Definition and Control Program (MODCQP) is intended to assist a planner in preparing MPSX input data for the Puerto Rico Water Resources Planning Model. The model utilizes a mixed-integer mathematical program to identify a minimum present cost set of water resources projects (diversions, reservoirs, ground-water fields, desalinization plants, water treatment plants, and inter-basin transfers of water) which will meet a set of future water demands and to determine their sequence of construction. While MODCOP was specifically written to generate MPSX input data for the planning model described in this report, the program can be easily modified to reflect changes in the model's mathematical structure.

FASTER - A tool for DSN forecasting and scheduling

NASA Technical Reports Server (NTRS)

Werntz, David; Loyola, Steven; Zendejas, Silvino

1993-01-01

FASTER (Forecasting And Scheduling Tool for Earth-based Resources) is a suite of tools designed for forecasting and scheduling JPL's Deep Space Network (DSN). The DSN is a set of antennas and other associated resources that must be scheduled for satellite communications, astronomy, maintenance, and testing. FASTER consists of MS-Windows based programs that replace two existing programs (RALPH and PC4CAST). FASTER was designed to be more flexible, maintainable, and user friendly. FASTER makes heavy use of commercial software to allow for customization by users. FASTER implements scheduling as a two pass process: the first pass calculates a predictive profile of resource utilization; the second pass uses this information to calculate a cost function used in a dynamic programming optimization step. This information allows the scheduler to 'look ahead' at activities that are not as yet scheduled. FASTER has succeeded in allowing wider access to data and tools, reducing the amount of effort expended and increasing the quality of analysis.

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Momoh, James A.

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies,more » software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.« less

Criteria-Based Resource Allocation: A Tool to Improve Public Health Impact.

PubMed

Graham, J Ross; Mackie, Christopher

2016-01-01

Resource allocation in local public health (LPH) has been reported as a significant challenge for practitioners and a Public Health Services and Systems Research priority. Ensuring available resources have maximum impact on community health and maintaining public confidence in the resource allocation process are key challenges. A popular strategy in health care settings to address these challenges is Program Budgeting and Marginal Analysis (PBMA). This case study used PBMA in an LPH setting to examine its appropriateness and utility. The criteria-based resource allocation process PBMA was implemented to guide the development of annual organizational budget in an attempt to maximize the impact of agency resources. Senior leaders and managers were surveyed postimplementation regarding process facilitators, challenges, and successes. Canada's largest autonomous LPH agency. PBMA was used to shift 3.4% of the agency budget from lower-impact areas (through 34 specific disinvestments) to higher-impact areas (26 specific reinvestments). Senior leaders and managers validated the process as a useful approach for improving the public health impact of agency resources. However, they also reported the process may have decreased frontline staff confidence in senior leadership. In this case study, PBMA was used successfully to reallocate a sizable portion of an LPH agency's budget toward higher-impact activities. PBMA warrants further study as a tool to support optimal resource allocation in LPH settings.

Multidimensional indexing structure for use with linear optimization queries

NASA Technical Reports Server (NTRS)

Bergman, Lawrence David (Inventor); Castelli, Vittorio (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Smith, John Richard (Inventor)

2002-01-01

Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.

Measuring the usefulness of family planning job aids following distribution at training workshops.

PubMed

Tumlinson, Katherine; Hubacher, David; Wesson, Jennifer; Lasway, Christine

2010-09-01

A job aid is a tool, such as a flowchart or checklist, that makes it easier for staff to carry out tasks by providing quick access to needed information. Many public health organizations are engaged in the production of job aids intended to improve adherence to important medical guidelines and protocols, particularly in resource-constrained countries. However, some evidence suggests that actual use of job aids remains low. One strategy for improving utilization is the introduction of job aids in training workshops. This paper summarizes the results of two separate evaluations conducted in Uganda and the Dominican Republic (DR) which measured the usefulness of a series of four family planning checklists 7-24 months after distribution in training workshops. While more than half of the health care providers used the checklists at least once, utilization rates were sub-optimal. However, the vast majority of those providers who utilized the checklists found them to be very useful in their work.

[Emergency care in the autonomous regions of Spain. Improvement in pre-hospital emergency care and welfare coordination. SESPAS Report 2012].

PubMed

Miguel García, Félix; Fernández Quintana, Ana Isabel; Díaz Prats, Amadeo

2012-03-01

The present article describes the general organization of pre-hospital emergency care in the autonomous regions and provides data on activity corresponding to 2010, drawn from the information available in the Primary Care Information System of the Ministry of Health, Social Policy and Equality. Emergency care is provided through various organizational structures covering 24-hour periods. Family medicine attended 17.8 million emergency consultations and nursing attended 10.2 million (year 2010, 14 autonomous communities, 79.7% of the National Health System population). Emergency department utilization ranged between 0.11 and 0.83 urgent family physician consultations per inhabitant/year and between 0.05 and 0.57 nursing consultations per inhabitant/year. Any reform in the management of pre-hospital emergency care will involve organizational changes and aims to produce measurable improvements in healthcare coordination. In the new organizational designs, most of the responsibility lies with human resources in order to achieve the new goals for the future aims to be presented in an operational teamwork structure. Undoubtedly, the main challenge is to achieve optimal coordination with other welfare levels, including the police, social services, nursing homes, etc. If optimal care of the population needs to count on the efforts of all these groups, mobility, individual differences, consistent achievement of high standards, and -most of all- the use of these services by citizens will determine the final result. The results can be quantified in various ways, but evaluation should concentrate on the resources used, the degree of satisfaction among all the parties involved and optimal management of demand, which will help to disseminate the need for a rational resource use. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

Aether: leveraging linear programming for optimal cloud computing in genomics

PubMed Central

Luber, Jacob M; Tierney, Braden T; Cofer, Evan M; Patel, Chirag J

2018-01-01

Abstract Motivation Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Results Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users’ existing HPC pipelines. Availability and implementation Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. Contact chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:29228186

Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

NASA Astrophysics Data System (ADS)

Ayuningrum, Theresia Vika; Purnaweni, Hartuti

2018-02-01

Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

Study on the pre-treatment of oxidized zinc ore prior to flotation

NASA Astrophysics Data System (ADS)

He, Dong-sheng; Chen, Yun; Xiang, Ping; Yu, Zheng-jun; Potgieter, J. H.

2018-02-01

The pre-treatment of zinc oxide bearing ores with high slime content is important to ensure that resources are utilized optimally. This paper reports an improved process using hydrocyclone de-sliming, dispersion reagents, and magnetic removal of iron minerals for the pre-treatment of zinc oxide ore with a high slime and iron content, and the benefits compared to traditional technologies are shown. In addition, this paper investigates the damage related to fine slime and iron during zinc oxide flotation, the necessity of using hydrocyclone de-sliming together with dispersion reagents to alleviate the influence of slime, and interactions among hydrocyclone de-sliming, reagent dispersion, and magnetic iron removal. Results show that under optimized operating conditions the entire beneficiation technology results in a flotation concentrate with a Zn grade of 34.66% and a recovery of 73.41%.

Managing time-substitutable electricity usage using dynamic controls

DOEpatents

Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

2017-02-07

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

Managing time-substitutable electricity usage using dynamic controls

DOEpatents

Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

2017-02-21

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

[Comparison of potential yield and resource utilization efficiency of main food crops in three provinces of Northeast China under climate change].

