Demonstration of a vectorial optical field generator with adaptive close loop control.

PubMed

Chen, Jian; Kong, Lingjiang; Zhan, Qiwen

2017-12-01

We experimentally demonstrate a vectorial optical field generator (VOF-Gen) with an adaptive close loop control. The close loop control capability is illustrated with the calibration of polarization modulation of the system. To calibrate the polarization ratio modulation, we generate 45° linearly polarized beam and make it propagate through a linear analyzer whose transmission axis is orthogonal to the incident beam. For the retardation calibration, circularly polarized beam is employed and a circular polarization analyzer with the opposite chirality is placed in front of the CCD as the detector. In both cases, the close loop control automatically changes the value of the corresponding calibration parameters in the pre-set ranges to generate the phase patterns applied to the spatial light modulators and records the intensity distribution of the output beam by the CCD camera. The optimized calibration parameters are determined corresponding to the minimum total intensity in each case. Several typical kinds of vectorial optical beams are created with and without the obtained calibration parameters, and the full Stokes parameter measurements are carried out to quantitatively analyze the polarization distribution of the generated beams. The comparisons among these results clearly show that the obtained calibration parameters could remarkably improve the accuracy of the polarization modulation of the VOF-Gen, especially for generating elliptically polarized beam with large ellipticity, indicating the significance of the presented close loop in enhancing the performance of the VOF-Gen.

Distributed Coordination of Energy Storage with Distributed Generators

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

Yang, Tao; Wu, Di; Stoorvogel, Antonie A.

2016-07-18

With a growing emphasis on energy efficiency and system flexibility, a great effort has been made recently in developing distributed energy resources (DER), including distributed generators and energy storage systems. This paper first formulates an optimal coordination problem considering constraints at both system and device levels, including power balance constraint, generator output limits, storage energy and power capacity and charging/discharging efficiencies. An algorithm is then proposed to dynamically and automatically coordinate DERs in a distributed manner. With the proposed algorithm, the agent at each DER only maintains a local incremental cost and updates it through information exchange with a fewmore » neighbors, without relying on any central decision maker. Simulation results are used to illustrate and validate the proposed algorithm.« less

Voltage management of distribution networks with high penetration of distributed photovoltaic generation sources

NASA Astrophysics Data System (ADS)

Alyami, Saeed

Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage

Voltage regulation in distribution networks with distributed generation

NASA Astrophysics Data System (ADS)

Blažič, B.; Uljanić, B.; Papič, I.

2012-11-01

The paper deals with the topic of voltage regulation in distribution networks with relatively high distributed energy resources (DER) penetration. The problem of voltage rise is described and different options for voltage regulation are given. The influence of DER on voltage profile and the effectiveness of the investigated solutions are evaluated by means of simulation in DIgSILENT. The simulated network is an actual distribution network in Slovenia with a relatively high penetration of distributed generation. Recommendations for voltage control in networks with DER penetration are given at the end.

Distributed Generation to Support Development-Focused Climate Action

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

Cox, Sadie; Gagnon, Pieter; Stout, Sherry

2016-09-01

This paper explores the role of distributed generation, with a high renewable energy contribution, in supporting low emission climate-resilient development. The paper presents potential impacts on development (via energy access), greenhouse gas emission mitigation, and climate resilience directly associated with distributed generation, as well as specific actions that may enhance or increase the likelihood of climate and development benefits. This paper also seeks to provide practical and timely insights to support distributed generation policymaking and planning within the context of common climate and development goals as the distributed generation landscape rapidly evolves globally. Country-specific distributed generation policy and program examples,more » as well as analytical tools that can inform efforts internationally, are also highlighted throughout the paper.« less

Mechanisms generating kappa distributions in plasmas

NASA Astrophysics Data System (ADS)

Livadiotis, Georgios

2017-10-01

Kappa distributions have become increasingly widespread across plasma physics. Publication records reveal an exponential growth of papers relevant to kappa distributions. However, the vast majority of publications refer to statistical fits and applications of these distributions in plasmas. Up to date, there is no systematic analysis on the origin of kappa distributions, that is, the mechanisms that can generate kappa distributions in plasmas. The general scheme that characterizes these mechanisms is composed of two parts: (1) the generation of local correlations among particles, and (2) the thermalization, that is, the stabilization of the particle system into stationary states described by kappa distributions or combinations thereof. Several mechanisms are known in the literature, each characterized by a specific relationship between the plasma properties. These relationships serve as conditions that need to be fulfilled for the corresponding mechanisms to be applied in the plasma. Using these relationships, we identify three mechanisms that generate kappa distributions in the solar wind plasma: (i) Debye shielding, (ii) magnetic field binding, and (iii) thermal fluctuations, each one prevailing in different scales of the solar wind plasma and magnetic field properties. The work was supported in part by the project NNX17AB74G of NASA's HGI Program.

Investigation into the efficacy of generating synthetic pathological oscillations for domain adaptation

NASA Astrophysics Data System (ADS)

Lewis, Rory; Ellenberger, James; Williams, Colton; White, Andrew M.

2013-11-01

In the ongoing investigation of integrating Knowledge Discovery in Databases (KDD) into neuroscience, we present a paper that facilitates overcoming the two challenges preventing this integration. Pathological oscillations found in the human brain are difficult to evaluate because 1) there is often no time to learn and train off of the same distribution in the fatally sick, and 2) sinusoidal signals found in the human brain are complex and transient in nature requiring large data sets to work with which are costly and often very expensive or impossible to acquire. Overcoming these challenges in today's neuro-intensive-care unit (ICU) requires insurmountable resources. For these reasons, optimizing KDD for pathological oscillations so machine learning systems can predict neuropathological states would be of immense value. Domain adaptation, which allows a way of predicting on a separate set of data than the training data, can theoretically overcome the first challenge. However, the challenge of acquiring large data sets that show whether domain adaptation is a good candidate to test in a live neuro ICU remains a challenge. To solve this conundrum, we present a methodology for generating synthesized neuropathological oscillations for domain adaptation.

Distributed Generation of Electricity and its Environmental Impacts

EPA Pesticide Factsheets

Distributed generation refers to technologies that generate electricity at or near where it will be used. Learn about how distributed energy generation can support the delivery of clean, reliable power to additional customers.

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

PubMed Central

Kopp, Michael; Hermisson, Joachim

2009-01-01

We consider a population that adapts to a gradually changing environment. Our aim is to describe how ecological and genetic factors combine to determine the genetic basis of adaptation. Specifically, we consider the evolution of a polygenic trait that is under stabilizing selection with a moving optimum. The ecological dynamics are defined by the strength of selection, \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}{\\mathrm{\\tilde {{\\sigma}}}}\\end{equation*}\\end{document}, and the speed of the optimum, \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}\\tilde {{\\upsilon}}\\end{equation*}\\end{document}; the key genetic parameters are the mutation rate Θ and the variance of the effects of new mutations, ω. We develop analytical approximations within an “adaptive-walk” framework and describe how selection acts as a sieve that transforms a given distribution of new mutations into the distribution of adaptive substitutions. Our analytical results are complemented by individual-based simulations. We find that (i) the ecological dynamics have a strong effect on the distribution of adaptive substitutions and their impact depends largely on a single composite measure \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin

Data Transparency | Distributed Generation Interconnection Collaborative |

Science.gov Websites

quality and availability are increasingly vital for reducing the costs of distributed generation completion in certain areas, increasing accountability for utility application processing. As distributed PV NREL, HECO, TSRG Improving Data Transparency for the Distributed PV Interconnection Process: Emergent

Distributed Generation Market Demand Model | NREL

Science.gov Websites

Demand Model The Distributed Generation Market Demand (dGen) model simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the dGen model can help develop deployment forecasts for distributed resources, including sensitivity to

Adaptive distributed outlier detection for WSNs.

PubMed

De Paola, Alessandra; Gaglio, Salvatore; Lo Re, Giuseppe; Milazzo, Fabrizio; Ortolani, Marco

2015-05-01

The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication complexity, and also considering externally imposed constraints on such conflicting goals. The performed experimental evaluation showed that our approach is able to improve the considered metrics for latency and energy consumption, with limited impact on classification accuracy.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Anisotropic adaptive mesh generation in two dimensions for CFD

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

Borouchaki, H.; Castro-Diaz, M.J.; George, P.L.

This paper describes the extension of the classical Delaunay method in the case where anisotropic meshes are required such as in CFD when the modelized physic is strongly directional. The way in which such a mesh generation method can be incorporated in an adaptative loop of CFD as well as the case of multicriterium adaptation are discussed. Several concrete application examples are provided to illustrate the capabilities of the proposed method.

A collection of Australian Drosophila datasets on climate adaptation and species distributions.

PubMed

Hangartner, Sandra B; Hoffmann, Ary A; Smith, Ailie; Griffin, Philippa C

2015-11-24

The Australian Drosophila Ecology and Evolution Resource (ADEER) collates Australian datasets on drosophilid flies, which are aimed at investigating questions around climate adaptation, species distribution limits and population genetics. Australian drosophilid species are diverse in climatic tolerance, geographic distribution and behaviour. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Whereas some species show adaptability to climate changes through genetic and plastic changes, other species have limited adaptive capacity. This knowledge has been used to identify traits and genetic polymorphisms involved in climate change adaptation and build predictive models of responses to climate change. ADEER brings together 103 datasets from 39 studies published between 1982-2013 in a single online resource. All datasets can be downloaded freely in full, along with maps and other visualisations. These historical datasets are preserved for future studies, which will be especially useful for assessing climate-related changes over time.

Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots

PubMed Central

Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated movements, (2) distributed (at each leg) recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and (3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps, leg damage adaptations, as well as climbing over high obstacles. Furthermore, we demonstrate that the newly developed recurrent network based approach to online forward models outperforms the adaptive neuron forward models

Adaptive Practice: Next Generation Evidence-Based Practice in Digital Environments.

PubMed

Kennedy, Margaret Ann

2016-01-01

Evidence-based practice in nursing is considered foundational to safe, competent care. To date, rigid traditional perceptions of what constitutes 'evidence' have constrained the recognition and use of practice-based evidence and the exploitation of novel forms of evidence from data rich environments. Advancements such as the conceptualization of clinical intelligence, the prevalence of increasingly sophisticated digital health information systems, and the advancement of the Big Data phenomenon have converged to generate a new contemporary context. In today's dynamic data-rich environments, clinicians have new sources of valid evidence, and need a new paradigm supporting clinical practice that is adaptive to information generated by diverse electronic sources. This opinion paper presents adaptive practice as the next generation of evidence-based practice in contemporary evidence-rich environments and provides recommendations for the next phase of evolution.

Adaptive Phase Delay Generator

NASA Technical Reports Server (NTRS)

Greer, Lawrence

2013-01-01

There are several experimental setups involving rotating machinery that require some form of synchronization. The adaptive phase delay generator (APDG) the Bencic-1000 is a flexible instrument that allows the user to generate pulses synchronized to the rising edge of a tachometer signal from any piece of rotating machinery. These synchronized pulses can vary by the delay angle, pulse width, number of pulses per period, number of skipped pulses, and total number of pulses. Due to the design of the pulse generator, any and all of these parameters can be changed independently, yielding an unparalleled level of versatility. There are two user interfaces to the APDG. The first is a LabVIEW program that has the advantage of displaying all of the pulse parameters and input signal data within one neatly organized window on the PC monitor. Furthermore, the LabVIEW interface plots the rpm of the two input signal channels in real time. The second user interface is a handheld portable device that goes anywhere a computer is not accessible. It consists of a liquid-crystal display and keypad, which enable the user to control the unit by scrolling through a host of command menus and parameter listings. The APDG combines all of the desired synchronization control into one unit. The experimenter can adjust the delay, pulse width, pulse count, number of skipped pulses, and produce a specified number of pulses per revolution. Each of these parameters can be changed independently, providing an unparalleled level of versatility when synchronizing hardware to a host of rotating machinery. The APDG allows experimenters to set up quickly and generate a host of synchronizing configurations using a simple user interface, which hopefully leads to faster results.

Application Processing | Distributed Generation Interconnection

Science.gov Websites

delivering swift customer service. The rapid rise of distributed generation (DG) PV interconnection speed processing, reduce paperwork, and improve customer service. Webinars and publications are

Fast adaptive composite grid methods on distributed parallel architectures

NASA Technical Reports Server (NTRS)

Lemke, Max; Quinlan, Daniel

1992-01-01

The fast adaptive composite (FAC) grid method is compared with the adaptive composite method (AFAC) under variety of conditions including vectorization and parallelization. Results are given for distributed memory multiprocessor architectures (SUPRENUM, Intel iPSC/2 and iPSC/860). It is shown that the good performance of AFAC and its superiority over FAC in a parallel environment is a property of the algorithm and not dependent on peculiarities of any machine.

Adaptive Quadrature Detection for Multicarrier Continuous-Variable Quantum Key Distribution

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

2015-03-01

We propose the adaptive quadrature detection for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD scheme uses Gaussian subcarrier continuous variables for the information conveying and Gaussian sub-channels for the transmission. The proposed multicarrier detection scheme dynamically adapts to the sub-channel conditions using a corresponding statistics which is provided by our sophisticated sub-channel estimation procedure. The sub-channel estimation phase determines the transmittance coefficients of the sub-channels, which information are used further in the adaptive quadrature decoding process. We define the technique called subcarrier spreading to estimate the transmittance conditions of the sub-channels with a theoretical error-minimum in the presence of a Gaussian noise. We introduce the terms of single and collective adaptive quadrature detection. We also extend the results for a multiuser multicarrier CVQKD scenario. We prove the achievable error probabilities, the signal-to-noise ratios, and quantify the attributes of the framework. The adaptive detection scheme allows to utilize the extra resources of multicarrier CVQKD and to maximize the amount of transmittable information. This work was partially supported by the GOP-1.1.1-11-2012-0092 (Secure quantum key distribution between two units on optical fiber network) project sponsored by the EU and European Structural Fund, and by the COST Action MP1006.

Effects of Distributed Generation on Overcurrent Relay Coordination and an Adaptive Protection Scheme

NASA Astrophysics Data System (ADS)

Ilik, Semih C.; Arsoy, Aysen B.

2017-07-01

Integration of distributed generation (DG) such as renewable energy sources to electrical network becomes more prevalent in recent years. Grid connection of DG has effects on load flow directions, voltage profile, short circuit power and especially protection selectivity. Applying traditional overcurrent protection scheme is inconvenient when system reliability and sustainability are considered. If a fault happens in DG connected network, short circuit contribution of DG, creates additional branch element feeding the fault current; compels to consider directional overcurrent (OC) protection scheme. Protection coordination might get lost for changing working conditions when DG sources are connected. Directional overcurrent relay parameters are determined for downstream and upstream relays when different combinations of DG connected singular or plural, on radial test system. With the help of proposed flow chart, relay parameters are updated and coordination between relays kept sustained for different working conditions in DigSILENT PowerFactory program.

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

Distribution, habitat and adaptability of the genus Tapirus.

PubMed

García, Manolo J; Medici, Emília Patrícia; Naranjo, Eduardo J; Novarino, Wilson; Leonardo, Raquel S

2012-12-01

In this manuscript, as a starting point, the ancient and current distribution of the genus Tapirus are summarized, from its origins, apparently in Europe, to current ranges. Subsequently, original and current tapir habitats are described, as well as changes in ancient habitats. As the manuscript goes on, we examine the ways in which tapir species interact with their habitats and the main aspects of habitat use, spatial ecology and adaptability. Having reviewed the historic and current distribution of tapirs, as well as their use and selection of habitats, we introduce the concept of adaptability, considering that some of the tapir physiological characteristics and behavioral strategies can reduce the negative impact of habitat alteration and climate change. Finally, we provide recommendations for future research priorities. The conservation community is still missing important pieces of information for the effective conservation of tapirs and their remaining habitats in Central and South America and Southeast Asia. Reconstructing how tapir species reached their current distribution ranges, interpreting how they interact with their habitats and gathering information regarding the strategies they use to cope with habitat changes will increase our understanding about these animals and contribute to the development of conservation strategies. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov Websites

Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next -Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution Infrastructure This project develops innovative, real-time optimization and control methods for next-generation

Subscribe to DGIC Updates | Distributed Generation Interconnection

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Distributed Generation Interconnection Collaborative. Subscribe Please provide and submit the following information to subscribe. The mailing list addresses are never sold, rented, distributed, or disclosed in any

Self-adaptive demodulation for polarization extinction ratio in distributed polarization coupling.

PubMed

Zhang, Hongxia; Ren, Yaguang; Liu, Tiegen; Jia, Dagong; Zhang, Yimo

2013-06-20

A self-adaptive method for distributed polarization extinction ratio (PER) demodulation is demonstrated. It is characterized by dynamic PER threshold coupling intensity (TCI) and nonuniform PER iteration step length (ISL). Based on the preset PER calculation accuracy and original distribution coupling intensity, TCI and ISL can be made self-adaptive to determine contributing coupling points inside the polarizing devices. Distributed PER is calculated by accumulating those coupling points automatically and selectively. Two different kinds of polarization-maintaining fibers are tested, and PERs are obtained after merely 3-5 iterations using the proposed method. Comparison experiments with Thorlabs commercial instrument are also conducted, and results show high consistency. In addition, the optimum preset PER calculation accuracy of 0.05 dB is obtained through many repeated experiments.

Fast Reliability Assessing Method for Distribution Network with Distributed Renewable Energy Generation

NASA Astrophysics Data System (ADS)

Chen, Fan; Huang, Shaoxiong; Ding, Jinjin; Ding, Jinjin; Gao, Bo; Xie, Yuguang; Wang, Xiaoming

2018-01-01

This paper proposes a fast reliability assessing method for distribution grid with distributed renewable energy generation. First, the Weibull distribution and the Beta distribution are used to describe the probability distribution characteristics of wind speed and solar irradiance respectively, and the models of wind farm, solar park and local load are built for reliability assessment. Then based on power system production cost simulation probability discretization and linearization power flow, a optimal power flow objected with minimum cost of conventional power generation is to be resolved. Thus a reliability assessment for distribution grid is implemented fast and accurately. The Loss Of Load Probability (LOLP) and Expected Energy Not Supplied (EENS) are selected as the reliability index, a simulation for IEEE RBTS BUS6 system in MATLAB indicates that the fast reliability assessing method calculates the reliability index much faster with the accuracy ensured when compared with Monte Carlo method.

Adaptive Metropolis Sampling with Product Distributions

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Lee, Chiu Fan

2005-01-01

The Metropolis-Hastings (MH) algorithm is a way to sample a provided target distribution pi(z). It works by repeatedly sampling a separate proposal distribution T(x,x') to generate a random walk {x(t)}. We consider a modification of the MH algorithm in which T is dynamically updated during the walk. The update at time t uses the {x(t' less than t)} to estimate the product distribution that has the least Kullback-Leibler distance to pi. That estimate is the information-theoretically optimal mean-field approximation to pi. We demonstrate through computer experiments that our algorithm produces samples that are superior to those of the conventional MH algorithm.

Adaptive spatial filtering for daytime satellite quantum key distribution

NASA Astrophysics Data System (ADS)

Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.

2014-11-01

The rate of secure key generation (SKG) in quantum key distribution (QKD) is adversely affected by optical noise and loss in the quantum channel. In a free-space atmospheric channel, the scattering of sunlight into the channel can lead to quantum bit error ratios (QBERs) sufficiently large to preclude SKG. Furthermore, atmospheric turbulence limits the degree to which spatial filtering can reduce sky noise without introducing signal losses. A system simulation quantifies the potential benefit of tracking and higher-order adaptive optics (AO) technologies to SKG rates in a daytime satellite engagement scenario. The simulations are performed assuming propagation from a low-Earth orbit (LEO) satellite to a terrestrial receiver that includes an AO system comprised of a Shack-Hartmann wave-front sensor (SHWFS) and a continuous-face-sheet deformable mirror (DM). The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain waveoptics hardware emulator. Secure key generation rates are then calculated for the decoy state QKD protocol as a function of the receiver field of view (FOV) for various pointing angles. The results show that at FOVs smaller than previously considered, AO technologies can enhance SKG rates in daylight and even enable SKG where it would otherwise be prohibited as a consequence of either background optical noise or signal loss due to turbulence effects.

Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations

PubMed Central

Good, Benjamin H.; Rouzine, Igor M.; Balick, Daniel J.; Hallatschek, Oskar; Desai, Michael M.

2012-01-01

When large asexual populations adapt, competition between simultaneously segregating mutations slows the rate of adaptation and restricts the set of mutations that eventually fix. This phenomenon of interference arises from competition between mutations of different strengths as well as competition between mutations that arise on different fitness backgrounds. Previous work has explored each of these effects in isolation, but the way they combine to influence the dynamics of adaptation remains largely unknown. Here, we describe a theoretical model to treat both aspects of interference in large populations. We calculate the rate of adaptation and the distribution of fixed mutational effects accumulated by the population. We focus particular attention on the case when the effects of beneficial mutations are exponentially distributed, as well as on a more general class of exponential-like distributions. In both cases, we show that the rate of adaptation and the influence of genetic background on the fixation of new mutants is equivalent to an effective model with a single selection coefficient and rescaled mutation rate, and we explicitly calculate these effective parameters. We find that the effective selection coefficient exactly coincides with the most common fixed mutational effect. This equivalence leads to an intuitive picture of the relative importance of different types of interference effects, which can shift dramatically as a function of the population size, mutation rate, and the underlying distribution of fitness effects. PMID:22371564

Distribution of tubulin, kinesin, and dynein in light- and dark-adapted octopus retinas.

PubMed

Martinez, J M; Elfarissi, H; De Velasco, B; Ochoa, G H; Miller, A M; Clark, Y M; Matsumoto, B; Robles, L J

2000-01-01

Cephalopod retinas exhibit several responses to light and dark adaptation, including rhabdom size changes, photopigment movements, and pigment granule migration. Light- and dark-directed rearrangements of microfilament and microtubule cytoskeletal transport pathways could drive these changes. Recently, we localized actin-binding proteins in light-/dark-adapted octopus rhabdoms and suggested that actin cytoskeletal rearrangements bring about the formation and degradation of rhabdomere microvilli subsets. To determine if the microtubule cytoskeleton and associated motor proteins control the other light/dark changes, we used immunoblotting and immunocytochemical procedures to map the distribution of tubulin, kinesin, and dynein in dorsal and ventral halves of light- and dark-adapted octopus retinas. Immunoblots detected alpha- and beta-tubulin, dynein intermediate chain, and kinesin heavy chain in extracts of whole retinas. Epifluorescence and confocal microscopy showed that the tubulin proteins were distributed throughout the retina with more immunoreactivity in retinas exposed to light. Kinesin localization was heavy in the pigment layer of light- and dark-adapted ventral retinas but was less prominent in the dorsal region. Dynein distribution also varied in dorsal and ventral retinas with more immunoreactivity in light- and dark-adapted ventral retinas and confocal microscopy emphasized the granular nature of this labeling. We suggest that light may regulate the distribution of microtubule cytoskeletal proteins in the octopus retina and that position, dorsal versus ventral, also influences the distribution of motor proteins. The microtubule cytoskeleton is most likely involved in pigment granule migration in the light and dark and with the movement of transport vesicles from the photoreceptor inner segments to the rhabdoms.

Business Models and Regulation | Distributed Generation Interconnection

Science.gov Websites

@nrel.gov 303-384-4641 Utilities and regulators are responding to the growth of distributed generation with new business models and approaches. The growing role of distributed resources in the electricity Electric Cooperative, Groton Utilities Distributed Solar for Small Utilities A recording of the webinar is

Adaptive Molecular Evolution for 13,000 Phage Generations

PubMed Central

Wichman, Holly A.; Millstein, Jack; Bull, J. J.

2005-01-01

Bacteriophage φX174 was evolved on a continuous supply of sensitive hosts for 180 days (∼13,000 phage generations). The average rate of nucleotide substitution was nearly 0.2% (11 substitutions)/20 days, and, surprisingly, substitutions accumulated in a clock-like manner throughout the study, except for a low rate during the first 20 days. Rates of silent and missense substitutions varied over time and among genes. Approximately 40% of the 71 missense changes and 25% of the 58 silent changes have been observed in previous adaptations; the rate of parallel substitution was highest in the early phase of the evolution, but 7% of the later changes had evolved in previous studies of much shorter duration. Several lines of evidence suggest that most of the changes were adaptive, even many of the silent substitutions. The sustained, high rate of adaptive evolution for 180 days defies a model of adaptation to a constant environment. We instead suggest that continuing molecular evolution reflects a potentially indefinite arms race, stemming from high levels of co-infection and the resulting conflict among genomes competing within the same cell. PMID:15687276

Competition and Cooperation of Distributed Generation and Power System

NASA Astrophysics Data System (ADS)

Miyake, Masatoshi; Nanahara, Toshiya

Advances in distributed generation technologies together with the deregulation of an electric power industry can lead to a massive introduction of distributed generation. Since most of distributed generation will be interconnected to a power system, coordination and competition between distributed generators and large-scale power sources would be a vital issue in realizing a more desirable energy system in the future. This paper analyzes competitions between electric utilities and cogenerators from the viewpoints of economic and energy efficiency based on the simulation results on an energy system including a cogeneration system. First, we examine best response correspondence of an electric utility and a cogenerator with a noncooperative game approach: we obtain a Nash equilibrium point. Secondly, we examine the optimum strategy that attains the highest social surplus and the highest energy efficiency through global optimization.

Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

Enhancing performance of LCoS-SLM as adaptive optics by using computer-generated holograms modulation software

NASA Astrophysics Data System (ADS)

Tsai, Chun-Wei; Lyu, Bo-Han; Wang, Chen; Hung, Cheng-Chieh

2017-05-01

We have already developed multi-function and easy-to-use modulation software that was based on LabVIEW system. There are mainly four functions in this modulation software, such as computer generated holograms (CGH) generation, CGH reconstruction, image trimming, and special phase distribution. Based on the above development of CGH modulation software, we could enhance the performance of liquid crystal on silicon - spatial light modulator (LCoSSLM) as similar as the diffractive optical element (DOE) and use it on various adaptive optics (AO) applications. Through the development of special phase distribution, we are going to use the LCoS-SLM with CGH modulation software into AO technology, such as optical microscope system. When the LCOS-SLM panel is integrated in an optical microscope system, it could be placed on the illumination path or on the image forming path. However, LCOS-SLM provides a program-controllable liquid crystal array for optical microscope. It dynamically changes the amplitude or phase of light and gives the obvious advantage, "Flexibility", to the system

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive invasive species distribution models: A framework for modeling incipient invasions

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

2015-01-01

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Advanced, Adaptive, Modular, Distributed, Generic Universal FADEC Framework for Intelligent Propulsion Control Systems (Preprint)

DTIC Science & Technology

2007-09-01

AFRL-RZ-WP-TP-2008-2044 ADVANCED, ADAPTIVE, MODULAR, DISTRIBUTED, GENERIC UNIVERSAL FADEC FRAMEWORK FOR INTELLIGENT PROPULSION CONTROL...GRANT NUMBER 4. TITLE AND SUBTITLE ADVANCED, ADAPTIVE, MODULAR, DISTRIBUTED, GENERIC UNIVERSAL FADEC FRAMEWORK FOR INTELLIGENT PROPULSION... FADEC is unique and expensive to develop, produce, maintain, and upgrade for its particular application. Each FADEC is a centralized system, with a

A model-based exploration of the role of pattern generating circuits during locomotor adaptation.

PubMed

Marjaninejad, Ali; Finley, James M

2016-08-01

In this study, we used a model-based approach to explore the potential contributions of central pattern generating circuits (CPGs) during adaptation to external perturbations during locomotion. We constructed a neuromechanical modeled of locomotion using a reduced-phase CPG controller and an inverted pendulum mechanical model. Two different forms of locomotor adaptation were examined in this study: split-belt treadmill adaptation and adaptation to a unilateral, elastic force field. For each simulation, we first examined the effects of phase resetting and varying the model's initial conditions on the resulting adaptation. After evaluating the effect of phase resetting on the adaptation of step length symmetry, we examined the extent to which the results from these simple models could explain previous experimental observations. We found that adaptation of step length symmetry during split-belt treadmill walking could be reproduced using our model, but this model failed to replicate patterns of adaptation observed in response to force field perturbations. Given that spinal animal models can adapt to both of these types of perturbations, our findings suggest that there may be distinct features of pattern generating circuits that mediate each form of adaptation.

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects

PubMed Central

2016-01-01

Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments. PMID:26990188

MEAT: An Authoring Tool for Generating Adaptable Learning Resources

ERIC Educational Resources Information Center

Kuo, Yen-Hung; Huang, Yueh-Min

2009-01-01

Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

Distributed database kriging for adaptive sampling (D²KAS)

DOE PAGES

Roehm, Dominic; Pavel, Robert S.; Barros, Kipton; ...