PubMed

Wang, Xiao-yu; Yang, Xiao-guang; Sun, Shuang; Xie, Wen-juan

2015-10-01

Based on the daily data of 65 meteorological stations from 1961 to 2010 and the crop phenology data in the potential cultivation zones of thermophilic and chimonophilous crops in Northeast China, the crop potential yields were calculated through step-by-step correction method. The spatio-temporal distribution of the crop potential yields at different levels was analyzed. And then we quantified the limitations of temperature and precipitation on the crop potential yields and compared the differences in the climatic resource utilization efficiency. The results showed that the thermal potential yields of six crops (including maize, rice, spring wheat, sorghum, millet and soybean) during the period 1961-2010 deceased from west to east. The climatic potential yields of the five crops (spring wheat not included) were higher in the south than in the north. The potential yield loss rate due to temperature limitations of the six crops presented a spatial distribution pattern and was higher in the east than in the west. Among the six main crops, the yield potential loss rate due to temperature limitation of the soybean was the highest (51%), and those of the other crops fluctuated within the range of 33%-41%. The potential yield loss rate due to water limitation had an obvious regional difference, and was high in Songnen Plain and Changbai Mountains. The potential yield loss rate of spring wheat was the highest (50%), and those of the other four rainfed crops fluctuated within the range of 8%-10%. The solar energy utilization efficiency of the six main crops ranged from 0.9% to 2.7%, in the order of maize> sorghum>rice>millet>spring wheat>soybean. The precipitation utilization efficiency of the maize, sorghum, spring wheat, millet and soybean under rainfed conditions ranged from 8 to 35 kg . hm-2 . mm-1, in the order of maize>sorghum>spring wheat>millet>soybean. In those areas with lower efficiency of solar energy utilization and precipitation utilization, such as Changbai Mountains and the south of Lesser Khingan Mountains, measures could be taken to increase the efficiency of resource utilization such as rational close-planting, selection of droughtresistant varieties, proper and timely fertilization, farming for soil water storage, optimization of crop layout and so on.

The 5 Clinical Pillars of Value for Total Joint Arthroplasty in a Bundled Payment Paradigm.

PubMed

Kim, Kelvin; Iorio, Richard

2017-06-01

Our large, urban, tertiary, university-based institution reflects on its 4-year experience with Bundled Payments for Care Improvement. We will describe the importance of 5 clinical pillars that have contributed to the early success of our bundled payment initiative. We are convinced that value-based care delivered through bundled payment initiatives is the best method to optimize patient outcomes while rewarding surgeons and hospitals for adapting to the evolving healthcare reforms. We summarize a number of experiences and lessons learned since the implementation of Bundled Payments for Care Improvement at our institution. Our experience has led to the development of more refined clinical pathways and coordination of care through evidence-based approaches. We have established that the success of the bundled payment program rests on the following 5 main clinical pillars: (1) optimizing patient selection and comorbidities; (2) optimizing care coordination, patient education, shared decision making, and patient expectations; (3) using a multimodal pain management protocol and minimizing narcotic use to facilitate rapid rehabilitation; (4) optimizing blood management, and standardizing venous thromboembolic disease prophylaxis treatment by risk standardizing patients and minimizing the use of aggressive anticoagulation; and (5) minimizing post-acute facility and resource utilization, and maximizing home resources for patient recovery. From our extensive experience with bundled payment models, we have established 5 clinical pillars of value for bundled payments. Our hope is that these principles will help ease the transition to value-based care for less-experienced healthcare systems. Copyright © 2017 Elsevier Inc. All rights reserved.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Kómár, P.; Kessler, E. M.; Bishof, M.; Jiang, L.; Sørensen, A. S.; Ye, J.; Lukin, M. D.

2014-08-01

The development of precise atomic clocks plays an increasingly important role in modern society. Shared timing information constitutes a key resource for navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System. By combining precision metrology and quantum networks, we propose a quantum, cooperative protocol for operating a network of geographically remote optical atomic clocks. Using nonlocal entangled states, we demonstrate an optimal utilization of global resources, and show that such a network can be operated near the fundamental precision limit set by quantum theory. Furthermore, the internal structure of the network, combined with quantum communication techniques, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy.

Fossil Energy Planning for Navajo Nation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acedo, Margarita

This project includes fossil energy transition planning to find optimal solutions that benefit the Navajo Nation and stakeholders. The majority of the tribe’s budget currently comes from fossil energy-revenue. The purpose of this work is to assess potential alternative energy resources including solar photovoltaics and biomass (microalgae for either biofuel or food consumption). This includes evaluating carbon-based reserves related to the tribe’s resources including CO 2 emissions for the Four Corners generating station. The methodology for this analysis will consist of data collection from publicly available data, utilizing expertise from national laboratories and academics, and evaluating economic, health, and environmentalmore » impacts. Finally, this report will highlight areas of opportunities to implement renewable energy in the Navajo Nation by presenting the technology requirements, cost, and considerations to energy, water, and environment in an educational structure.« less

The application of Firefly algorithm in an Adaptive Emergency Evacuation Centre Management (AEECM) for dynamic relocation of flood victims

NASA Astrophysics Data System (ADS)

ChePa, Noraziah; Hashim, Nor Laily; Yusof, Yuhanis; Hussain, Azham

2016-08-01

Flood evacuation centre is defined as a temporary location or area of people from disaster particularly flood as a rescue or precautionary measure. Gazetted evacuation centres are normally located at secure places which have small chances from being drowned by flood. However, due to extreme flood several evacuation centres in Kelantan were unexpectedly drowned. Currently, there is no study done on proposing a decision support aid to reallocate victims and resources of the evacuation centre when the situation getting worsens. Therefore, this study proposes a decision aid model to be utilized in realizing an adaptive emergency evacuation centre management system. This study undergoes two main phases; development of algorithm and models, and development of a web-based and mobile app. The proposed model operates using Firefly multi-objective optimization algorithm that creates an optimal schedule for the relocation of victims and resources for an evacuation centre. The proposed decision aid model and the adaptive system can be applied in supporting the National Security Council's respond mechanisms for handling disaster management level II (State level) especially in providing better management of the flood evacuating centres.

Modelling radicalization: how small violent fringe sects develop into large indoctrinated societies

PubMed Central

2017-01-01

We model radicalization in a society consisting of two competing religious, ethnic or political groups. Each of the ‘sects’ is divided into moderate and radical factions, with intra-group transitions occurring either spontaneously or through indoctrination. We also include the possibility of one group violently attacking the other. The intra-group transition rates of one group are modelled to explicitly depend on the actions and characteristics of the other, including violent episodes, effectively coupling the dynamics of the two sects. We use a game theoretic framework and assume that radical factions may tune ‘strategic’ parameters to optimize given utility functions aimed at maximizing their ranks while minimizing the damage inflicted by their rivals. Constraints include limited overall resources that must be optimally allocated between indoctrination and external attacks on the other group. Various scenarios are considered, from symmetric sects whose behaviours mirror each other, to totally asymmetric ones where one sect may have a larger population or a superior resource availability. We discuss under what conditions sects preferentially employ indoctrination or violence, and how allowing sects to readjust their strategies allows for small, violent sects to grow into large, indoctrinated communities. PMID:28879010

Modelling radicalization: how small violent fringe sects develop into large indoctrinated societies

NASA Astrophysics Data System (ADS)

Short, Martin B.; McCalla, Scott G.; D'Orsogna, Maria R.

2017-08-01

We model radicalization in a society consisting of two competing religious, ethnic or political groups. Each of the `sects' is divided into moderate and radical factions, with intra-group transitions occurring either spontaneously or through indoctrination. We also include the possibility of one group violently attacking the other. The intra-group transition rates of one group are modelled to explicitly depend on the actions and characteristics of the other, including violent episodes, effectively coupling the dynamics of the two sects. We use a game theoretic framework and assume that radical factions may tune `strategic' parameters to optimize given utility functions aimed at maximizing their ranks while minimizing the damage inflicted by their rivals. Constraints include limited overall resources that must be optimally allocated between indoctrination and external attacks on the other group. Various scenarios are considered, from symmetric sects whose behaviours mirror each other, to totally asymmetric ones where one sect may have a larger population or a superior resource availability. We discuss under what conditions sects preferentially employ indoctrination or violence, and how allowing sects to readjust their strategies allows for small, violent sects to grow into large, indoctrinated communities.

Study the impact of rainfall on the United Arab Emirates dams using remote sensing and image processing techniques

NASA Astrophysics Data System (ADS)

Al Marzouqi, Fatima A.; Al Besher, Shaikha A.; Al Mansoori, Saeed H.

2017-10-01

The United Arab Emirates (UAE) has given great attention to the environment and sustainable development through applications of best practices of global standards that ensure optimal investment in natural resources. Since the UAE is located in an arid region which is known as dry, sandy and get a small amount of rainfall, thus the water resources are limited and accordingly, the government has initiated an integrated water resources management (IWRM) strategy to meet the increasing demands of water. Dams are considered as one of the important strategies that are suitable for this arid region. An event of rainfall if between heavy to severe in a short duration could cause flash floods and damages to population centers and areas of agriculture nearby. To prevent that from happening, several dams and barriers were built to protect human life and infrastructure. Besides contribution to enhance the water resources and use them optimally to irrigate the growing agricultural areas across the country. Geographically, most of the dams were located in the northern and eastern part of the UAE, around mountainous areas. This study aims to monitor the changes that occurred to five dams of the north-eastern region of the UAE during 2015 and 2016 through the use of remote sensing technology of optical images captured by "DubaiSat-2". The segmentation approach utilized in this study is based on a band ratio technique called Normalized Difference Water Index (NDWI). The experimental results revealed that the proposed approach is efficient in detecting dams from multispectral satellite images.

County-Level Population Economic Status and Medicare Imaging Resource Consumption.

PubMed

Rosenkrantz, Andrew B; Hughes, Danny R; Prabhakar, Anand M; Duszak, Richard

2017-06-01

The aim of this study was to assess relationships between county-level variation in Medicare beneficiary imaging resource consumption and measures of population economic status. The 2013 CMS Geographic Variation Public Use File was used to identify county-level per capita Medicare fee-for-service imaging utilization and nationally standardized costs to the Medicare program. The County Health Rankings public data set was used to identify county-level measures of population economic status. Regional variation was assessed, and multivariate regressions were performed. Imaging events per 1,000 Medicare beneficiaries varied 1.8-fold (range, 2,723-4,843) at the state level and 5.3-fold (range, 1,228-6,455) at the county level. Per capita nationally standardized imaging costs to Medicare varied 4.2-fold (range, $84-$353) at the state level and 14.1-fold (range, $33-$471) at the county level. Within individual states, county-level utilization varied on average 2.0-fold (range, 1.1- to 3.1-fold), and costs varied 2.8-fold (range, 1.1- to 6.4-fold). For both large urban populations and small rural states, Medicare imaging resource consumption was heterogeneously variable at the county level. Adjusting for county-level gender, ethnicity, rural status, and population density, countywide unemployment rates showed strong independent positive associations with Medicare imaging events (β = 26.96) and costs (β = 4.37), whereas uninsured rates showed strong independent positive associations with Medicare imaging costs (β = 2.68). Medicare imaging utilization and costs both vary far more at the county than at the state level. Unfavorable measures of county-level population economic status in the non-Medicare population are independently associated with greater Medicare imaging resource consumption. Future efforts to optimize Medicare imaging use should consider the influence of local indigenous socioeconomic factors outside the scope of traditional beneficiary-focused policy initiatives. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Optimization of numerical weather/wave prediction models based on information geometry and computational techniques

NASA Astrophysics Data System (ADS)

Galanis, George; Famelis, Ioannis; Kalogeri, Christina

2014-10-01

The last years a new highly demanding framework has been set for environmental sciences and applied mathematics as a result of the needs posed by issues that are of interest not only of the scientific community but of today's society in general: global warming, renewable resources of energy, natural hazards can be listed among them. Two are the main directions that the research community follows today in order to address the above problems: The utilization of environmental observations obtained from in situ or remote sensing sources and the meteorological-oceanographic simulations based on physical-mathematical models. In particular, trying to reach credible local forecasts the two previous data sources are combined by algorithms that are essentially based on optimization processes. The conventional approaches in this framework usually neglect the topological-geometrical properties of the space of the data under study by adopting least square methods based on classical Euclidean geometry tools. In the present work new optimization techniques are discussed making use of methodologies from a rapidly advancing branch of applied Mathematics, the Information Geometry. The latter prove that the distributions of data sets are elements of non-Euclidean structures in which the underlying geometry may differ significantly from the classical one. Geometrical entities like Riemannian metrics, distances, curvature and affine connections are utilized in order to define the optimum distributions fitting to the environmental data at specific areas and to form differential systems that describes the optimization procedures. The methodology proposed is clarified by an application for wind speed forecasts in the Kefaloniaisland, Greece.

Producing regionally-relevant multiobjective tradeoffs to engage with Colorado water managers

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Basdekas, L.; Dilling, L.

2016-12-01

Disseminating results from water resources systems analysis research can be challenging when there are political or regulatory barriers associated with real-world models, or when a research model does not incorporate management context to which practitioners can relate. As part of a larger transdisciplinary study, we developed a broadly-applicable case study in collaboration with our partners at six diverse water utilities in the Front Range of Colorado, USA. Our model, called the "Eldorado Utility Planning Model", incorporates realistic water management decisions and objectives and achieves a pragmatic balance between system complexity and simplicity. Using the sophisticated modeling platform RiverWare, we modeled a spatially distributed regional network in which, under varying climate scenarios, the Eldorado Utility can meet growing demand from its variety of sources and by interacting with other users in the network. In accordance with complicated Front Range water laws, ownership, priority of use, and restricted uses of water are tracked through RiverWare's accounting functionality. To achieve good system performance, Eldorado can make decisions such as expand/build a reservoir, purchase rights from one or more actors, and enact conservation. This presentation introduces the model, and motivates how it can be used to aid researchers in developing multi-objective evolutionary algorithm (MOEA)-based optimization for similar multi-reservoir systems in Colorado and the Western US. Within the optimization, system performance is quantified by 5 objectives: minimizing time in restrictions; new storage capacity; newly developed supply; and uncaptured water; and maximizing year-end storage. Our results demonstrate critical tradeoffs between the objectives and show how these tradeoffs are affected by several realistic climate change scenarios. These results were used within an interactive workshop that helped demonstrate the application of MOEA-based optimization for water management in the western US.

Dynamic traffic grooming with Spectrum Engineering (TG-SE) in flexible grid optical networks

NASA Astrophysics Data System (ADS)

Yu, Xiaosong; Zhao, Yongli; Zhang, Jiawei; Wang, Jianping; Zhang, Guoying; Chen, Xue; Zhang, Jie

2015-12-01

Flexible grid has emerged as an evolutionary technology to satisfy the ever increasing demand for higher spectrum efficiency and operational flexibility. To optimize the spectrum resource utilization, this paper introduces the concept of Spectrum Engineering in flex-grid optical networks. The sliceable optical transponder has been proposed to offload IP traffic to the optical layer and reduce the number of IP router ports and transponders. We discuss the impact of sliceable transponder in traffic grooming and propose several traffic-grooming schemes with Spectrum Engineering (TG-SE). Our results show that there is a tradeoff among different traffic grooming policies, which should be adopted based on the network operator's objectives. The proposed traffic grooming with Spectrum Engineering schemes can reduce OPEX as well as increase spectrum efficiency by efficiently utilizing the bandwidth variability and capability of sliceable optical transponders.

Improving the Fabrication of Semiconductor Bragg Lasers

NASA Astrophysics Data System (ADS)

Chen, Eric Ping Chun

Fabrication process developments for Bragg reflection lasers have been optimized in this thesis using resources available to the group. New e-beam lithography and oxide etch recipes have been developed to minimize sidewall roughness and residues. E-beam evaporated metal contacts for semiconductor diode laser utilizing oblique angle deposition have also been developed in-house for the first time. Furthermore, improvement in micro-loading effect of DFB laser etching has been demonstrated where the ratio of tapered portion of the sidewall to total etch depth is reduced by half, from 33% to 15%. Electrical, optical and thermal performance of the fabricated lasers are characterized. Comparing the results to previous generation lasers, average dynamic resistance is decreased drastically from 14 Ohms to 7 Ohms and threshold current density also reduced from 1705A/cm2 to 1383A/ cm2. Improvement in laser performance is result of reduced loss from optimized fabrication processes. BRL bow-tie tapered lasers is then fabricated for the first time and output power of 18mW at 200mA input is measured. Benefiting from the increased effective area and better carrier utilization, reduction in threshold current density from 1383A/cm 2 to 712A/cm2 is observed.

Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

PubMed

Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend

2011-10-11

In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.

Photovoltaic frequency–watt curve design for frequency regulation and fast contingency reserves

DOE PAGES

Johnson, Jay; Neely, Jason C.; Delhotal, Jarod J.; ...