2015-03-18

We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method. A finite-volume scheme integrates the macro-scale conservation laws for elastodynamics, which are closed by momentum and energy fluxes evaluated at the micro-scale. In the original approach, molecular dynamics (MD) simulations are launched for every macro-scale volume element. Our adaptive sampling scheme replaces a large fraction of costly micro-scale MD simulations with fast table lookup and prediction. The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our predictionmore » scheme. For the latter we use kriging, which estimates an unknown value and its uncertainty (error) at a specific location in parameter space by using weighted averages of the neighboring points. We find that our adaptive scheme significantly improves simulation performance by a factor of 2.5 to 25, while retaining high accuracy for various choices of the algorithm parameters.« less

Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

NASA Astrophysics Data System (ADS)

Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia

PubMed Central

Vojtkó, András; Farkas, Tünde; Szabó, Anna; Havadtői, Krisztina; Vojtkó, Anna E.; Tölgyesi, Csaba; Cseh, Viktória; Erdős, László; Maák, István Elek; Keppel, Gunnar

2017-01-01

Background and aims Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems. Methods We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses. Key Results Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes). Conclusions There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming. PMID:28025290

Polarization-multiplexed plasmonic phase generation with distributed nanoslits.

PubMed

Lee, Seung-Yeol; Kim, Kyuho; Lee, Gun-Yeal; Lee, Byoungho

2015-06-15

Methods for multiplexing surface plasmon polaritons (SPPs) have been attracting much attention due to their potentials for plasmonic integrated systems, plasmonic holography, and optical tweezing. Here, using closely-distanced distributed nanoslits, we propose a method for generating polarization-multiplexed SPP phase profiles which can be applied for implementing general SPP phase distributions. Two independent types of SPP phase generation mechanisms - polarization-independent and polarization-reversible ones - are combined to generate fully arbitrary phase profiles for each optical handedness. As a simple verification of the proposed scheme, we experimentally demonstrate that the location of plasmonic focus can be arbitrary designed, and switched by the change of optical handedness.

Next Generation Distributed Computing for Cancer Research

PubMed Central

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing. PMID:25983539

Next generation distributed computing for cancer research.

PubMed

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing.

Distributed state-space generation of discrete-state stochastic models

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Gluckman, Joshua; Nicol, David

1995-01-01

High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.

Generation of distributed W-states over long distances

NASA Astrophysics Data System (ADS)

Li, Yi

2017-08-01

Ultra-secure quantum communication between distant locations requires distributed entangled states between nodes. Various methodologies have been proposed to tackle this technological challenge, of which the so-called DLCZ protocol is the most promising and widely adopted scheme. This paper aims to extend this well-known protocol to a multi-node setting where the entangled W-state is generated between nodes over long distances. The generation of multipartite W-states is the foundation of quantum networks, paving the way for quantum communication and distributed quantum computation.

Logs Analysis of Adapted Pedagogical Scenarios Generated by a Simulation Serious Game Architecture

ERIC Educational Resources Information Center

Callies, Sophie; Gravel, Mathieu; Beaudry, Eric; Basque, Josianne

2017-01-01

This paper presents an architecture designed for simulation serious games, which automatically generates game-based scenarios adapted to learner's learning progression. We present three central modules of the architecture: (1) the learner model, (2) the adaptation module and (3) the logs module. The learner model estimates the progression of the…

Numerical modeling of landslide-generated tsunami using adaptive unstructured meshes

NASA Astrophysics Data System (ADS)

Wilson, Cian; Collins, Gareth; Desousa Costa, Patrick; Piggott, Matthew

2010-05-01

Landslides impacting into or occurring under water generate waves, which can have devastating environmental consequences. Depending on the characteristics of the landslide the waves can have significant amplitude and potentially propagate over large distances. Linear models of classical earthquake-generated tsunamis cannot reproduce the highly nonlinear generation mechanisms required to accurately predict the consequences of landslide-generated tsunamis. Also, laboratory-scale experimental investigation is limited to simple geometries and short time-scales before wave reflections contaminate the data. Computational fluid dynamics models based on the nonlinear Navier-Stokes equations can simulate landslide-tsunami generation at realistic scales. However, traditional chessboard-like structured meshes introduce superfluous resolution and hence the computing power required for such a simulation can be prohibitively high, especially in three dimensions. Unstructured meshes allow the grid spacing to vary rapidly from high resolution in the vicinity of small scale features to much coarser, lower resolution in other areas. Combining this variable resolution with dynamic mesh adaptivity allows such high resolution zones to follow features like the interface between the landslide and the water whilst minimising the computational costs. Unstructured meshes are also better suited to representing complex geometries and bathymetries allowing more realistic domains to be simulated. Modelling multiple materials, like water, air and a landslide, on an unstructured adaptive mesh poses significant numerical challenges. Novel methods of interface preservation must be considered and coupled to a flow model in such a way that ensures conservation of the different materials. Furthermore this conservation property must be maintained during successive stages of mesh optimisation and interpolation. In this paper we validate a new multi-material adaptive unstructured fluid dynamics model

Network-Oriented Approach to Distributed Generation Planning

NASA Astrophysics Data System (ADS)

Kochukov, O.; Mutule, A.

2017-06-01

The main objective of the paper is to present an innovative complex approach to distributed generation planning and show the advantages over existing methods. The approach will be most suitable for DNOs and authorities and has specific calculation targets to support the decision-making process. The method can be used for complex distribution networks with different arrangement and legal base.

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia.

PubMed

Bátori, Zoltán; Vojtkó, András; Farkas, Tünde; Szabó, Anna; Havadtői, Krisztina; Vojtkó, Anna E; Tölgyesi, Csaba; Cseh, Viktória; Erdős, László; Maák, István Elek; Keppel, Gunnar

2017-01-01

Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems. We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses. Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes). There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming. © The Author 2016. Published by Oxford University Press on behalf of

Comprehensive evaluation of impacts of distributed generation integration in distribution network

NASA Astrophysics Data System (ADS)

Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu

2018-04-01

All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.

Bioinspired adaptive gradient refractive index distribution lens

NASA Astrophysics Data System (ADS)

Yin, Kezhen; Lai, Chuan-Yar; Wang, Jia; Ji, Shanzuo; Aldridge, James; Feng, Jingxing; Olah, Andrew; Baer, Eric; Ponting, Michael

2018-02-01

Inspired by the soft, deformable human eye lens, a synthetic polymer gradient refractive index distribution (GRIN) lens with an adaptive geometry and focal power has been demonstrated via multilayer coextrusion and thermoforming of nanolayered elastomeric polymer films. A set of 30 polymer nanolayered films comprised of two thermoplastic polyurethanes having a refractive index difference of 0.05 were coextruded via forced-assembly technique. The set of 30 nanolayered polymer films exhibited transmission near 90% with each film varying in refractive index by 0.0017. An adaptive GRIN lens was fabricated from a laminated stack of the variable refractive index films with a 0.05 spherical GRIN. This lens was subsequently deformed by mechanical ring compression of the lens. Variation in the optical properties of the deformable GRIN lens was determined, including 20% variation in focal length and reduced spherical aberration. These properties were measured and compared to simulated results by placido-cone topography and ANSYS methods. The demonstration of a solid-state, dynamic focal length, GRIN lens with improved aberration correction was discussed relative to the potential future use in implantable devices.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

Blood Vessel Adaptation with Fluctuations in Capillary Flow Distribution

PubMed Central

Hu, Dan; Cai, David; Rangan, Aaditya V.

2012-01-01

Throughout the life of animals and human beings, blood vessel systems are continuously adapting their structures – the diameter of vessel lumina, the thickness of vessel walls, and the number of micro-vessels – to meet the changing metabolic demand of the tissue. The competition between an ever decreasing tendency of luminal diameters and an increasing stimulus from the wall shear stress plays a key role in the adaptation of luminal diameters. However, it has been shown in previous studies that the adaptation dynamics based only on these two effects is unstable. In this work, we propose a minimal adaptation model of vessel luminal diameters, in which we take into account the effects of metabolic flow regulation in addition to wall shear stresses and the decreasing tendency of luminal diameters. In particular, we study the role, in the adaptation process, of fluctuations in capillary flow distribution which is an important means of metabolic flow regulation. The fluctuation in the flow of a capillary group is idealized as a switch between two states, i.e., an open-state and a close-state. Using this model, we show that the adaptation of blood vessel system driven by wall shear stress can be efficiently stabilized when the open time ratio responds sensitively to capillary flows. As micro-vessel rarefaction is observed in our simulations with a uniformly decreased open time ratio of capillary flows, our results point to a possible origin of micro-vessel rarefaction, which is believed to induce hypertension. PMID:23029014

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Model-Driven Test Generation of Distributed Systems

NASA Technical Reports Server (NTRS)

Easwaran, Arvind; Hall, Brendan; Schweiker, Kevin

2012-01-01

This report describes a novel test generation technique for distributed systems. Utilizing formal models and formal verification tools, spe cifically the Symbolic Analysis Laboratory (SAL) tool-suite from SRI, we present techniques to generate concurrent test vectors for distrib uted systems. These are initially explored within an informal test validation context and later extended to achieve full MC/DC coverage of the TTEthernet protocol operating within a system-centric context.

Adaptive microfluidic gradient generator for quantitative chemotaxis experiments.

PubMed

Anielski, Alexander; Pfannes, Eva K B; Beta, Carsten

2017-03-01

Chemotactic motion in a chemical gradient is an essential cellular function that controls many processes in the living world. For a better understanding and more detailed modelling of the underlying mechanisms of chemotaxis, quantitative investigations in controlled environments are needed. We developed a setup that allows us to separately address the dependencies of the chemotactic motion on the average background concentration and on the gradient steepness of the chemoattractant. In particular, both the background concentration and the gradient steepness can be kept constant at the position of the cell while it moves along in the gradient direction. This is achieved by generating a well-defined chemoattractant gradient using flow photolysis. In this approach, the chemoattractant is released by a light-induced reaction from a caged precursor in a microfluidic flow chamber upstream of the cell. The flow photolysis approach is combined with an automated real-time cell tracker that determines changes in the cell position and triggers movement of the microscope stage such that the cell motion is compensated and the cell remains at the same position in the gradient profile. The gradient profile can be either determined experimentally using a caged fluorescent dye or may be alternatively determined by numerical solutions of the corresponding physical model. To demonstrate the function of this adaptive microfluidic gradient generator, we compare the chemotactic motion of Dictyostelium discoideum cells in a static gradient and in a gradient that adapts to the position of the moving cell.

Generating Adaptive Behaviour within a Memory-Prediction Framework

PubMed Central

Rawlinson, David; Kowadlo, Gideon

2012-01-01

The Memory-Prediction Framework (MPF) and its Hierarchical-Temporal Memory implementation (HTM) have been widely applied to unsupervised learning problems, for both classification and prediction. To date, there has been no attempt to incorporate MPF/HTM in reinforcement learning or other adaptive systems; that is, to use knowledge embodied within the hierarchy to control a system, or to generate behaviour for an agent. This problem is interesting because the human neocortex is believed to play a vital role in the generation of behaviour, and the MPF is a model of the human neocortex. We propose some simple and biologically-plausible enhancements to the Memory-Prediction Framework. These cause it to explore and interact with an external world, while trying to maximize a continuous, time-varying reward function. All behaviour is generated and controlled within the MPF hierarchy. The hierarchy develops from a random initial configuration by interaction with the world and reinforcement learning only. Among other demonstrations, we show that a 2-node hierarchy can learn to successfully play “rocks, paper, scissors” against a predictable opponent. PMID:22272231

Distributed query plan generation using multiobjective genetic algorithm.

PubMed

Panicker, Shina; Kumar, T V Vijay

2014-01-01

A distributed query processing strategy, which is a key performance determinant in accessing distributed databases, aims to minimize the total query processing cost. One way to achieve this is by generating efficient distributed query plans that involve fewer sites for processing a query. In the case of distributed relational databases, the number of possible query plans increases exponentially with respect to the number of relations accessed by the query and the number of sites where these relations reside. Consequently, computing optimal distributed query plans becomes a complex problem. This distributed query plan generation (DQPG) problem has already been addressed using single objective genetic algorithm, where the objective is to minimize the total query processing cost comprising the local processing cost (LPC) and the site-to-site communication cost (CC). In this paper, this DQPG problem is formulated and solved as a biobjective optimization problem with the two objectives being minimize total LPC and minimize total CC. These objectives are simultaneously optimized using a multiobjective genetic algorithm NSGA-II. Experimental comparison of the proposed NSGA-II based DQPG algorithm with the single objective genetic algorithm shows that the former performs comparatively better and converges quickly towards optimal solutions for an observed crossover and mutation probability.

Distributed Query Plan Generation Using Multiobjective Genetic Algorithm

PubMed Central

Panicker, Shina; Vijay Kumar, T. V.

2014-01-01

A distributed query processing strategy, which is a key performance determinant in accessing distributed databases, aims to minimize the total query processing cost. One way to achieve this is by generating efficient distributed query plans that involve fewer sites for processing a query. In the case of distributed relational databases, the number of possible query plans increases exponentially with respect to the number of relations accessed by the query and the number of sites where these relations reside. Consequently, computing optimal distributed query plans becomes a complex problem. This distributed query plan generation (DQPG) problem has already been addressed using single objective genetic algorithm, where the objective is to minimize the total query processing cost comprising the local processing cost (LPC) and the site-to-site communication cost (CC). In this paper, this DQPG problem is formulated and solved as a biobjective optimization problem with the two objectives being minimize total LPC and minimize total CC. These objectives are simultaneously optimized using a multiobjective genetic algorithm NSGA-II. Experimental comparison of the proposed NSGA-II based DQPG algorithm with the single objective genetic algorithm shows that the former performs comparatively better and converges quickly towards optimal solutions for an observed crossover and mutation probability. PMID:24963513

Adaptive template generation for amyloid PET using a deep learning approach.