2016-09-02

When renewable energy resources are installed in electricity grids, they typically increase generation variability and displace thermal generator control action and inertia. Grid operators combat these emerging challenges with advanced distributed energy resource (DER) functions to support frequency and provide voltage regulation and protection mechanisms. This paper focuses on providing frequency reserves using autonomous IEC TR 61850-90-7 pointwise frequency-watt (FW) functions that adjust DER active power as a function of measured grid frequency. The importance of incorporating FW functions into a fleet of photovoltaic (PV) systems is demonstrated in simulation. Effects of FW curve design, including curtailment, deadband, and droop,more » were analyzed against performance metrics using Latin hypercube sampling for 20%, 70%, and 120% PV penetration scenarios on the Hawaiian island of Lanai. Finally, to understand the financial implications of FW functions to utilities, a performance function was defined based on monetary costs attributable to curtailed PV production, load shedding, and generator wear. An optimization wrapper was then created to find the best FW function curve for each penetration level. Lastly, it was found that in all cases, the utility would save money by implementing appropriate FW functions.« less

In-Situ Resource Utilization (ISRU) Capability Roadmap Progress Review

NASA Technical Reports Server (NTRS)

Sanders, Gerald B.; Duke, Michael

2005-01-01

A progress review on In-Situ Resource Utilization (ISRU) capability is presented. The topics include: 1) In-Situ Resource Utilization (ISRU) Capability Roadmap: Level 1; 2) ISRU Emphasized Architecture Overview; 3) ISRU Capability Elements: Level 2 and below; and 4) ISRU Capability Roadmap Wrap-up.

Protecting water and wastewater infrastructure from cyber attacks

NASA Astrophysics Data System (ADS)

Panguluri, Srinivas; Phillips, William; Cusimano, John

2011-12-01

Multiple organizations over the years have collected and analyzed data on cyber attacks and they all agree on one conclusion: cyber attacks are real and can cause significant damages. This paper presents some recent statistics on cyber attacks and resulting damages. Water and wastewater utilities must adopt countermeasures to prevent or minimize the damage in case of such attacks. Many unique challenges are faced by the water and wastewater industry while selecting and implementing security countermeasures; the key challenges are: 1) the increasing interconnection of their business and control system networks, 2) large variation of proprietary industrial control equipment utilized, 3) multitude of cross-sector cyber-security standards, and 4) the differences in the equipment vendor's approaches to meet these security standards. The utilities can meet these challenges by voluntarily selecting and adopting security standards, conducting a gap analysis, performing vulnerability/risk analysis, and undertaking countermeasures that best meets their security and organizational requirements. Utilities should optimally utilize their limited resources to prepare and implement necessary programs that are designed to increase cyber-security over the years. Implementing cyber security does not necessarily have to be expensive, substantial improvements can be accomplished through policy, procedure, training and awareness. Utilities can also get creative and allocate more funding through annual budgets and reduce dependence upon capital improvement programs to achieve improvements in cyber-security.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

PubMed

Zomorodian, Mehdi; Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method

PubMed Central

Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system. PMID:29216200

Symbiosis of sea anemones and hermit crabs: different resource utilization patterns in the Aegean Sea

NASA Astrophysics Data System (ADS)

Vafeiadou, Anna-Maria; Antoniadou, Chryssanthi; Chintiroglou, Chariton

2012-09-01

The small-scale distribution and resource utilization patterns of hermit crabs living in symbiosis with sea anemones were investigated in the Aegean Sea. Four hermit crab species, occupying shells of nine gastropod species, were found in symbiosis with the sea anemone Calliactis parasitica. Shell resource utilization patterns varied among hermit crabs, with Dardanus species utilizing a wide variety of shells. The size structure of hermit crab populations also affected shell resource utilization, with small-sized individuals inhabiting a larger variety of shells. Sea anemone utilization patterns varied both among hermit crab species and among residence shells, with larger crabs and shells hosting an increased abundance and biomass of C. parasitica. The examined biometric relationships suggested that small-sized crabs carry, proportionally to their weight, heavier shells and increased anemone biomass than larger ones. Exceptions to the above patterns are related either to local resource availability or to other environmental factors.

Heuristic-based scheduling algorithm for high level synthesis

NASA Technical Reports Server (NTRS)

Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye

1992-01-01

A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.

Are airbags effective in decreasing trauma in auto accidents?

PubMed

Williams, Regan F; Croce, Martin A

2009-01-01

Multiple studies have addressed the effect of airbags on injury and mortality after motor vehicle collision with discrepant results (Table 1). Although large, population-based studies have minimized the protective effect of airbags, the most recent studies examining airbags have shown a decrease in injury and death, with the greatest protective effect seen when they are used in conjunction with seatbelts. Optimal restraint use is also associated with a decrease in infectious morbidity and hospital resource utilization. The widespread use of seatbelts and airbags will continue to save lives and decrease morbidity after motor vehicle collision.

An Architecture for Cross-Cloud System Management

NASA Astrophysics Data System (ADS)

Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad

The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.

Integrating prediction, provenance, and optimization into high energy workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schram, M.; Bansal, V.; Friese, R. D.

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

A national assessment of children with special health care needs: prevalence of special needs and use of health care services among children in the military health system.

PubMed

Williams, Thomas V; Schone, Eric M; Archibald, Nancy D; Thompson, Joseph W

2004-08-01

Children are frequently perceived to be healthy, low-risk individuals with a majority of clinical services devoted to health maintenance and preventive clinical services. However, a subset of children have unique needs that require specialized care to achieve optimal health outcomes. The purpose of this research was to use survey tools that have been developed to identify children with special health care needs (CSHCN) to measure prevalence and resource needs of these children in the military health system (MHS). The US Department of Defense manages the MHS, which is one of the largest integrated health care systems in the world and provides care to almost 2,000000 children. We incorporated the CSHCN survey screener and assessment questions into the annual health care survey of beneficiaries who are eligible for benefits within the MHS. In addition, we used claims information available from inpatient and outpatient services. We used parent reports from the survey to estimate the prevalence of CSHCN. Incorporating claims data and restricting our analyses to those who were enrolled continuously in a military health maintenance organization (TRICARE Prime), we described utilization of different types of health care resources and compared CSHCN with their healthy counterparts. Finally, we examined alternative types of special needs and performed regression analyses to identify the major determinants of health needs and resource utilization to guide system management and policy development. CSHCN compose 23% of the TRICARE Prime enrollees who are younger than 18 years and whose parents responded to the survey. The needs of a majority of these children consist of prescription medications and services targeting medical, mental health, and educational needs. CSHCN experience 5 times as many admissions and 10 times as many days in hospitals compared with children without special needs. CSHCN are responsible for nearly half of outpatient visits for enrolled children and more than three quarters of inpatient days. Service utilization varies dramatically by type of special need and other demographic variables. CSHCN represent a major challenge to organized systems of care and our society. Because they represent a group of children who are particularly at risk with potential for improved health outcomes, efforts to improve quality, coordinate care, and optimize efficiency should focus on this target population.

Predisposing characteristics, enabling resources and need as predictors of utilization and clinical outcomes for veterans receiving mental health services.

PubMed

Fasoli, DiJon R; Glickman, Mark E; Eisen, Susan V

2010-04-01

Though demand for mental health services (MHS) among US veterans is increasing, MHS utilization per veteran is decreasing. With health and social service needs competing for limited resources, it is important to understand the association between patient factors, MHS utilization, and clinical outcomes. We use a framework based on Andersen's behavioral model of health service utilization to examine predisposing characteristics, enabling resources, and clinical need as predictors of MHS utilization and clinical outcomes. This was a prospective observational study of veterans receiving inpatient or outpatient MHS through Veterans Administration programs. Clinician ratings (Global Assessment of Functioning [GAF]) and self-report assessments (Behavior and Symptom Identification Scale-24) were completed for 421 veterans at enrollment and 3 months later. Linear and logistic regression analyses were conducted to examine: (1) predisposing characteristics, enabling resources, and need as predictors of MHS inpatient, residential, and outpatient utilization and (2) the association between individual characteristics, utilization, and clinical outcomes. Being older, female, having greater clinical need, lack of enabling resources (employment, stable housing, and social support), and easy access to treatment significantly predicted greater MHS utilization at 3-month follow-up. Less clinical need and no inpatient psychiatric hospitalization predicted better GAF and Behavior and Symptom Identification Scale-24 scores. White race and residential treatment also predicted better GAF scores. Neither enabling resources, nor number of outpatient mental health visits predicted clinical outcomes. This application of Andersen's behavioral model of health service utilization confirmed associations between some predisposing characteristics, need, and enabling resources on MHS utilization but only predisposing characteristics, need, and utilization were associated with clinical outcomes.