PubMed

Kang, Seung Kwan; Seo, Seongho; Shin, Seong A; Byun, Min Soo; Lee, Dong Young; Kim, Yu Kyeong; Lee, Dong Soo; Lee, Jae Sung

2018-05-11

Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. In this study, we applied deep neural networks to generate individually adaptive PET templates for robust and accurate SN of amyloid PET without using matched 3D MR images. Using 681 pairs of simultaneously acquired 11 C-PIB PET and T1-weighted 3D MRI scans of AD, MCI, and cognitively normal subjects, we trained and tested two deep neural networks [convolutional auto-encoder (CAE) and generative adversarial network (GAN)] that produce adaptive best PET templates. More specifically, the networks were trained using 685,100 pieces of augmented data generated by rotating 527 randomly selected datasets and validated using 154 datasets. The input to the supervised neural networks was the 3D PET volume in native space and the label was the spatially normalized 3D PET image using the transformation parameters obtained from MRI-based SN. The proposed deep learning approach significantly enhanced the quantitative accuracy of MRI-less amyloid PET assessment by reducing the SN error observed when an average amyloid PET template is used. Given an input image, the trained deep neural networks rapidly provide individually adaptive 3D PET templates without any discontinuity between the slices (in 0.02 s). As the proposed method does not require 3D MRI for the SN of PET images, it has great potential for use in routine analysis of amyloid PET images in clinical practice and research. © 2018 Wiley Periodicals, Inc.

Cross-cultural adaptation of the Portuguese version of the Patient-Generated Subjective Global Assessment.

PubMed

Duarte Bonini Campos, J A; Dias do Prado, C

2012-01-01

The cross-cultural adaptation of the Patient-Generated Subjective Global Assessment is important so it can be used with confidence in Portuguese language. To perform a cross-cultural adaptation of the Portuguese version of the Patient-Generated Subjective Global Assessment and to estimate its intrarater reliability. This is a validation study. Face Validity was classified by 17 health professionals and 10 Portuguese language specialists. Idiomatic, semantic, cultural and conceptual equivalences were analyzed. The questionnaire was completed by 20 patients of the Amaral Carvalho Hospital (Jaú, São Paulo, Brazil) in order to verify the Comprehension Index of each item. Therefore, 27 committee members classified each item into "essential", "useful, but not essential" and "not necessary", in order to calculate the Content Validity Ratio. After, this version of the questionnaire was applied twice to 62 patients of the hospital cited above. The intrarater reliability of the nutritional status analyzed by Patient-Generated Subjective Global Assessment was estimated by Kappa statistics. The Portuguese version of the Patient-Generated Subjective Global Assessment presented 10 incomprehensible expressions. The items "a year ago weight" and "dry mouth symptom" presented the lowest Content Validity Ratio. Substantial intrarater reliability (k = 0.78, p = 0.001) was observed. The cross-cultural adaptation of the Portuguese version of the Patient-Generated Subjective Global Assessment became simple and understandable for Brazilian patients. Thus, this version of the Patient-Generated Subjective Global Assessment was considered a valid and a reliable method.

System and method for islanding detection and prevention in distributed generation

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

Bhowmik, Shibashis; Mazhari, Iman; Parkhideh, Babak

Various examples are directed to systems and methods for detecting an islanding condition at an inverter configured to couple a distributed generation system to an electrical grid network. A controller may determine a command frequency and a command frequency variation. The controller may determine that the command frequency variation indicates a potential islanding condition and send to the inverter an instruction to disconnect the distributed generation system from the electrical grid network. When the distributed generation system is disconnected from the electrical grid network, the controller may determine whether the grid network is valid.

Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

2010-09-01

This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

DOE PAGES

Li, Weixuan; Lin, Guang

2015-03-21

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes’ rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle thesemore » challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.« less

An adaptive importance sampling algorithm for Bayesian inversion with multimodal distributions

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

Li, Weixuan; Lin, Guang, E-mail: guanglin@purdue.edu

2015-08-01

Parametric uncertainties are encountered in the simulations of many physical systems, and may be reduced by an inverse modeling procedure that calibrates the simulation results to observations on the real system being simulated. Following Bayes' rule, a general approach for inverse modeling problems is to sample from the posterior distribution of the uncertain model parameters given the observations. However, the large number of repetitive forward simulations required in the sampling process could pose a prohibitive computational burden. This difficulty is particularly challenging when the posterior is multimodal. We present in this paper an adaptive importance sampling algorithm to tackle thesemore » challenges. Two essential ingredients of the algorithm are: 1) a Gaussian mixture (GM) model adaptively constructed as the proposal distribution to approximate the possibly multimodal target posterior, and 2) a mixture of polynomial chaos (PC) expansions, built according to the GM proposal, as a surrogate model to alleviate the computational burden caused by computational-demanding forward model evaluations. In three illustrative examples, the proposed adaptive importance sampling algorithm demonstrates its capabilities of automatically finding a GM proposal with an appropriate number of modes for the specific problem under study, and obtaining a sample accurately and efficiently representing the posterior with limited number of forward simulations.« less

Next generation tools for genomic data generation, distribution, and visualization

PubMed Central

2010-01-01

Background With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data. Results Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser. Conclusions These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq. PMID:20828407

Size distributions of micro-bubbles generated by a pressurized dissolution method

NASA Astrophysics Data System (ADS)

Taya, C.; Maeda, Y.; Hosokawa, S.; Tomiyama, A.; Ito, Y.

2012-03-01

Size of micro-bubbles is widely distributed in the range of one to several hundreds micrometers and depends on generation methods, flow conditions and elapsed times after the bubble generation. Although a size distribution of micro-bubbles should be taken into account to improve accuracy in numerical simulations of flows with micro-bubbles, a variety of the size distribution makes it difficult to introduce the size distribution in the simulations. On the other hand, several models such as the Rosin-Rammler equation and the Nukiyama-Tanazawa equation have been proposed to represent the size distribution of particles or droplets. Applicability of these models to the size distribution of micro-bubbles has not been examined yet. In this study, we therefore measure size distribution of micro-bubbles generated by a pressurized dissolution method by using a phase Doppler anemometry (PDA), and investigate the applicability of the available models to the size distributions of micro-bubbles. Experimental apparatus consists of a pressurized tank in which air is dissolved in liquid under high pressure condition, a decompression nozzle in which micro-bubbles are generated due to pressure reduction, a rectangular duct and an upper tank. Experiments are conducted for several liquid volumetric fluxes in the decompression nozzle. Measurements are carried out at the downstream region of the decompression nozzle and in the upper tank. The experimental results indicate that (1) the Nukiyama-Tanasawa equation well represents the size distribution of micro-bubbles generated by the pressurized dissolution method, whereas the Rosin-Rammler equation fails in the representation, (2) the bubble size distribution of micro-bubbles can be evaluated by using the Nukiyama-Tanasawa equation without individual bubble diameters, when mean bubble diameter and skewness of the bubble distribution are given, and (3) an evaluation method of visibility based on the bubble size distribution and bubble

Optimal Solar PV Arrays Integration for Distributed Generation

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

Omitaomu, Olufemi A; Li, Xueping

2012-01-01

Solar photovoltaic (PV) systems hold great potential for distributed energy generation by installing PV panels on rooftops of residential and commercial buildings. Yet challenges arise along with the variability and non-dispatchability of the PV systems that affect the stability of the grid and the economics of the PV system. This paper investigates the integration of PV arrays for distributed generation applications by identifying a combination of buildings that will maximize solar energy output and minimize system variability. Particularly, we propose mean-variance optimization models to choose suitable rooftops for PV integration based on Markowitz mean-variance portfolio selection model. We further introducemore » quantity and cardinality constraints to result in a mixed integer quadratic programming problem. Case studies based on real data are presented. An efficient frontier is obtained for sample data that allows decision makers to choose a desired solar energy generation level with a comfortable variability tolerance level. Sensitivity analysis is conducted to show the tradeoffs between solar PV energy generation potential and variability.« less

Grid generation and adaptation via Monge-Kantorovich optimization in 2D and 3D

NASA Astrophysics Data System (ADS)

Delzanno, Gian Luca; Chacon, Luis; Finn, John M.

2008-11-01

In a recent paper [1], Monge-Kantorovich (MK) optimization was proposed as a method of grid generation/adaptation in two dimensions (2D). The method is based on the minimization of the L2 norm of grid point displacement, constrained to producing a given positive-definite cell volume distribution (equidistribution constraint). The procedure gives rise to the Monge-Amp'ere (MA) equation: a single, non-linear scalar equation with no free-parameters. The MA equation was solved in Ref. [1] with the Jacobian Free Newton-Krylov technique and several challenging test cases were presented in squared domains in 2D. Here, we extend the work of Ref. [1]. We first formulate the MK approach in physical domains with curved boundary elements and in 3D. We then show the results of applying it to these more general cases. We show that MK optimization produces optimal grids in which the constraint is satisfied numerically to truncation error. [1] G.L. Delzanno, L. Chac'on, J.M. Finn, Y. Chung, G. Lapenta, A new, robust equidistribution method for two-dimensional grid generation, submitted to Journal of Computational Physics (2008).

Situational variations in ethnic identity across immigration generations: Implications for acculturative change and cross-cultural adaptation.

PubMed

Noels, Kimberly A; Clément, Richard

2015-12-01

This study examined whether the acculturation of ethnic identity is first evident in more public situations with greater opportunity for intercultural interaction and eventually penetrates more intimate situations. It also investigated whether situational variations in identity are associated with cross-cultural adaptation. First-generation (G1), second-generation (G2) and mixed-parentage second-generation (G2.5) young adult Canadians (n = 137, n = 169, and n = 91, respectively) completed a questionnaire assessing their heritage and Canadian identities across four situational domains (family, friends, university and community), global heritage identity and cross-cultural adaptation. Consistent with the acculturation penetration hypothesis, the results showed Canadian identity was stronger than heritage identity in public domains, but the converse was true in the family domain; moreover, the difference between the identities in the family domain was attenuated in later generations. Situational variability indicated better adaptation for the G1 cohort, but poorer adaptation for the G2.5 cohort. For the G2 cohort, facets of global identity moderated the relation, such that those with a weaker global identity experienced greater difficulties and hassles with greater identity variability but those with a stronger identity did not. These results are interpreted in light of potential interpersonal issues implied by situational variation for each generation cohort. © 2015 International Union of Psychological Science.

Optimal Output of Distributed Generation Based On Complex Power Increment

NASA Astrophysics Data System (ADS)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Design Flexibility for Uncertain Distributed Generation from Photovoltaics

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

Palmintier, Bryan; Krishnamurthy, Dheepak; Wu, Hongyu

2016-12-12

Uncertainty in the future adoption patterns for distributed energy resources (DERs) introduces a challenge for electric distribution system planning. This paper explores the potential for flexibility in design - also known as real options - to identify design solutions that may never emerge when future DER patterns are treated as deterministic. A test case for storage system design with uncertain distributed generation for solar photovoltaics (DGPV) demonstrates this approach and is used to study sensitivities to a range of techno-economic assumptions.

Real time testing of intelligent relays for synchronous distributed generation islanding detection

NASA Astrophysics Data System (ADS)

Zhuang, Davy

As electric power systems continue to grow to meet ever-increasing energy demand, their security, reliability, and sustainability requirements also become more stringent. The deployment of distributed energy resources (DER), including generation and storage, in conventional passive distribution feeders, gives rise to integration problems involving protection and unintentional islanding. Distributed generators need to be islanded for safety reasons when disconnected or isolated from the main feeder as distributed generator islanding may create hazards to utility and third-party personnel, and possibly damage the distribution system infrastructure, including the distributed generators. This thesis compares several key performance indicators of a newly developed intelligent islanding detection relay, against islanding detection devices currently used by the industry. The intelligent relay employs multivariable analysis and data mining methods to arrive at decision trees that contain both the protection handles and the settings. A test methodology is developed to assess the performance of these intelligent relays on a real time simulation environment using a generic model based on a real-life distribution feeder. The methodology demonstrates the applicability and potential advantages of the intelligent relay, by running a large number of tests, reflecting a multitude of system operating conditions. The testing indicates that the intelligent relay often outperforms frequency, voltage and rate of change of frequency relays currently used for islanding detection, while respecting the islanding detection time constraints imposed by standing distributed generator interconnection guidelines.

Adaptive, Distributed Control of Constrained Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Adaptive grid generation in a patient-specific cerebral aneurysm

NASA Astrophysics Data System (ADS)

Hodis, Simona; Kallmes, David F.; Dragomir-Daescu, Dan

2013-11-01

Adapting grid density to flow behavior provides the advantage of increasing solution accuracy while decreasing the number of grid elements in the simulation domain, therefore reducing the computational time. One method for grid adaptation requires successive refinement of grid density based on observed solution behavior until the numerical errors between successive grids are negligible. However, such an approach is time consuming and it is often neglected by the researchers. We present a technique to calculate the grid size distribution of an adaptive grid for computational fluid dynamics (CFD) simulations in a complex cerebral aneurysm geometry based on the kinematic curvature and torsion calculated from the velocity field. The relationship between the kinematic characteristics of the flow and the element size of the adaptive grid leads to a mathematical equation to calculate the grid size in different regions of the flow. The adaptive grid density is obtained such that it captures the more complex details of the flow with locally smaller grid size, while less complex flow characteristics are calculated on locally larger grid size. The current study shows that kinematic curvature and torsion calculated from the velocity field in a cerebral aneurysm can be used to find the locations of complex flow where the computational grid needs to be refined in order to obtain an accurate solution. We found that the complexity of the flow can be adequately described by velocity and vorticity and the angle between the two vectors. For example, inside the aneurysm bleb, at the bifurcation, and at the major arterial turns the element size in the lumen needs to be less than 10% of the artery radius, while at the boundary layer, the element size should be smaller than 1% of the artery radius, for accurate results within a 0.5% relative approximation error. This technique of quantifying flow complexity and adaptive remeshing has the potential to improve results accuracy and reduce

Effects of payoff functions and preference distributions in an adaptive population

NASA Astrophysics Data System (ADS)

Yang, H. M.; Ting, Y. S.; Wong, K. Y. Michael

2008-03-01

Adaptive populations such as those in financial markets and distributed control can be modeled by the Minority Game. We consider how their dynamics depends on the agents’ initial preferences of strategies, when the agents use linear or quadratic payoff functions to evaluate their strategies. We find that the fluctuations of the population making certain decisions (the volatility) depends on the diversity of the distribution of the initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. In systems with linear payoffs, this results in dynamical transitions from vanishing volatility to a nonvanishing one. For low signal dimensions, the dynamical transitions for the different signals do not take place at the same critical diversity. Rather, a cascade of dynamical transitions takes place when the diversity is reduced. In contrast, no phase transitions are found in systems with the quadratic payoffs. Instead, a basin boundary of attraction separates two groups of samples in the space of the agents’ decisions. Initial states inside this boundary converge to small volatility, while those outside diverge to a large one. Furthermore, when the preference distribution becomes more polarized, the dynamics becomes more erratic. All the above results are supported by good agreement between simulations and theory.

Distributed Pedagogical Leadership and Generative Dialogue in Educational Nodes

ERIC Educational Resources Information Center

Jappinen, Aini-Kristiina; Sarja, Anneli

2012-01-01

The article presents practices of distributed pedagogical leadership and generative dialogue as a tool with which management and personnel can better operate in the increasingly turbulent world of education. Distributed pedagogical leadership includes common characteristics of a professional learning community when the educational actors…

Granular Flow Graph, Adaptive Rule Generation and Tracking.

PubMed

Pal, Sankar Kumar; Chakraborty, Debarati Bhunia

2017-12-01

A new method of adaptive rule generation in granular computing framework is described based on rough rule base and granular flow graph, and applied for video tracking. In the process, several new concepts and operations are introduced, and methodologies formulated with superior performance. The flow graph enables in defining an intelligent technique for rule base adaptation where its characteristics in mapping the relevance of attributes and rules in decision-making system are exploited. Two new features, namely, expected flow graph and mutual dependency between flow graphs are defined to make the flow graph applicable in the tasks of both training and validation. All these techniques are performed in neighborhood granular level. A way of forming spatio-temporal 3-D granules of arbitrary shape and size is introduced. The rough flow graph-based adaptive granular rule-based system, thus produced for unsupervised video tracking, is capable of handling the uncertainties and incompleteness in frames, able to overcome the incompleteness in information that arises without initial manual interactions and in providing superior performance and gaining in computation time. The cases of partial overlapping and detecting the unpredictable changes are handled efficiently. It is shown that the neighborhood granulation provides a balanced tradeoff between speed and accuracy as compared to pixel level computation. The quantitative indices used for evaluating the performance of tracking do not require any information on ground truth as in the other methods. Superiority of the algorithm to nonadaptive and other recent ones is demonstrated extensively.

Bas-relief generation using adaptive histogram equalization.

PubMed

Sun, Xianfang; Rosin, Paul L; Martin, Ralph R; Langbein, Frank C

2009-01-01

An algorithm is presented to automatically generate bas-reliefs based on adaptive histogram equalization (AHE), starting from an input height field. A mesh model may alternatively be provided, in which case a height field is first created via orthogonal or perspective projection. The height field is regularly gridded and treated as an image, enabling a modified AHE method to be used to generate a bas-relief with a user-chosen height range. We modify the original image-contrast-enhancement AHE method to use gradient weights also to enhance the shape features of the bas-relief. To effectively compress the height field, we limit the height-dependent scaling factors used to compute relative height variations in the output from height variations in the input; this prevents any height differences from having too great effect. Results of AHE over different neighborhood sizes are averaged to preserve information at different scales in the resulting bas-relief. Compared to previous approaches, the proposed algorithm is simple and yet largely preserves original shape features. Experiments show that our results are, in general, comparable to and in some cases better than the best previously published methods.

A concurrent distributed system for aircraft tactical decision generation

NASA Technical Reports Server (NTRS)

Mcmanus, John W.

1990-01-01

A research program investigating the use of AI techniques to aid in the development of a tactical decision generator (TDG) for within visual range (WVR) air combat engagements is discussed. The application of AI programming and problem-solving methods in the development and implementation of a concurrent version of the computerized logic for air-to-air warfare simulations (CLAWS) program, a second-generation TDG, is presented. Concurrent computing environments and programming approaches are discussed, and the design and performance of prototype concurrent TDG system (Cube CLAWS) are presented. It is concluded that the Cube CLAWS has provided a useful testbed to evaluate the development of a distributed blackboard system. The project has shown that the complexity of developing specialized software on a distributed, message-passing architecture such as the Hypercube is not overwhelming, and that reasonable speedups and processor efficiency can be achieved by a distributed blackboard system. The project has also highlighted some of the costs of using a distributed approach to designing a blackboard system.

Generation of Kappa Distributions in Solar Wind at 1 au

NASA Astrophysics Data System (ADS)

Livadiotis, G.; Desai, M. I.; Wilson, L. B., III

2018-02-01

We examine the generation of kappa distributions in the solar wind plasma near 1 au. Several mechanisms are mentioned in the literature, each characterized by a specific relationship between the solar wind plasma features, the interplanetary magnetic field (IMF), and the kappa index—the parameter that governs the kappa distributions. This relationship serves as a signature condition that helps the identification of the mechanism in the plasma. In general, a mechanism that generates kappa distributions involves a single or a series of stochastic or physical processes that induces local correlations among particles. We identify three fundamental solar wind plasma conditions that can generate kappa distributions, noted as (i) Debye shielding, (ii) frozen IMF, and (iii) temperature fluctuations, each one prevailing in different scales of solar wind plasma and magnetic field properties. Moreover, our findings show that the kappa distributions, and thus, their generating mechanisms, vary significantly with solar wind features: (i) the kappa index has different dependence on the solar wind speed for slow and fast modes, i.e., slow wind is characterized by a quasi-constant kappa index, κ ≈ 4.3 ± 0.7, while fast wind exhibits kappa indices that increase with bulk speed; (ii) the dispersion of magnetosonic waves is more effective for lower kappa indices (i.e., further from thermal equilibrium); and (iii) the kappa and polytropic indices are positively correlated, as it was anticipated by the theory.

Generation of Adaptive Gait Patterns for Quadruped Robot with CPG Network including Motor Dynamic Model

NASA Astrophysics Data System (ADS)

Son, Yurak; Kamano, Takuya; Yasuno, Takashi; Suzuki, Takayuki; Harada, Hironobu

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environment. The CPGs act as the flexible oscillators of the joints and make the desired angle of the joints. The CPGs are mutually connected each other, and the sets of their coupling parameters are adjusted by genetic algorithm so that the quadruped robot can realize the stable and adequate gait patterns. As a result of generation, the suitable CPG networks for not only a walking straight gait pattern but also rotation gait patterns are obtained. Experimental results demonstrate that the proposed CPG networks are effective to automatically adjust the adaptive gait patterns for the tested quadruped robot under various environment. Furthermore, the target tracking control based on image processing is achieved by combining the generated gait patterns.

Adaptive Development

NASA Technical Reports Server (NTRS)

2005-01-01

The goal of this research is to develop and demonstrate innovative adaptive seal technologies that can lead to dramatic improvements in engine performance, life, range, and emissions, and enhance operability for next generation gas turbine engines. This work is concentrated on the development of self-adaptive clearance control systems for gas turbine engines. Researchers have targeted the high-pressure turbine (HPT) blade tip seal location for following reasons: Current active clearance control (ACC) systems (e.g., thermal case-cooling schemes) cannot respond to blade tip clearance changes due to mechanical, thermal, and aerodynamic loads. As such they are prone to wear due to the required tight running clearances during operation. Blade tip seal wear (increased clearances) reduces engine efficiency, performance, and service life. Adaptive sealing technology research has inherent impact on all envisioned 21st century propulsion systems (e.g. distributed vectored, hybrid and electric drive propulsion concepts).

Distributed Adaptive Finite-Time Approach for Formation-Containment Control of Networked Nonlinear Systems Under Directed Topology.

PubMed

Wang, Yujuan; Song, Yongduan; Ren, Wei

2017-07-06

This paper presents a distributed adaptive finite-time control solution to the formation-containment problem for multiple networked systems with uncertain nonlinear dynamics and directed communication constraints. By integrating the special topology feature of the new constructed symmetrical matrix, the technical difficulty in finite-time formation-containment control arising from the asymmetrical Laplacian matrix under single-way directed communication is circumvented. Based upon fractional power feedback of the local error, an adaptive distributed control scheme is established to drive the leaders into the prespecified formation configuration in finite time. Meanwhile, a distributed adaptive control scheme, independent of the unavailable inputs of the leaders, is designed to keep the followers within a bounded distance from the moving leaders and then to make the followers enter the convex hull shaped by the formation of the leaders in finite time. The effectiveness of the proposed control scheme is confirmed by the simulation.

Microscale air quality impacts of distributed power generation facilities.

PubMed

Olaguer, Eduardo P; Knipping, Eladio; Shaw, Stephanie; Ravindran, Satish

2016-08-01

The electric system is experiencing rapid growth in the adoption of a mix of distributed renewable and fossil fuel sources, along with increasing amounts of off-grid generation. New operational regimes may have unforeseen consequences for air quality. A three-dimensional microscale chemical transport model (CTM) driven by an urban wind model was used to assess gaseous air pollutant and particulate matter (PM) impacts within ~10 km of fossil-fueled distributed power generation (DG) facilities during the early afternoon of a typical summer day in Houston, TX. Three types of DG scenarios were considered in the presence of motor vehicle emissions and a realistic urban canopy: (1) a 25-MW natural gas turbine operating at steady state in either simple cycle or combined heating and power (CHP) mode; (2) a 25-MW simple cycle gas turbine undergoing a cold startup with either moderate or enhanced formaldehyde emissions; and (3) a data center generating 10 MW of emergency power with either diesel or natural gas-fired backup generators (BUGs) without pollution controls. Simulations of criteria pollutants (NO2, CO, O3, PM) and the toxic pollutant, formaldehyde (HCHO), were conducted assuming a 2-hr operational time period. In all cases, NOx titration dominated ozone production near the source. The turbine scenarios did not result in ambient concentration enhancements significantly exceeding 1 ppbv for gaseous pollutants or over 1 µg/m(3) for PM after 2 hr of emission, assuming realistic plume rise. In the case of the datacenter with diesel BUGs, ambient NO2 concentrations were enhanced by 10-50 ppbv within 2 km downwind of the source, while maximum PM impacts in the immediate vicinity of the datacenter were less than 5 µg/m(3). Plausible scenarios of distributed fossil generation consistent with the electricity grid's transformation to a more flexible and modernized system suggest that a substantial amount of deployment would be required to significantly affect air quality on

Adaptive triangular mesh generation

NASA Technical Reports Server (NTRS)

Erlebacher, G.; Eiseman, P. R.

1984-01-01

A general adaptive grid algorithm is developed on triangular grids. The adaptivity is provided by a combination of node addition, dynamic node connectivity and a simple node movement strategy. While the local restructuring process and the node addition mechanism take place in the physical plane, the nodes are displaced on a monitor surface, constructed from the salient features of the physical problem. An approximation to mean curvature detects changes in the direction of the monitor surface, and provides the pulling force on the nodes. Solutions to the axisymmetric Grad-Shafranov equation demonstrate the capturing, by triangles, of the plasma-vacuum interface in a free-boundary equilibrium configuration.

Genetic adaptation to captivity can occur in a single generation

PubMed Central

Christie, Mark R.; Marine, Melanie L.; French, Rod A.; Blouin, Michael S.

2012-01-01

Captive breeding programs are widely used for the conservation and restoration of threatened and endangered species. Nevertheless, captive-born individuals frequently have reduced fitness when reintroduced into the wild. The mechanism for these fitness declines has remained elusive, but hypotheses include environmental effects of captive rearing, inbreeding among close relatives, relaxed natural selection, and unintentional domestication selection (adaptation to captivity). We used a multigenerational pedigree analysis to demonstrate that domestication selection can explain the precipitous decline in fitness observed in hatchery steelhead released into the Hood River in Oregon. After returning from the ocean, wild-born and first-generation hatchery fish were used as broodstock in the hatchery, and their offspring were released into the wild as smolts. First-generation hatchery fish had nearly double the lifetime reproductive success (measured as the number of returning adult offspring) when spawned in captivity compared with wild fish spawned under identical conditions, which is a clear demonstration of adaptation to captivity. We also documented a tradeoff among the wild-born broodstock: Those with the greatest fitness in a captive environment produced offspring that performed the worst in the wild. Specifically, captive-born individuals with five (the median) or more returning siblings (i.e., offspring of successful broodstock) averaged 0.62 returning offspring in the wild, whereas captive-born individuals with less than five siblings averaged 2.05 returning offspring in the wild. These results demonstrate that a single generation in captivity can result in a substantial response to selection on traits that are beneficial in captivity but severely maladaptive in the wild. PMID:22184236

Wealth distribution across communities of adaptive financial agents

NASA Astrophysics Data System (ADS)

DeLellis, Pietro; Garofalo, Franco; Lo Iudice, Francesco; Napoletano, Elena

2015-08-01

This paper studies the trading volumes and wealth distribution of a novel agent-based model of an artificial financial market. In this model, heterogeneous agents, behaving according to the Von Neumann and Morgenstern utility theory, may mutually interact. A Tobin-like tax (TT) on successful investments and a flat tax are compared to assess the effects on the agents’ wealth distribution. We carry out extensive numerical simulations in two alternative scenarios: (i) a reference scenario, where the agents keep their utility function fixed, and (ii) a focal scenario, where the agents are adaptive and self-organize in communities, emulating their neighbours by updating their own utility function. Specifically, the interactions among the agents are modelled through a directed scale-free network to account for the presence of community leaders, and the herding-like effect is tested against the reference scenario. We observe that our model is capable of replicating the benefits and drawbacks of the two taxation systems and that the interactions among the agents strongly affect the wealth distribution across the communities. Remarkably, the communities benefit from the presence of leaders with successful trading strategies, and are more likely to increase their average wealth. Moreover, this emulation mechanism mitigates the decrease in trading volumes, which is a typical drawback of TTs.

The role of stimulus-specific adaptation in songbird syntax generation

NASA Astrophysics Data System (ADS)

Wittenbach, Jason D.

Sequential behaviors are an important part of the behavioral repertoire of many animals and understanding how neural circuits encode and generate such sequences is a long-standing question in neuroscience. The Bengalese finch is a useful model system for studying variable action sequences. The songs of these birds consist of well-defined vocal elements (syllables) that are strung together to form sequences. The ordering of the syllables within the sequence is variable but not random - it shows complex statistical patterns (syntax). While often thought to be first-order, the syntax of the Bengalese finch song shows a distinct form of history dependence where the probability of repeating a syllable decreases as a function of the number of repetitions that have already occurred. Current models of the Bengalese finch song control circuitry offer no explanation for this repetition adaptation. The Bengalese finch also uses real-time auditory feedback to control the song syntax. Considering these facts, we hypothesize that repetition adaptation in the Bengalese finch syntax may be caused by stimulus-specific adaptation - a wide-spread phenomenon where neural responses to a specific stimulus become weaker with repeated presentations of the same stimulus. We begin by proposing a computational model for the song-control circuit where an auditory feedback signal that undergoes stimulus-specific adaptation helps drive repeated syllables. We show that this model does indeed capture the repetition adaptation observed in Bengalese finch syntax; along the way, we derive a new probabilistic model for repetition adaptation. Key predictions of our model are analyzed in light of experiments performed by collaborators. Next we extend the model in order to predict how the syntax will change as a function of brain temperature. These predictions are compared to experimental results from collaborators where portions of the Bengalese finch song circuit are cooled in awake and behaving birds

Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

NASA Technical Reports Server (NTRS)

Wang, Ray (Inventor)

2009-01-01

A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

A new low-energy bremsstrahlung generator for GEANT4.