Using Forecasting to Predict Long-Term Resource Utilization for Web Services

ERIC Educational Resources Information Center

Yoas, Daniel W.

2013-01-01

Researchers have spent years understanding resource utilization to improve scheduling, load balancing, and system management through short-term prediction of resource utilization. Early research focused primarily on single operating systems; later, interest shifted to distributed systems and, finally, into web services. In each case researchers…

Resource Utilization by Native and Invasive Earthworms and Their Effects on Soil Carbon and Nitrogen Dynamics in Puerto Rican Soils

Treesearch

Ching-Yu Huang; Grizelle Gonzalez; Paul F. Hendrix

2016-01-01

Resource utilization by earthworms affects soil C and N dynamics and further colonization of invasive earthworms. By applying 13C-labeled Tabebuia heterophylla leaves and 15N-labeled Andropogon glomeratus grass, we investigated resource utilization by three earthworm species (...

Combinatorial Optimization in Project Selection Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Dewi, Sari; Sawaluddin

2018-01-01

This paper discusses the problem of project selection in the presence of two objective functions that maximize profit and minimize cost and the existence of some limitations is limited resources availability and time available so that there is need allocation of resources in each project. These resources are human resources, machine resources, raw material resources. This is treated as a consideration to not exceed the budget that has been determined. So that can be formulated mathematics for objective function (multi-objective) with boundaries that fulfilled. To assist the project selection process, a multi-objective combinatorial optimization approach is used to obtain an optimal solution for the selection of the right project. It then described a multi-objective method of genetic algorithm as one method of multi-objective combinatorial optimization approach to simplify the project selection process in a large scope.

Optimal resource states for local state discrimination

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Somshubhro; Halder, Saronath; Nathanson, Michael

2018-02-01

We study the problem of locally distinguishing pure quantum states using shared entanglement as a resource. For a given set of locally indistinguishable states, we define a resource state to be useful if it can enhance local distinguishability and optimal if it can distinguish the states as well as global measurements and is also minimal with respect to a partial ordering defined by entanglement and dimension. We present examples of useful resources and show that an entangled state need not be useful for distinguishing a given set of states. We obtain optimal resources with explicit local protocols to distinguish multipartite Greenberger-Horne-Zeilinger and graph states and also show that a maximally entangled state is an optimal resource under one-way local operations and classical communication to distinguish any bipartite orthonormal basis which contains at least one entangled state of full Schmidt rank.

NASA In-Situ Resource Utilization Project-and Seals Challenges

NASA Technical Reports Server (NTRS)

Sacksteder, Kurt; Linne, Diane

2006-01-01

A viewgraph presentation on NASA's In-Situ Resource Utilization Project and Seals Challenges is shown. The topics include: 1) What Are Space Resources?; 2) Space Resource Utilization for Exploration; 3) ISRU Enables Affordable, Sustainable & Flexible Exploration; 4) Propellant from the Moon Could Revolutionize Space Transportation; 5) NASA ISRU Capability Roadmap Study, 2005; 6) Timeline for ISRU Capability Implementation; 7) Lunar ISRU Implementation Approach; 8) ISRU Technical-to-Mission Capability Roadmap; 9) ISRU Resources & Products of Interest; and 10) Challenging Seals Requirements for ISRU.

Stochastic Optimization For Water Resources Allocation

NASA Astrophysics Data System (ADS)

Yamout, G.; Hatfield, K.

2003-12-01

For more than 40 years, water resources allocation problems have been addressed using deterministic mathematical optimization. When data uncertainties exist, these methods could lead to solutions that are sub-optimal or even infeasible. While optimization models have been proposed for water resources decision-making under uncertainty, no attempts have been made to address the uncertainties in water allocation problems in an integrated approach. This paper presents an Integrated Dynamic, Multi-stage, Feedback-controlled, Linear, Stochastic, and Distributed parameter optimization approach to solve a problem of water resources allocation. It attempts to capture (1) the conflict caused by competing objectives, (2) environmental degradation produced by resource consumption, and finally (3) the uncertainty and risk generated by the inherently random nature of state and decision parameters involved in such a problem. A theoretical system is defined throughout its different elements. These elements consisting mainly of water resource components and end-users are described in terms of quantity, quality, and present and future associated risks and uncertainties. Models are identified, modified, and interfaced together to constitute an integrated water allocation optimization framework. This effort is a novel approach to confront the water allocation optimization problem while accounting for uncertainties associated with all its elements; thus resulting in a solution that correctly reflects the physical problem in hand.

The use of an integrated variable fuzzy sets in water resources management

NASA Astrophysics Data System (ADS)

Qiu, Qingtai; Liu, Jia; Li, Chuanzhe; Yu, Xinzhe; Wang, Yang

2018-06-01

Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

Sensitivity Analysis and Optimization of the Nuclear Fuel Cycle: A Systematic Approach

NASA Astrophysics Data System (ADS)

Passerini, Stefano

For decades, nuclear energy development was based on the expectation that recycling of the fissionable materials in the used fuel from today's light water reactors into advanced (fast) reactors would be implemented as soon as technically feasible in order to extend the nuclear fuel resources. More recently, arguments have been made for deployment of fast reactors in order to reduce the amount of higher actinides, hence the longevity of radioactivity, in the materials destined to a geologic repository. The cost of the fast reactors, together with concerns about the proliferation of the technology of extraction of plutonium from used LWR fuel as well as the large investments in construction of reprocessing facilities have been the basis for arguments to defer the introduction of recycling technologies in many countries including the US. In this thesis, the impacts of alternative reactor technologies on the fuel cycle are assessed. Additionally, metrics to characterize the fuel cycles and systematic approaches to using them to optimize the fuel cycle are presented. The fuel cycle options of the 2010 MIT fuel cycle study are re-examined in light of the expected slower rate of growth in nuclear energy today, using the CAFCA (Code for Advanced Fuel Cycle Analysis). The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycle options available in the future. The options include limited recycling in L WRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. Additional fuel cycle scenarios presented for the first time in this work assume the deployment of innovative recycling reactor technologies such as the Reduced Moderation Boiling Water Reactors and Uranium-235 initiated Fast Reactors. A sensitivity study focused on system and technology parameters of interest has been conducted to test the robustness of the conclusions presented in the MIT Fuel Cycle Study. These conclusions are found to still hold, even when considering alternative technologies and different sets of simulation assumptions. Additionally, a first of a kind optimization scheme for the nuclear fuel cycle analysis is proposed and the applications of such an optimization are discussed. Optimization metrics of interest for different stakeholders in the fuel cycle (economics, fuel resource utilization, high level waste, transuranics/proliferation management, and environmental impact) are utilized for two different optimization techniques: a linear one and a stochastic one. Stakeholder elicitation provided sets of relative weights for the identified metrics appropriate to each stakeholder group, which were then successfully used to arrive at optimum fuel cycle configurations for recycling technologies. The stochastic optimization tool, based on a genetic algorithm, was used to identify non-inferior solutions according to Pareto's dominance approach to optimization. The main tradeoff for fuel cycle optimization was found to be between economics and most of the other identified metrics. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Saile, Lynn; Freire de Carvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2011-01-01

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Time-aware service-classified spectrum defragmentation algorithm for flex-grid optical networks

NASA Astrophysics Data System (ADS)

Qiu, Yang; Xu, Jing

2018-01-01

By employing sophisticated routing and spectrum assignment (RSA) algorithms together with a finer spectrum granularity (namely frequency slot) in resource allocation procedures, flex-grid optical networks can accommodate diverse kinds of services with high spectrum-allocation flexibility and resource-utilization efficiency. However, the continuity and the contiguity constraints in spectrum allocation procedures may always induce some isolated, small-sized, and unoccupied spectral blocks (known as spectrum fragments) in flex-grid optical networks. Although these spectrum fragments are left unoccupied, they can hardly be utilized by the subsequent service requests directly because of their spectral characteristics and the constraints in spectrum allocation. In this way, the existence of spectrum fragments may exhaust the available spectrum resources for a coming service request and thus worsens the networking performance. Therefore, many reactive defragmentation algorithms have been proposed to handle the fragmented spectrum resources via re-optimizing the routing paths and the spectrum resources for the existing services. But the routing-path and the spectrum-resource re-optimization in reactive defragmentation algorithms may possibly disrupt the traffic of the existing services and require extra components. By comparison, some proactive defragmentation algorithms (e.g. fragmentation-aware algorithms) were proposed to suppress spectrum fragments from their generation instead of handling the fragmented spectrum resources. Although these proactive defragmentation algorithms induced no traffic disruption and required no extra components, they always left the generated spectrum fragments unhandled, which greatly affected their efficiency in spectrum defragmentation. In this paper, by comprehensively considering the characteristics of both the reactive and the proactive defragmentation algorithms, we proposed a time-aware service-classified (TASC) spectrum defragmentation algorithm, which simultaneously employed proactive and reactive mechanisms in suppressing spectrum fragments with the awareness of services' types and their duration times. By dividing the spectrum resources into several flexible groups according to services' types and limiting both the spectrum allocation and the spectrum re-tuning for a certain service inside one specific spectrum group according to its type, the proposed TASC defragmentation algorithm cannot only suppress spectrum fragments from generation inside each spectrum group, but also handle the fragments generated between two adjacent groups. In this way, the proposed TASC algorithm gains higher efficiency in suppressing spectrum fragments than both the reactive and the proactive defragmentation algorithms. Additionally, as the generation of spectrum fragments is retrained between spectrum groups and the defragmentation procedure is limited inside each spectrum group, the induced traffic disruption for the existing services can be possibly reduced. Besides, the proposed TASC defragmentation algorithm always re-tunes the spectrum resources of the service with the maximum duration time first in spectrum defragmentation procedure, which can further reduce spectrum fragments because of the fact that the services with longer duration times always have higher possibility in inducing spectrum fragments than the services with shorter duration times. The simulation results show that the proposed TASC defragmentation algorithm can significantly reduce the number of the generated spectrum fragments while improving the service blocking performance.

The Conservation and Protection: The Development and Utilization of Human Resources.

ERIC Educational Resources Information Center

Lippitt, Ronald

The three dimensions of the quality of the environment for human resource development are discussed as issues of opportunity versus deprivation, issues of growth inducing versus growth destroying interventions, and issues of utilization versus non-utilization of human resources. Both pathology and potential are illustrated by descriptions of our…

18 CFR 2.78 - Utilization and conservation of natural resources-natural gas.

Code of Federal Regulations, 2011 CFR

2011-04-01

... conservation of natural resources-natural gas. 2.78 Section 2.78 Conservation of Power and Water Resources... INTERPRETATIONS Statements of General Policy and Interpretations Under the Natural Gas Act § 2.78 Utilization and conservation of natural resources—natural gas. (a)(1) The national interests in the development and utilization...

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

NASA Technical Reports Server (NTRS)

Rutishauser, David

2006-01-01

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

The association of optimism and perceived discrimination with health care utilization in adults with sickle cell disease.

PubMed

Stanton, Michael V; Jonassaint, Charles R; Bartholomew, Frederick B; Edwards, Christopher; Richman, Laura; DeCastro, Laura; Williams, Redford

2010-11-01

We evaluated the effect of perceived discrimination, optimism, and their interaction on health care utilization among African American adults with sickle cell disease (SCD). Measures of optimism and perceived discrimination were obtained in 49 African American SCD patients. Multiple regression analyses controlling for sex and age tested effects of optimism and perceived discrimination on the number of emergency department visits (ED) and number and duration of hospitalizations over the past year. A perceived discrimination-optimism interaction was associated with number of emergency departments visits (b = .29, p = .052), number of hospitalizations (b = .36, p = .019), and duration of hospitalizations (b = .30, p = .045) such that those with high perceived discrimination/high optimism had the greatest health care utilization. African American SCD patients with high perceived discrimination/high optimism had greater health care utilization than patients who reported either low perceived discrimination or low optimism. This study suggests that patient personality and coping styles should be considered when evaluating the effects of stress on SCD-related outcomes.

Reading the Tea Leaves: How Utilities in the West Are Managing Carbon Regulatory Risk in their Resource Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barbose, Galen; Wiser, Ryan; Phadke, Amol

2008-02-01

The long economic lifetime and development lead-time of many electric infrastructure investments requires that utility resource planning consider potential costs and risks over a lengthy time horizon. One long-term -- and potentially far-reaching -- risk currently facing the electricity industry is the uncertain cost of future carbon dioxide (CO2) regulations. Recognizing the importance of this issue, many utilities (sometimes spurred by state regulatory requirements) are beginning to actively assess carbon regulatory risk within their resource planning processes, and to evaluate options for mitigating that risk. However, given the relatively recent emergence of this issue and the rapidly changing political landscape,more » methods and assumptions used to analyze carbon regulatory risk, and the impact of this analysis on the selection of a preferred resource portfolio, vary considerably across utilities. In this study, we examine the treatment of carbon regulatory risk in utility resource planning, through a comparison of the most-recent resource plans filed by fifteen investor-owned and publicly-owned utilities in the Western U.S. Together, these utilities account for approximately 60percent of retail electricity sales in the West, and cover nine of eleven Western states. This report has two related elements. First, we compare and assess utilities' approaches to addressing key analytical issues that arise when considering the risk of future carbon regulations. Second, we summarize the composition and carbon intensity of the preferred resource portfolios selected by these fifteen utilities and compare them to potential CO2 emission benchmark levels.« less

Study on the Water Resource Sustainable Utilization Evaluation Index System in Jiangsu Coast Reclamation Region

NASA Astrophysics Data System (ADS)

Ren, L.

2016-12-01

As a comprehensive system, there are many subsystems such as water resource subsystem, social subsystem, economic subsystem and ecological subsystem in water resource sustainable utilization system. In this paper, an evaluation system including three levels is set up according to the metric demands of sustainable water resource utilization in Jiangsu coast reclamation region, namely the target level, the rule level, and the index level. Considering the large number of the indexes, the analytic hierarchy process is used to determine the weights of all these subsystems in the total goal of water sustainable utilization. By analyzing these weights, the attributes of water resource itself is found to be the most important aspect for the evaluation of sustainable utilization in Jiangsu coast reclamation region, and the second important aspect is the situation of the eco-environment.

Pricing Resources in LTE Networks through Multiobjective Optimization

PubMed Central

Lai, Yung-Liang; Jiang, Jehn-Ruey

2014-01-01

The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid “user churn,” which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution. PMID:24526889

Pricing resources in LTE networks through multiobjective optimization.

PubMed

Lai, Yung-Liang; Jiang, Jehn-Ruey

2014-01-01

The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid "user churn," which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.

Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control

NASA Astrophysics Data System (ADS)

Maringanti, Chetan; Chaubey, Indrajeet; Popp, Jennie

2009-06-01

Best management practices (BMPs) are effective in reducing the transport of agricultural nonpoint source pollutants to receiving water bodies. However, selection of BMPs for placement in a watershed requires optimization of the available resources to obtain maximum possible pollution reduction. In this study, an optimization methodology is developed to select and place BMPs in a watershed to provide solutions that are both economically and ecologically effective. This novel approach develops and utilizes a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The BMP tool replaces the dynamic linkage of the distributed parameter watershed model during optimization and therefore reduces the computation time considerably. Total pollutant load from the watershed, and net cost increase from the baseline, were the two objective functions minimized during the optimization process. The optimization model, consisting of a multiobjective genetic algorithm (NSGA-II) in combination with a watershed simulation tool (Soil Water and Assessment Tool (SWAT)), was developed and tested for nonpoint source pollution control in the L'Anguille River watershed located in eastern Arkansas. The optimized solutions provided a trade-off between the two objective functions for sediment, phosphorus, and nitrogen reduction. The results indicated that buffer strips were very effective in controlling the nonpoint source pollutants from leaving the croplands. The optimized BMP plans resulted in potential reductions of 33%, 32%, and 13% in sediment, phosphorus, and nitrogen loads, respectively, from the watershed.