PubMed

Peralta, L; Rodrigues, P; Trindade, A; Pia, M G

2005-01-01

The 2BN bremsstrahlung cross section is a well-adapted distribution to describe the radiative processes at low-electron kinetic energy (E(k) < 500 keV). In this work a method to implement this distribution in a Monte Carlo generator is developed.

Simulation of load-sharing in standalone distributed generation system

NASA Astrophysics Data System (ADS)

Ajewole, Titus O.; Craven, Robert P. M.; Kayode, Olakunle; Babalola, Olufisayo S.

2018-05-01

This paper presents a study on load-sharing among the component generating units of a multi-source electric microgrid that is operated as an autonomous ac supply-mode system. Emerging trend in power system development permits deployment of microgrids for standalone or stand-by applications, thereby requiring active- and reactive power sharing among the discrete generating units contained in hybrid-source microgrids. In this study, therefore, a laboratory-scale model of a microgrid energized with three renewable energy-based sources is employed as a simulation platform to investigate power sharing among the power-generating units. Each source is represented by a source emulator that captures the real operational characteristics of the mimicked generating unit and, with implementation of real-life weather data and load profiles on the model; the sharing of the load among the generating units is investigated. There is a proportionate generation of power by the three source emulators, with their frequencies perfectly synchronized at the point of common coupling as a result of balance flow of power among them. This hybrid topology of renewable energy-based microgrid could therefore be seamlessly adapted into national energy mix by the indigenous electric utility providers in Nigeria.

Longitudinal effects of adaptive interventions with a speech-generating devicein minimally verbal children with ASD

PubMed Central

Almirall, Daniel; DiStefano, Charlotte; Chang, Ya-Chih; Shire, Stephanie; Kaiser, Ann; Lu, Xi; Nahum-Shani, Inbal; Landa, Rebecca; Mathy, Pamela; Kasari, Connie

2016-01-01

Objective There are limited data on the effects of adaptive social communication interventions with a speech-generating device in autism. This study is the first to compare growth in communications outcomes among three adaptive interventions in school-aged children with autism spectrum disorder (ASD) who are minimally verbal. Methods Sixty-one children, aged 5–8 years participated in a sequential, multiple-assignment randomized trial (SMART). All children received a developmental communication intervention: joint attention, symbolic play, engagement and regulation (JASP) with enhanced milieu teaching (EMT). The SMART included three two-stage, 24-week adaptive interventions with different provisions of a speech-generating device (SGD) in the context of JASP+EMT. The first adaptive intervention, with no SGD, initially assigned JASP+EMT alone; then intensified JASP+EMT for slow responders. In the second adaptive intervention, slow responders to JASP+EMT were assigned JASP+EMT+SGD. The third adaptive intervention initially assigned JASP+EMT+SGD; then intensified JASP+EMT+SGD for slow responders. Analyses examined between-group differences in change in outcomes from baseline to week 36. Verbal outcomes included spontaneous communicative utterances and novel words. Non-linguistic communication outcomes included initiating joint attention and behavior regulation, and play. Results The adaptive intervention beginning with JASP+EMT+SGD was estimated as superior. There were significant (P<0.05) between-group differences in change in spontaneous communicative utterances and initiating joint attention. Conclusions School-aged children with ASD who are minimally verbal make significant gains in communication outcomes with an adaptive intervention beginning with JASP+EMT+SGD. Future research should explore mediators and moderators of the adaptive intervention effects and second-stage intervention options that further capitalize on early gains in treatment. PMID:26954267

Control of dispatch dynamics for lowering the cost of distributed generation in the built environment

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Distributed generation can provide many benefits over traditional central generation such as increased reliability and efficiency while reducing emissions. Despite these potential benefits, distributed generation is generally not purchased unless it reduces energy costs. Economic dispatch strategies can be designed such that distributed generation technologies reduce overall facility energy costs. In this thesis, a microturbine generator is dispatched using different economic control strategies, reducing the cost of energy to the facility. Several industrial and commercial facilities are simulated using acquired electrical, heating, and cooling load data. Industrial and commercial utility rate structures are modeled after Southern California Edison and Southern California Gas Company tariffs and used to find energy costs for the simulated buildings and corresponding microturbine dispatch. Using these control strategies, building models, and utility rate models, a parametric study examining various generator characteristics is performed. An economic assessment of the distributed generation is then performed for both the microturbine generator and parametric study. Without the ability to export electricity to the grid, the economic value of distributed generation is limited to reducing the individual costs that make up the cost of energy for a building. Any economic dispatch strategy must be built to reduce these individual costs. While the ability of distributed generation to reduce cost depends of factors such as electrical efficiency and operations and maintenance cost, the building energy demand being serviced has a strong effect on cost reduction. Buildings with low load factors can accept distributed generation with higher operating costs (low electrical efficiency and/or high operations and maintenance cost) due to the value of demand reduction. As load factor increases, lower operating cost generators are desired due to a larger portion of the building load

Network integration of distributed power generation

NASA Astrophysics Data System (ADS)

Dondi, Peter; Bayoumi, Deia; Haederli, Christoph; Julian, Danny; Suter, Marco

The world-wide move to deregulation of the electricity and other energy markets, concerns about the environment, and advances in renewable and high efficiency technologies has led to major emphasis being placed on the use of small power generation units in a variety of forms. The paper reviews the position of distributed generation (DG, as these small units are called in comparison with central power plants) with respect to the installation and interconnection of such units with the classical grid infrastructure. In particular, the status of technical standards both in Europe and USA, possible ways to improve the interconnection situation, and also the need for decisions that provide a satisfactory position for the network operator (who remains responsible for the grid, its operation, maintenance and investment plans) are addressed.

Illustration of distributed generation effects on protection system coordination

NASA Astrophysics Data System (ADS)

Alawami, Hussain Adnan

Environmental concerns, market forces, and emergence of new technologies have recently resulted in restructuring electric utility from vertically integrated networks to competitive deregulated entities. Distributed generation (DG) is playing a major role in such deregulated markets. When they are installed in small amounts and small sizes, their impacts on the system may be negligible. When their penetration levels increase as well as their sizes, however, they may start affecting the system performance from more than one aspect. Power system protection needs to be re-assessed after the emergence of DG. This thesis attempts to illustrate the impact of DG on the power system protection coordination. It will study the operation of the impedance relays, fuses, reclosers and overcurrent relays when a DG is added to the distribution network. Different DG sizes, distances from the network and locations within the distribution system will be considered. Power system protection coordination is very sensitive to the DG size where it is not for the DG distance. DG location has direct impact on the operation of the protective devices especially when it is inserted in the middle point of the distribution system. Key Words, Distributed Generation, Impedance relay, fuses, reclosers, overcurrent relays, power system protection coordination.

Estimating probable flaw distributions in PWR steam generator tubes

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

Gorman, J.A.; Turner, A.P.L.

1997-02-01

This paper describes methods for estimating the number and size distributions of flaws of various types in PWR steam generator tubes. These estimates are needed when calculating the probable primary to secondary leakage through steam generator tubes under postulated accidents such as severe core accidents and steam line breaks. The paper describes methods for two types of predictions: (1) the numbers of tubes with detectable flaws of various types as a function of time, and (2) the distributions in size of these flaws. Results are provided for hypothetical severely affected, moderately affected and lightly affected units. Discussion is provided regardingmore » uncertainties and assumptions in the data and analyses.« less

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

PubMed

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

PubMed Central

Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

Impact of Load Balancing on Unstructured Adaptive Grid Computations for Distributed-Memory Multiprocessors

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak; Simon, Horst D.

1996-01-01

The computational requirements for an adaptive solution of unsteady problems change as the simulation progresses. This causes workload imbalance among processors on a parallel machine which, in turn, requires significant data movement at runtime. We present a new dynamic load-balancing framework, called JOVE, that balances the workload across all processors with a global view. Whenever the computational mesh is adapted, JOVE is activated to eliminate the load imbalance. JOVE has been implemented on an IBM SP2 distributed-memory machine in MPI for portability. Experimental results for two model meshes demonstrate that mesh adaption with load balancing gives more than a sixfold improvement over one without load balancing. We also show that JOVE gives a 24-fold speedup on 64 processors compared to sequential execution.

Characterisation of the dynamic behaviour of lipid droplets in the early mouse embryo using adaptive harmonic generation microscopy.

PubMed

Watanabe, Tomoko; Thayil, Anisha; Jesacher, Alexander; Grieve, Kate; Debarre, Delphine; Wilson, Tony; Booth, Martin; Srinivas, Shankar

2010-06-03

Lipid droplets (LD) are organelles with an important role in normal metabolism and disease. The lipid content of embryos has a major impact on viability and development. LD in Drosophila embryos and cultured cell lines have been shown to move and fuse in a microtubule dependent manner. Due to limitations in current imaging technology, little is known about the behaviour of LD in the mammalian embryo. Harmonic generation microscopy (HGM) allows one to image LD without the use of exogenous labels. Adaptive optics can be used to correct aberrations that would otherwise degrade the quality and information content of images. We have built a harmonic generation microscope with adaptive optics to characterise early mouse embryogenesis. At fertilization, LD are small and uniformly distributed, but in the implanting blastocyst, LD are larger and enriched in the invading giant cells of the trophectoderm. Time-lapse studies reveal that LD move continuously and collide but do not fuse, instead forming aggregates that subsequently behave as single units. Using specific inhibitors, we show that the velocity and dynamic behaviour of LD is dependent not only on microtubules as in other systems, but also on microfilaments. We explore the limits within which HGM can be used to study living embryos without compromising viability and make the counterintuitive finding that 16 J of energy delivered continuously over a period of minutes can be less deleterious than an order of magnitude lower energy delivered dis-continuously over a period of hours. LD in pre-implantation mouse embryos show a previously unappreciated complexity of behaviour that is dependent not only on microtubules, but also microfilaments. Unlike LD in other systems, LD in the mouse embryo do not fuse but form aggregates. This study establishes HGM with adaptive optics as a powerful tool for the study of LD biology and provides insights into the photo-toxic effects of imaging embryos.

Predicting the impacts of climate change on animal distributions: the importance of local adaptation and species' traits

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

HELLMANN, J. J.; LOBO, N. F.

2011-12-20

The geographic range limits of many species are strongly affected by climate and are expected to change under global warming. For species that are able to track changing climate over broad geographic areas, we expect to see shifts in species distributions toward the poles and away from the equator. A number of ecological and evolutionary factors, however, could restrict this shifting or redistribution under climate change. These factors include restricted habitat availability, restricted capacity for or barriers to movement, or reduced abundance of colonists due the perturbation effect of climate change. This research project examined the last of these constraintsmore » - that climate change could perturb local conditions to which populations are adapted, reducing the likelihood that a species will shift its distribution by diminishing the number of potential colonists. In the most extreme cases, species ranges could collapse over a broad geographic area with no poleward migration and an increased risk of species extinction. Changes in individual species ranges are the processes that drive larger phenomena such as changes in land cover, ecosystem type, and even changes in carbon cycling. For example, consider the poleward range shift and population outbreaks of the mountain pine beetle that has decimated millions of acres of Douglas fir trees in the western US and Canada. Standing dead trees cause forest fires and release vast quantities of carbon to the atmosphere. The beetle likely shifted its range because it is not locally adapted across its range, and it appears to be limited by winter low temperatures that have steadily increased in the last decades. To understand range and abundance changes like the pine beetle, we must reveal the extent of adaptive variation across species ranges - and the physiological basis of that adaptation - to know if other species will change as readily as the pine beetle. Ecologists tend to assume that range shifts are the

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

Integrated, Automated Distributed Generation Technologies Demonstration

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

Jensen, Kevin

2014-09-01

The purpose of the NETL Project was to develop a diverse combination of distributed renewable generation technologies and controls and demonstrate how the renewable generation could help manage substation peak demand at the ATK Promontory plant site. The Promontory plant site is located in the northwestern Utah desert approximately 25 miles west of Brigham City, Utah. The plant encompasses 20,000 acres and has over 500 buildings. The ATK Promontory plant primarily manufactures solid propellant rocket motors for both commercial and government launch systems. The original project objectives focused on distributed generation; a 100 kW (kilowatt) wind turbine, a 100 kWmore » new technology waste heat generation unit, a 500 kW energy storage system, and an intelligent system-wide automation system to monitor and control the renewable energy devices then release the stored energy during the peak demand time. The original goal was to reduce peak demand from the electrical utility company, Rocky Mountain Power (RMP), by 3.4%. For a period of time we also sought to integrate our energy storage requirements with a flywheel storage system (500 kW) proposed for the Promontory/RMP Substation. Ultimately the flywheel storage system could not meet our project timetable, so the storage requirement was switched to a battery storage system (300 kW.) A secondary objective was to design/install a bi-directional customer/utility gateway application for real-time visibility and communications between RMP, and ATK. This objective was not achieved because of technical issues with RMP, ATK Information Technology Department’s stringent requirements based on being a rocket motor manufacturing facility, and budget constraints. Of the original objectives, the following were achieved: • Installation of a 100 kW wind turbine. • Installation of a 300 kW battery storage system. • Integrated control system installed to offset electrical demand by releasing stored energy from renewable

Exploring the Dimensionality of Ethnic Minority Adaptation in Britain: An Analysis across Ethnic and Generational Lines

PubMed Central

Lessard-Phillips, Laurence

2015-01-01

In this article I explore the dimensionality of the long-term experiences of the main ethnic minority groups (their adaptation) in Britain. Using recent British data, I apply factor analysis to uncover the underlying number of factors behind variables deemed to be representative of the adaptation experience within the literature. I then attempt to assess the groupings of adaptation present in the data, to see whether a typology of adaptation exists (i.e. whether adaptation in different dimensions can be concomitant with others). The analyses provide an empirical evidence base to reflect on: (1) the extent of group differences in the adaptation process, which may cut across ethnic and generational lines; and (2) whether the uncovered dimensions of adaptation match existing theoretical views and empirical evidence. Results suggest that adaptation should be regarded as a multi-dimensional phenomenon where clear typologies of adaptation based on specific trade-offs (mostly cultural) appear to exist. PMID:28502998

Final Technical Report for Contract No. DE-EE0006332, "Integrated Simulation Development and Decision Support Tool-Set for Utility Market and Distributed Solar Power Generation"

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

Cormier, Dallas; Edra, Sherwin; Espinoza, Michael

This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations,more » identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.« less

Distributed Generation Market Demand Model (dGen): Documentation

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

Sigrin, Benjamin; Gleason, Michael; Preus, Robert

The Distributed Generation Market Demand model (dGen) is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States. The new model builds off, extends, and replaces NREL's SolarDS model (Denholm et al. 2009a), which simulates the market penetration of distributed PV only. Unlike the SolarDS model, dGen can modelmore » various DER technologies under one platform--it currently can simulate the adoption of distributed solar (the dSolar module) and distributed wind (the dWind module) and link with the ReEDS capacity expansion model (Appendix C). The underlying algorithms and datasets in dGen, which improve the representation of customer decision making as well as the spatial resolution of analyses (Figure ES-1), also are improvements over SolarDS.« less

Smart campus: Data on energy generation costs from distributed generation systems of electrical energy in a Nigerian University.