The Earth Phenomena Observing System: Intelligent Autonomy for Satellite Operations

NASA Technical Reports Server (NTRS)

Ricard, Michael; Abramson, Mark; Carter, David; Kolitz, Stephan

2003-01-01

Earth monitoring systems of the future may include large numbers of inexpensive small satellites, tasked in a coordinated fashion to observe both long term and transient targets. For best performance, a tool which helps operators optimally assign targets to satellites will be required. We present the design of algorithms developed for real-time optimized autonomous planning of large numbers of small single-sensor Earth observation satellites. The algorithms will reduce requirements on the human operators of such a system of satellites, ensure good utilization of system resources, and provide the capability to dynamically respond to temporal terrestrial phenomena. Our initial real-time system model consists of approximately 100 satellites and large number of points of interest on Earth (e.g., hurricanes, volcanoes, and forest fires) with the objective to maximize the total science value of observations over time. Several options for calculating the science value of observations include the following: 1) total observation time, 2) number of observations, and the 3) quality (a function of e.g., sensor type, range, slant angle) of the observations. An integrated approach using integer programming, optimization and astrodynamics is used to calculate optimized observation and sensor tasking plans.

Streamflow variability and optimal capacity of run-of-river hydropower plants

NASA Astrophysics Data System (ADS)

Basso, S.; Botter, G.

2012-10-01

The identification of the capacity of a run-of-river plant which allows for the optimal utilization of the available water resources is a challenging task, mainly because of the inherent temporal variability of river flows. This paper proposes an analytical framework to describe the energy production and the economic profitability of small run-of-river power plants on the basis of the underlying streamflow regime. We provide analytical expressions for the capacity which maximize the produced energy as a function of the underlying flow duration curve and minimum environmental flow requirements downstream of the plant intake. Similar analytical expressions are derived for the capacity which maximize the economic return deriving from construction and operation of a new plant. The analytical approach is applied to a minihydro plant recently proposed in a small Alpine catchment in northeastern Italy, evidencing the potential of the method as a flexible and simple design tool for practical application. The analytical model provides useful insight on the major hydrologic and economic controls (e.g., streamflow variability, energy price, costs) on the optimal plant capacity and helps in identifying policy strategies to reduce the current gap between the economic and energy optimizations of run-of-river plants.

Using game theory for perceptual tuned rate control algorithm in video coding

NASA Astrophysics Data System (ADS)

Luo, Jiancong; Ahmad, Ishfaq

2005-03-01

This paper proposes a game theoretical rate control technique for video compression. Using a cooperative gaming approach, which has been utilized in several branches of natural and social sciences because of its enormous potential for solving constrained optimization problems, we propose a dual-level scheme to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks. At the frame level, the algorithm allocates target bits to frames based on their coding complexity. At the macroblock level, the algorithm distributes bits to macroblocks by defining a bargaining game. Macroblocks play cooperatively to compete for shares of resources (bits) to optimize their quantization scales while considering the Human Visual System"s perceptual property. Since the whole frame is an entity perceived by viewers, macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint. The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution. Another advantage is that it allows multi-objective optimization with multiple decision makers (macroblocks). The simulation results testify the algorithm"s ability to achieve accurate bit rate with good perceptual quality, and to maintain a stable buffer level.

Resource Optimization Scheme for Multimedia-Enabled Wireless Mesh Networks

PubMed Central

Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md. Jalil; Suh, Doug Young

2014-01-01

Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment. PMID:25111241

Resource optimization scheme for multimedia-enabled wireless mesh networks.

PubMed

Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md Jalil; Suh, Doug Young

2014-08-08

Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment.

Enhanced recovery pathways optimize health outcomes and resource utilization: a meta-analysis of randomized controlled trials in colorectal surgery.

PubMed

Adamina, Michel; Kehlet, Henrik; Tomlinson, George A; Senagore, Anthony J; Delaney, Conor P

2011-06-01

Health care systems provide care to increasingly complex and elderly patients. Colorectal surgery is a prime example, with high volumes of major procedures, significant morbidity, prolonged hospital stays, and unplanned readmissions. This situation is exacerbated by an exponential rise in costs that threatens the stability of health care systems. Enhanced recovery pathways (ERP) have been proposed as a means to reduce morbidity and improve effectiveness of care. We have reviewed the evidence supporting the implementation of ERP in clinical practice. Medline, Embase, and the Cochrane library were searched for randomized, controlled trials comparing ERP with traditional care in colorectal surgery. Systematic reviews and papers on ERP based on data published in major surgical and anesthesiology journals were critically reviewed by international contributors, experienced in the development and implementation of ERP. A random-effect Bayesian meta-analysis was performed, including 6 randomized, controlled trials totalizing 452 patients. For patients adhering to ERP, length of stay decreased by 2.5 days (95% credible interval [CrI] -3.92 to -1.11), whereas 30-day morbidity was halved (relative risk, 0.52; 95% CrI, 0.36-0.73) and readmission was not increased (relative risk, 0.59; 95% CrI, 0.14-1.43) when compared with patients undergoing traditional care. Adherence to ERP achieves a reproducible improvement in the quality of care by enabling standardization of health care processes. Thus, while accelerating recovery and safely reducing hospital stay, ERPs optimize utilization of health care resources. ERPs can and should be routinely used in care after colorectal and other major gastrointestinal procedures. Copyright © 2011 Mosby, Inc. All rights reserved.

SIMRAND I- SIMULATION OF RESEARCH AND DEVELOPMENT PROJECTS

NASA Technical Reports Server (NTRS)

Miles, R. F.

1994-01-01

The Simulation of Research and Development Projects program (SIMRAND) aids in the optimal allocation of R&D resources needed to achieve project goals. SIMRAND models the system subsets or project tasks as various network paths to a final goal. Each path is described in terms of task variables such as cost per hour, cost per unit, availability of resources, etc. Uncertainty is incorporated by treating task variables as probabilistic random variables. SIMRAND calculates the measure of preference for each alternative network. The networks yielding the highest utility function (or certainty equivalence) are then ranked as the optimal network paths. SIMRAND has been used in several economic potential studies at NASA's Jet Propulsion Laboratory involving solar dish power systems and photovoltaic array construction. However, any project having tasks which can be reduced to equations and related by measures of preference can be modeled. SIMRAND analysis consists of three phases: reduction, simulation, and evaluation. In the reduction phase, analytical techniques from probability theory and simulation techniques are used to reduce the complexity of the alternative networks. In the simulation phase, a Monte Carlo simulation is used to derive statistics on the variables of interest for each alternative network path. In the evaluation phase, the simulation statistics are compared and the networks are ranked in preference by a selected decision rule. The user must supply project subsystems in terms of equations based on variables (for example, parallel and series assembly line tasks in terms of number of items, cost factors, time limits, etc). The associated cumulative distribution functions and utility functions for each variable must also be provided (allowable upper and lower limits, group decision factors, etc). SIMRAND is written in Microsoft FORTRAN 77 for batch execution and has been implemented on an IBM PC series computer operating under DOS.

A market-based optimization approach to sensor and resource management

NASA Astrophysics Data System (ADS)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

Simultaneous personnel and vehicle shift scheduling in the waste management sector.

PubMed

Ghiani, Gianpaolo; Guerriero, Emanuela; Manni, Andrea; Manni, Emanuele; Potenza, Agostino

2013-07-01

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Substance abuse intensive outpatient treatment: does program graduation matter?

PubMed

Wallace, Amy E; Weeks, William B

2004-07-01

Program graduation, even after controlling for length of stay, may predict for improved outcomes in some substance abuse treatment settings. We investigated the role of program graduation by comparing social outcomes and inpatient utilization the years before and after treatment among graduates and dropouts of a Veterans Administration substance abuse intensive outpatient program. At enrollment, graduates and dropouts were similar in all spheres measured. Patients who completed the treatment program used significantly fewer psychiatric inpatient bed days of care the year after they completed the program, both in comparison to their own prior use and in comparison to program dropouts. Graduates were more likely to be abstinent and less likely to fully relapse or be incarcerated at 6-month followup. Further research is needed to discern optimal treatment length-that which maximizes both length of stay and completion rates, while optimizing use of limited treatment resources.

Minimal-delay traffic grooming for WDM star networks

NASA Astrophysics Data System (ADS)

Choi, Hongsik; Garg, Nikhil; Choi, Hyeong-Ah

2003-10-01

All-optical networks face the challenge of reducing slower opto-electronic conversions by managing assignment of traffic streams to wavelengths in an intelligent manner, while at the same time utilizing bandwidth resources to the maximum. This challenge becomes harder in networks closer to the end users that have insufficient data to saturate single wavelengths as well as traffic streams outnumbering the usable wavelengths, resulting in traffic grooming which requires costly traffic analysis at access nodes. We study the problem of traffic grooming that reduces the need to analyze traffic, for a class of network architecture most used by Metropolitan Area Networks; the star network. The problem being NP-complete, we provide an efficient twice-optimal-bound greedy heuristic for the same, that can be used to intelligently groom traffic at the LANs to reduce latency at the access nodes. Simulation results show that our greedy heuristic achieves a near-optimal solution.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

[Utilization suitability of forest resources in typical forest zone of Changbai Mountains].

PubMed

Hao, Zhanqing; Yu, Deyong; Xiong, Zaiping; Ye, Ji

2004-10-01

Conservation of natural forest does not simply equal to no logging. The Northeast China Forest Region has a logging quota of mature forest as part of natural forest conservation project. How to determine the logging spots rationally and scientifically is very important. Recent scientific theories of forest resources management advocate that the utilization of forest resources should stick to the principle of sustaining use, and pay attention to the ecological function of forest resources. According to the logging standards, RS and GIS techniques can be used to detect the precise location of forest resources and obtain information of forest areas and types, and thus, provide more rational and scientific support for space choice about future utilization of forest resources. In this paper, the Lushuihe Forest Bureau was selected as a typical case in Changbai Mountains Forest Region to assess the utilization conditions of forest resources, and some advices on spatial choice for future management of forest resources in the study area were offered.

The utilization of poisons information resources in Australasia.

PubMed

Fountain, J S; Reith, D M; Holt, A

2014-02-01

To identify poisons information resources most commonly utilized by Australasian Emergency Department staff, and examine attitudes regarding the benefits and user experience of the electronic products used. A survey tool was mailed to six Emergency Departments each in New Zealand and Australia to be answered by medical and nursing staff. Eighty six (71.7%) responses were received from the 120 survey forms sent: 70 (81%) responders were medical staff, the remainder nursing. Electronic resources were the most accessed poisons information resource in New Zealand; Australians preferring discussion with a colleague; Poisons Information Centers were the least utilized resource in both countries. With regard to electronic resources, further differences were recognized between countries in: ease of access, ease of use, quality of information and quantity of information, with New Zealand better in all four themes. New Zealand ED staff favored electronic poisons information resources while Australians preferred discussion with a colleague. That Poisons Information Centers were the least utilized resource was surprising. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

Database resources of the National Center for Biotechnology Information

PubMed Central

Sayers, Eric W.; Barrett, Tanya; Benson, Dennis A.; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M.; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D.; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A.; Wagner, Lukas; Wang, Yanli; Wilbur, W. John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:22140104

Database resources of the National Center for Biotechnology Information

PubMed Central

2013-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page. PMID:23193264

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene; Ye, Jian

2009-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Mathematical Model and Artificial Intelligent Techniques Applied to a Milk Industry through DSM

NASA Astrophysics Data System (ADS)

Babu, P. Ravi; Divya, V. P. Sree

2011-08-01

The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. The main objective of this chapter is to discuss about the Peak load management and overcome the problems associated with it in processing industries such as Milk industry with the help of DSM techniques. The chapter presents a generalized mathematical model for minimizing the total operating cost of the industry subject to the constraints. The work presented in this chapter also deals with the results of application of Neural Network, Fuzzy Logic and Demand Side Management (DSM) techniques applied to a medium scale milk industrial consumer in India to achieve the improvement in load factor, reduction in Maximum Demand (MD) and also the consumer gets saving in the energy bill.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Komar, Peter; Kessler, Eric; Bishof, Michael; Jiang, Liang; Sorensen, Anders; Ye, Jun; Lukin, Mikhail

2014-05-01

Shared timing information constitutes a key resource for positioning and navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System (GPS). By combining precision metrology and quantum networks, we propose here a quantum, cooperative protocol for the operation of a network consisting of geographically remote optical atomic clocks. Using non-local entangled states, we demonstrate an optimal utilization of the global network resources, and show that such a network can be operated near the fundamental limit set by quantum theory yielding an ultra-precise clock signal. Furthermore, the internal structure of the network, combined with basic techniques from quantum communication, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy. See also: Komar et al. arXiv:1310.6045 (2013) and Kessler et al. arXiv:1310.6043 (2013).

Applying reinforcement learning techniques to detect hepatocellular carcinoma under limited screening capacity.

PubMed

Lee, Elliot; Lavieri, Mariel S; Volk, Michael L; Xu, Yongcai

2015-09-01

We investigate the problem faced by a healthcare system wishing to allocate its constrained screening resources across a population at risk for developing a disease. A patient's risk of developing the disease depends on his/her biomedical dynamics. However, knowledge of these dynamics must be learned by the system over time. Three classes of reinforcement learning policies are designed to address this problem of simultaneously gathering and utilizing information across multiple patients. We investigate a case study based upon the screening for Hepatocellular Carcinoma (HCC), and optimize each of the three classes of policies using the indifference zone method. A simulation is built to gauge the performance of these policies, and their performance is compared to current practice. We then demonstrate how the benefits of learning-based screening policies differ across various levels of resource scarcity and provide metrics of policy performance.

Optimized exploration resource evaluation using the MDT tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zainun, K.; Trice, M.L.

1995-10-01

This paper discusses exploration cost reduction and improved resource delineation benefits that were realized by use of the MDT (Modular Formation Dynamic Tester) tool to evaluate exploration prospects in the Malay Basin of the South China Sea. Frequently, open hole logs do not clearly define fluid content due to low salinity of the connate water and the effect of shale laminae or bioturbation in the silty, shaley sandstones. Therefore, extensive pressure measurements and fluid sampling are required to define fluid type and contacts. This paper briefly describes the features of the MDT tool which were utilized to reduce rig timemore » usage while providing more representative fluid samples and illustrates usage of these features with field examples. The tool has been used on several exploration wells and a comparison of MDT pressures and samples to results obtained with earlier vintage tools and production tests is also discussed.« less

Simulation platform of LEO satellite communication system based on OPNET

NASA Astrophysics Data System (ADS)

Zhang, Yu; Zhang, Yong; Li, Xiaozhuo; Wang, Chuqiao; Li, Haihao

2018-02-01

For the purpose of verifying communication protocol in the low earth orbit (LEO) satellite communication system, an Optimized Network Engineering Tool (OPNET) based simulation platform is built. Using the three-layer modeling mechanism, the network model, the node model and the process model of the satellite communication system are built respectively from top to bottom, and the protocol will be implemented by finite state machine and Proto-C language. According to satellite orbit parameters, orbit files are generated via Satellite Tool Kit (STK) and imported into OPNET, and the satellite nodes move along their orbits. The simulation platform adopts time-slot-driven mode, divides simulation time into continuous time slots, and allocates slot number for each time slot. A resource allocation strategy is simulated on this platform, and the simulation results such as resource utilization rate, system throughput and packet delay are analyzed, which indicate that this simulation platform has outstanding versatility.

On the Water-Food Nexus: an Optimization Approach for Water and Food Security

NASA Astrophysics Data System (ADS)

Mortada, Sarah; Abou Najm, Majdi; Yassine, Ali; Alameddine, Ibrahim; El-Fadel, Mutasem

2016-04-01

Water and food security is facing increased challenges with population increase, climate and land use change, as well as resource depletion coupled with pollution and unsustainable practices. Coordinated and effective management of limited natural resources have become an imperative to meet these challenges by optimizing the usage of resources under various constraints. In this study, an optimization model is developed for optimal resource allocation towards sustainable water and food security under nutritional, socio-economic, agricultural, environmental, and natural resources constraints. The core objective of this model is to maximize the composite water-food security status by recommending an optimal water and agricultural strategy. The model balances between the healthy nutritional demand side and the constrained supply side while considering the supply chain in between. It equally ensures that the population achieves recommended nutritional guidelines and population food-preferences by quantifying an optimum agricultural and water policy through transforming optimum food demands into optimum cropping policy given the water and land footprints of each crop or agricultural product. Through this process, water and food security are optimized considering factors that include crop-food transformation (food processing), water footprints, crop yields, climate, blue and green water resources, irrigation efficiency, arable land resources, soil texture, and economic policies. The model performance regarding agricultural practices and sustainable food and water security was successfully tested and verified both at a hypothetical and pilot scale levels.