PubMed

Okeniyi, Joshua O; Atayero, Aderemi A; Popoola, Segun I; Okeniyi, Elizabeth T; Alalade, Gbenga M

2018-04-01

This data article presents comparisons of energy generation costs from gas-fired turbine and diesel-powered systems of distributed generation type of electrical energy in Covenant University, Ota, Nigeria, a smart university campus driven by Information and Communication Technologies (ICT). Cumulative monthly data of the energy generation costs, for consumption in the institution, from the two modes electric power, which was produced at locations closed to the community consuming the energy, were recorded for the period spanning January to December 2017. By these, energy generation costs from the turbine system proceed from the gas-firing whereas the generation cost data from the diesel-powered generator also include data on maintenance cost for this mode of electrical power generation. These energy generation cost data that were presented in tables and graphs employ descriptive probability distribution and goodness-of-fit tests of statistical significance as the methods for the data detailing and comparisons. Information details from this data of energy generation costs are useful for furthering research developments and aiding energy stakeholders and decision-makers in the formulation of policies on energy generation modes, economic valuation in terms of costing and management for attaining energy-efficient/smart educational environment.

29 CFR 1910.269 - Electric power generation, transmission, and distribution.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Electric power generation, transmission, and distribution. 1910.269 Section 1910.269 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Special Industries § 1910.269 Electric power generation,...

29 CFR 1910.269 - Electric power generation, transmission, and distribution.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 5 2014-07-01 2014-07-01 false Electric power generation, transmission, and distribution. 1910.269 Section 1910.269 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Special Industries § 1910.269 Electric power generation,...

29 CFR 1910.269 - Electric power generation, transmission, and distribution.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 5 2013-07-01 2013-07-01 false Electric power generation, transmission, and distribution. 1910.269 Section 1910.269 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Special Industries § 1910.269 Electric power generation,...

29 CFR 1910.269 - Electric power generation, transmission, and distribution.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 5 2012-07-01 2012-07-01 false Electric power generation, transmission, and distribution. 1910.269 Section 1910.269 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Special Industries § 1910.269 Electric power generation,...

29 CFR 1910.269 - Electric power generation, transmission, and distribution.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 5 2011-07-01 2011-07-01 false Electric power generation, transmission, and distribution. 1910.269 Section 1910.269 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Special Industries § 1910.269 Electric power generation,...

Efficient generation of discontinuity-preserving adaptive triangulations from range images.

PubMed

Garcia, Miguel Angel; Sappa, Angel Domingo

2004-10-01

This paper presents an efficient technique for generating adaptive triangular meshes from range images. The algorithm consists of two stages. First, a user-defined number of points is adaptively sampled from the given range image. Those points are chosen by taking into account the surface shapes represented in the range image in such a way that points tend to group in areas of high curvature and to disperse in low-variation regions. This selection process is done through a noniterative, inherently parallel algorithm in order to gain efficiency. Once the image has been subsampled, the second stage applies a two and one half-dimensional Delaunay triangulation to obtain an initial triangular mesh. To favor the preservation of surface and orientation discontinuities (jump and crease edges) present in the original range image, the aforementioned triangular mesh is iteratively modified by applying an efficient edge flipping technique. Results with real range images show accurate triangular approximations of the given range images with low processing times.

Effect of Rayleigh-scattering distributed feedback on multiwavelength Raman fiber laser generation.

PubMed

El-Taher, A E; Harper, P; Babin, S A; Churkin, D V; Podivilov, E V; Ania-Castanon, J D; Turitsyn, S K

2011-01-15

We experimentally demonstrate a Raman fiber laser based on multiple point-action fiber Bragg grating reflectors and distributed feedback via Rayleigh scattering in an ~22-km-long optical fiber. Twenty-two lasing lines with spacing of ~100 GHz (close to International Telecommunication Union grid) in the C band are generated at the watt level. In contrast to the normal cavity with competition between laser lines, the random distributed feedback cavity exhibits highly stable multiwavelength generation with a power-equalized uniform distribution, which is almost independent on power.

Intelligent Distribution Voltage Control with Distributed Generation =

NASA Astrophysics Data System (ADS)

Castro Mendieta, Jose

In this thesis, three methods for the optimal participation of the reactive power of distributed generations (DGs) in unbalanced distributed network have been proposed, developed, and tested. These new methods were developed with the objectives of maintain voltage within permissible limits and reduce losses. The first method proposes an optimal participation of reactive power of all devices available in the network. The propose approach is validated by comparing the results with other methods reported in the literature. The proposed method was implemented using Simulink of Matlab and OpenDSS. Optimization techniques and the presentation of results are from Matlab. The co-simulation of Electric Power Research Institute's (EPRI) OpenDSS program solves a three-phase optimal power flow problem in the unbalanced IEEE 13 and 34-node test feeders. The results from this work showed a better loss reduction compared to the Coordinated Voltage Control (CVC) method. The second method aims to minimize the voltage variation on the pilot bus on distribution network using DGs. It uses Pareto and Fuzzy-PID logic to reduce the voltage variation. Results indicate that the proposed method reduces the voltage variation more than the other methods. Simulink of Matlab and OpenDSS is used in the development of the proposed approach. The performance of the method is evaluated on IEEE 13-node test feeder with one and three DGs. Variables and unbalanced loads are used, based on real consumption data, over a time window of 48 hours. The third method aims to minimize the reactive losses using DGs on distribution networks. This method analyzes the problem using the IEEE 13-node test feeder with three different loads and the IEEE 123-node test feeder with four DGs. The DGs can be fixed or variables. Results indicate that integration of DGs to optimize the reactive power of the network helps to maintain the voltage within the allowed limits and to reduce the reactive power losses. The thesis is

Optimal updating magnitude in adaptive flat-distribution sampling

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Drake, Justin A.; Ma, Jianpeng; Pettitt, B. Montgomery

2017-11-01

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Optimal updating magnitude in adaptive flat-distribution sampling.

PubMed

Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery

2017-11-07

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Distributed Generation Energy Technology Operations and Maintenance Costs |

Science.gov Websites

Costs Distributed Generation Energy Technology Operations and Maintenance Costs Transparent Cost Database Button The following charts indicate recent operations and maintenance (O&M) cost estimates available national-level cost data from a variety of sources. Costs in your specific location will vary. The

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

NASA Astrophysics Data System (ADS)

Zhao, Z.-G.; Zhou, L.-J.; Zhang, J.-T.; Zhu, Q.; Hedrick, J.-K.

2017-05-01

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

NASA Astrophysics Data System (ADS)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; Papka, M. E.; Benjamin, D. P.

2017-01-01

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application and the performance that was achieved.

Multimodal Estimation of Distribution Algorithms.

PubMed

Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun

2016-02-15

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.

Adaptive real time selection for quantum key distribution in lossy and turbulent free-space channels

NASA Astrophysics Data System (ADS)

Vallone, Giuseppe; Marangon, Davide G.; Canale, Matteo; Savorgnan, Ilaria; Bacco, Davide; Barbieri, Mauro; Calimani, Simon; Barbieri, Cesare; Laurenti, Nicola; Villoresi, Paolo

2015-04-01

The unconditional security in the creation of cryptographic keys obtained by quantum key distribution (QKD) protocols will induce a quantum leap in free-space communication privacy in the same way that we are beginning to realize secure optical fiber connections. However, free-space channels, in particular those with long links and the presence of atmospheric turbulence, are affected by losses, fluctuating transmissivity, and background light that impair the conditions for secure QKD. Here we introduce a method to contrast the atmospheric turbulence in QKD experiments. Our adaptive real time selection (ARTS) technique at the receiver is based on the selection of the intervals with higher channel transmissivity. We demonstrate, using data from the Canary Island 143-km free-space link, that conditions with unacceptable average quantum bit error rate which would prevent the generation of a secure key can be used once parsed according to the instantaneous scintillation using the ARTS technique.

Historical and Current U.S. Strategies for Boosting Distributed Generation

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

Lowder, Travis; Schwabe, Paul; Zhou, Ella

2015-10-29

This report seeks to introduce a variety of top-down and bottom-up practices that, in concert with the macro-environment of cost-reduction globally and early adoption in Europe, helped boost the distributed generation photovoltaic market in the United States. These experiences may serve as a reference in China's quest to promote distributed renewable energy.

Next Generation Multimedia Distributed Data Base Systems

NASA Technical Reports Server (NTRS)

Pendleton, Stuart E.

1997-01-01

The paradigm of client/server computing is changing. The model of a server running a monolithic application and supporting clients at the desktop is giving way to a different model that blurs the line between client and server. We are on the verge of plunging into the next generation of computing technology--distributed object-oriented computing. This is not only a change in requirements but a change in opportunities, and requires a new way of thinking for Information System (IS) developers. The information system demands caused by global competition are requiring even more access to decision making tools. Simply, object-oriented technology has been developed to supersede the current design process of information systems which is not capable of handling next generation multimedia.

Study on Distribution Reliability with Parallel and On-site Distributed Generation Considering Protection Miscoordination and Tie Line

NASA Astrophysics Data System (ADS)

Chaitusaney, Surachai; Yokoyama, Akihiko

In distribution system, Distributed Generation (DG) is expected to improve the system reliability as its backup generation. However, DG contribution in fault current may cause the loss of the existing protection coordination, e.g. recloser-fuse coordination and breaker-breaker coordination. This problem can drastically deteriorate the system reliability, and it is more serious and complicated when there are several DG sources in the system. Hence, the above conflict in reliability aspect unavoidably needs a detailed investigation before the installation or enhancement of DG is done. The model of composite DG fault current is proposed to find the threshold beyond which existing protection coordination is lost. Cases of protection miscoordination are described, together with their consequences. Since a distribution system may be tied with another system, the issues of tie line and on-site DG are integrated into this study. Reliability indices are evaluated and compared in the distribution reliability test system RBTS Bus 2.

Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

NASA Technical Reports Server (NTRS)

Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.

1992-01-01

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.

Evaluation of truncation error and adaptive grid generation for the transonic full potential flow calculations

NASA Technical Reports Server (NTRS)

Nakamura, S.

1983-01-01

The effects of truncation error on the numerical solution of transonic flows using the full potential equation are studied. The effects of adapting grid point distributions to various solution aspects including shock waves is also discussed. A conclusion is that a rapid change of grid spacing is damaging to the accuracy of the flow solution. Therefore, in a solution adaptive grid application an optimal grid is obtained as a tradeoff between the amount of grid refinement and the rate of grid stretching.

Grid-Connected Distributed Generation: Compensation Mechanism Basics

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

Aznar, Alexandra Y; Zinaman, Owen R

2017-10-02

This short report defines compensation mechanisms for grid-connected, behind-the-meter distributed generation (DG) systems as instruments that comprise three core elements: (1) metering and billing arrangements, (2) sell rate design, and (3) retail rate design. This report describes metering and billing arrangements, with some limited discussion of sell rate design. We detail the three possible arrangements for metering and billing of DG: net energy metering (NEM); buy all, sell all; and net billing.

Distributed Generation Energy Technology Capital Costs | Energy Analysis |

Science.gov Websites

Technology Capital Costs Transparent Cost Database Button The following charts indicate recent capital cost charts provide a compilation of available national-level cost data from a variety of sources. Costs in distributed generation data used within these charts. If you are seeking utility-scale technology capital cost

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

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

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the World- wide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE PAGES

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; ...

2016-09-29

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

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

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Anti-islanding Protection of Distributed Generation Using Rate of Change of Impedance

NASA Astrophysics Data System (ADS)

Shah, Pragnesh; Bhalja, Bhavesh

2013-08-01

Distributed Generation (DG), which is interlinked with distribution system, has inevitable effect on distribution system. Integrating DG with the utility network demands an anti-islanding scheme to protect the system. Failure to trip islanded generators can lead to problems such as threats to personnel safety, out-of-phase reclosing, and degradation of power quality. In this article, a new method for anti-islanding protection based on impedance monitoring of distribution network is carried out in presence of DG. The impedance measured between two phases is used to derive the rate of change of impedance (dz/dt), and its peak values are used for final trip decision. Test data are generated using PSCAD/EMTDC software package and the performance of the proposed method is evaluated in MatLab software. The simulation results show the effectiveness of the proposed scheme as it is capable to detect islanding condition accurately. Subsequently, it is also observed that the proposed scheme does not mal-operate during other disturbances such as short circuit and switching event.

Narrow-band generation in random distributed feedback fiber laser.

PubMed

Sugavanam, Srikanth; Tarasov, Nikita; Shu, Xuewen; Churkin, Dmitry V

2013-07-15

Narrow-band emission of spectral width down to ~0.05 nm line-width is achieved in the random distributed feedback fiber laser employing narrow-band fiber Bragg grating or fiber Fabry-Perot interferometer filters. The observed line-width is ~10 times less than line-width of other demonstrated up to date random distributed feedback fiber lasers. The random DFB laser with Fabry-Perot interferometer filter provides simultaneously multi-wavelength and narrow-band (within each line) generation with possibility of further wavelength tuning.

Post-migration adaptation and age at menarche in the second generation of migrants.

PubMed

Gomula, Aleksandra; Koziel, Slawomir

2015-01-01

Age at menarche is one of the most important measures of sexual maturation in girls. Since it has a high level of ecosensitivity, early environmental stress may trigger early puberty. One of these stress factors may be parental stress caused by the change of living conditions related to migration and adaptation to the new environment. Therefore, the aim of this study was to investigate the relationship between parental migration status and the timing of sexual maturity in second generation, i.e. migrants' daughters. Data were collected during the 2(nd) Polish Anthropological Survey carried out in 1966 - 1969. The information on age at menarche as well as demographic and social characteristics were collected by the use of a questionnaire. The results show that the age at menarche has been accelerated in girls from low socioeconomic status (low-SES) migrant families in comparison to low-SES non-migrant families. This study provides new biosocial evidence on the impact of the parental long-lasting post-migration adaptation on the timing of maturation in the second generation of migrants.

Neutron monitor generated data distributions in quantum variational Monte Carlo

NASA Astrophysics Data System (ADS)

Kussainov, A. S.; Pya, N.

2016-08-01

We have assessed the potential applications of the neutron monitor hardware as random number generator for normal and uniform distributions. The data tables from the acquisition channels with no extreme changes in the signal level were chosen as the retrospective model. The stochastic component was extracted by fitting the raw data with splines and then subtracting the fit. Scaling the extracted data to zero mean and variance of one is sufficient to obtain a stable standard normal random variate. Distributions under consideration pass all available normality tests. Inverse transform sampling is suggested to use as a source of the uniform random numbers. Variational Monte Carlo method for quantum harmonic oscillator was used to test the quality of our random numbers. If the data delivery rate is of importance and the conventional one minute resolution neutron count is insufficient, we could always settle for an efficient seed generator to feed into the faster algorithmic random number generator or create a buffer.

Generative models for discovering sparse distributed representations.

PubMed Central

Hinton, G E; Ghahramani, Z

1997-01-01

We describe a hierarchical, generative model that can be viewed as a nonlinear generalization of factor analysis and can be implemented in a neural network. The model uses bottom-up, top-down and lateral connections to perform Bayesian perceptual inference correctly. Once perceptual inference has been performed the connection strengths can be updated using a very simple learning rule that only requires locally available information. We demonstrate that the network learns to extract sparse, distributed, hierarchical representations. PMID:9304685

Nonlinear harmonic generation in distributed optical klystrons

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

H.P. Freund; George R. Neil

2001-12-01

A distributed optical klystron has the potential for dramatically shortening the total interaction length in high-gain free-electron lasers (INP 77-59, Novosibirsk, 1977; Nucl. Instr. and Meth A 304 (1991) 463) in comparison to a single-wiggler-segment configuration. This shortening can be even more dramatic if a nonlinear harmonic generation mechanism is used to reach the desired wavelength. An example operating at a 4.5{angstrom} fundamental and a 1.5{angstrom} harmonic is discussed.

Fast implementation of length-adaptive privacy amplification in quantum key distribution

NASA Astrophysics Data System (ADS)

Zhang, Chun-Mei; Li, Mo; Huang, Jing-Zheng; Patcharapong, Treeviriyanupab; Li, Hong-Wei; Li, Fang-Yi; Wang, Chuan; Yin, Zhen-Qiang; Chen, Wei; Keattisak, Sripimanwat; Han, Zhen-Fu

2014-09-01

Post-processing is indispensable in quantum key distribution (QKD), which is aimed at sharing secret keys between two distant parties. It mainly consists of key reconciliation and privacy amplification, which is used for sharing the same keys and for distilling unconditional secret keys. In this paper, we focus on speeding up the privacy amplification process by choosing a simple multiplicative universal class of hash functions. By constructing an optimal multiplication algorithm based on four basic multiplication algorithms, we give a fast software implementation of length-adaptive privacy amplification. “Length-adaptive” indicates that the implementation of privacy amplification automatically adapts to different lengths of input blocks. When the lengths of the input blocks are 1 Mbit and 10 Mbit, the speed of privacy amplification can be as fast as 14.86 Mbps and 10.88 Mbps, respectively. Thus, it is practical for GHz or even higher repetition frequency QKD systems.

Adaptive Control of Four-Leg VSC Based DSTATCOM in Distribution System

NASA Astrophysics Data System (ADS)

Singh, Bhim; Arya, Sabha Raj

2014-01-01

This work discusses an experimental performance of a four-leg Distribution Static Compensator (DSTATCOM) using an adaptive filter based approach. It is used for estimation of reference supply currents through extracting the fundamental active power components of three-phase distorted load currents. This control algorithm is implemented on an assembled DSTATCOM for harmonics elimination, neutral current compensation and load balancing, under nonlinear loads. Experimental results are discussed, and it is noticed that DSTATCOM is effective solution to perform satisfactory performance under load dynamics.

Noise adaptation in integrate-and fire neurons.

PubMed

Rudd, M E; Brown, L G

1997-07-01

The statistical spiking response of an ensemble of identically prepared stochastic integrate-and-fire neurons to a rectangular input current plus gaussian white noise is analyzed. It is shown that, on average, integrate-and-fire neurons adapt to the root-mean-square noise level of their input. This phenomenon is referred to as noise adaptation. Noise adaptation is characterized by a decrease in the average neural firing rate and an accompanying decrease in the average value of the generator potential, both of which can be attributed to noise-induced resets of the generator potential mediated by the integrate-and-fire mechanism. A quantitative theory of noise adaptation in stochastic integrate-and-fire neurons is developed. It is shown that integrate-and-fire neurons, on average, produce transient spiking activity whenever there is an increase in the level of their input noise. This transient noise response is either reduced or eliminated over time, depending on the parameters of the model neuron. Analytical methods are used to prove that nonleaky integrate-and-fire neurons totally adapt to any constant input noise level, in the sense that their asymptotic spiking rates are independent of the magnitude of their input noise. For leaky integrate-and-fire neurons, the long-run noise adaptation is not total, but the response to noise is partially eliminated. Expressions for the probability density function of the generator potential and the first two moments of the potential distribution are derived for the particular case of a nonleaky neuron driven by gaussian white noise of mean zero and constant variance. The functional significance of noise adaptation for the performance of networks comprising integrate-and-fire neurons is discussed.

The Development of Group Interaction Patterns: How Groups become Adaptive, Generative, and Transformative Learners

ERIC Educational Resources Information Center

London, Manuel; Sessa, Valerie I.

2007-01-01

This article integrates the literature on group interaction process analysis and group learning, providing a framework for understanding how patterns of interaction develop. The model proposes how adaptive, generative, and transformative learning processes evolve and vary in their functionality. Environmental triggers for learning, the group's…

Biodiversity, distributions and adaptations of Arctic species in the context of environmental change.

PubMed

Callaghan, Terry V; Björn, Lars Olof; Chernov, Yuri; Chapin, Terry; Christensen, Torben R; Huntley, Brian; Ims, Rolf A; Johansson, Margareta; Jolly, Dyanna; Jonasson, Sven; Matveyeva, Nadya; Panikov, Nicolai; Oechel, Walter; Shaver, Gus; Elster, Josef; Henttonen, Heikki; Laine, Kari; Taulavuori, Kari; Taulavuori, Erja; Zöckler, Christoph

2004-11-01

adapted to the Arctic's climate: some can metabolize at temperatures down to -39 degrees C. Cyanobacteria and algae have a wide range of adaptive strategies that allow them to avoid, or at least minimize UV injury. Microorganisms can tolerate most environmental conditions and they have short generation times which can facilitate rapid adaptation to new environments. In contrast, Arctic plant and animal species are very likely to change their distributions rather than evolve significantly in response to warming.

Performance Enhancement of Radial Distributed System with Distributed Generators by Reconfiguration Using Binary Firefly Algorithm

NASA Astrophysics Data System (ADS)

Rajalakshmi, N.; Padma Subramanian, D.; Thamizhavel, K.

2015-03-01

The extent of real power loss and voltage deviation associated with overloaded feeders in radial distribution system can be reduced by reconfiguration. Reconfiguration is normally achieved by changing the open/closed state of tie/sectionalizing switches. Finding optimal switch combination is a complicated problem as there are many switching combinations possible in a distribution system. Hence optimization techniques are finding greater importance in reducing the complexity of reconfiguration problem. This paper presents the application of firefly algorithm (FA) for optimal reconfiguration of radial distribution system with distributed generators (DG). The algorithm is tested on IEEE 33 bus system installed with DGs and the results are compared with binary genetic algorithm. It is found that binary FA is more effective than binary genetic algorithm in achieving real power loss reduction and improving voltage profile and hence enhancing the performance of radial distribution system. Results are found to be optimum when DGs are added to the test system, which proved the impact of DGs on distribution system.

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

Determination of optimum allocation and pricing of distributed generation using genetic algorithm methodology

NASA Astrophysics Data System (ADS)

Mwakabuta, Ndaga Stanslaus

Electric power distribution systems play a significant role in providing continuous and "quality" electrical energy to different classes of customers. In the context of the present restrictions on transmission system expansions and the new paradigm of "open and shared" infrastructure, new approaches to distribution system analyses, economic and operational decision-making need investigation. This dissertation includes three layers of distribution system investigations. In the basic level, improved linear models are shown to offer significant advantages over previous models for advanced analysis. In the intermediate level, the improved model is applied to solve the traditional problem of operating cost minimization using capacitors and voltage regulators. In the advanced level, an artificial intelligence technique is applied to minimize cost under Distributed Generation injection from private vendors. Soft computing techniques are finding increasing applications in solving optimization problems in large and complex practical systems. The dissertation focuses on Genetic Algorithm for investigating the economic aspects of distributed generation penetration without compromising the operational security of the distribution system. The work presents a methodology for determining the optimal pricing of distributed generation that would help utilities make a decision on how to operate their system economically. This would enable modular and flexible investments that have real benefits to the electric distribution system. Improved reliability for both customers and the distribution system in general, reduced environmental impacts, increased efficiency of energy use, and reduced costs of energy services are some advantages.

An adaptive random search for short term generation scheduling with network constraints.

PubMed

Marmolejo, J A; Velasco, Jonás; Selley, Héctor J

2017-01-01

This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

GENERIC VERIFICATION PROTOCOL: DISTRIBUTED GENERATION AND COMBINED HEAT AND POWER FIELD TESTING PROTOCOL

EPA Science Inventory

This report is a generic verification protocol by which EPA’s Environmental Technology Verification program tests newly developed equipment for distributed generation of electric power, usually micro-turbine generators and internal combustion engine generators. The protocol will ...

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

NASA Astrophysics Data System (ADS)

Choi, Young Hwan; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon

2017-11-01

In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Adaptive Critic-based Neurofuzzy Controller for the Steam Generator Water Level

NASA Astrophysics Data System (ADS)

Fakhrazari, Amin; Boroushaki, Mehrdad

2008-06-01

In this paper, an adaptive critic-based neurofuzzy controller is presented for water level regulation of nuclear steam generators. The problem has been of great concern for many years as the steam generator is a highly nonlinear system showing inverse response dynamics especially at low operating power levels. Fuzzy critic-based learning is a reinforcement learning method based on dynamic programming. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the backpropagation of error algorithm to tune online conclusion parts of the fuzzy inference rules. The critic agent here has a proportional-derivative structure and the fuzzy rule base has nine rules. The proposed controller shows satisfactory transient responses, disturbance rejection and robustness to model uncertainty. Its simple design procedure and structure, nominates it as one of the suitable controller designs for the steam generator water level control in nuclear power plant industry.

The Use of Complex Adaptive Systems as a Generative Metaphor in an Action Research Study of an Organisation

ERIC Educational Resources Information Center

Brown, Callum

2008-01-01

Understanding the dynamic behaviour of organisations is challenging and this study uses a model of complex adaptive systems as a generative metaphor to address this challenge. The research question addressed is: How might a conceptual model of complex adaptive systems be used to assist in understanding the dynamic nature of organisations? Using an…

Technology survey of electrical power generation and distribution for MIUS application

NASA Technical Reports Server (NTRS)

Gill, W. L.; Redding, T. E.

1975-01-01

Candidate electrical generation power systems for the modular integrated utility systems (MIUS) program are described. Literature surveys were conducted to cover both conventional and exotic generators. Heat-recovery equipment associated with conventional power systems and supporting equipment are also discussed. Typical ranges of operating conditions and generating efficiencies are described. Power distribution is discussed briefly. Those systems that appear to be applicable to MIUS have been indicated, and the criteria for equipment selection are discussed.

A Vero-cell-adapted vaccine donor strain of influenza A virus generated by serial passages.

PubMed

Hu, Weibin; Zhang, Hong; Han, Qinglin; Li, Li; Chen, Yixin; Xia, Ningshao; Chen, Ze; Shu, Yuelong; Xu, Ke; Sun, Bing

2015-01-03

A cell culture-based vaccine production system is preferred for the large-scale production of influenza vaccines and has advantages for generating vaccines against highly pathogenic influenza A viruses. Vero cells have been widely used in human vaccine manufacturing, and the safety of these cells has been well demonstrated. However, the most commonly used influenza-vaccine donor virus, A/Puerto Rico/8/1934 (PR8) virus, does not grow efficiently in Vero cells. Therefore, we adapted the PR8 virus to Vero cells by continuous passaging, and a high-growth strain was obtained after 20 passages. Sequence analysis and virological assays of the adapted strain revealed that mutations in four viral internal genes (NP, PB1, PA and NS1) were sufficient for adaptation. The recombinant virus harboring these mutations (PR8-4mut) displayed accelerated viral transport into the nucleus and increased RNP activity. Importantly, the PR8-4mut could serve as a backbone donor virus to support the growth of the H7N1, H9N2 and H5N1 avian viruses and the H1N1 and H3N2 human viruses in Vero cells without changing its pathogenicity in either chicken embryos or mice. Thus, our work describes the generation of a Vero-adapted, high-yield PR8-4mut virus that may serve as a promising candidate for an influenza-vaccine donor virus. Copyright © 2014 Elsevier Ltd. All rights reserved.

Robust distributed control of spacecraft formation flying with adaptive network topology

NASA Astrophysics Data System (ADS)

Shasti, Behrouz; Alasty, Aria; Assadian, Nima

2017-07-01

In this study, the distributed six degree-of-freedom (6-DOF) coordinated control of spacecraft formation flying in low earth orbit (LEO) has been investigated. For this purpose, an accurate coupled translational and attitude relative dynamics model of the spacecraft with respect to the reference orbit (virtual leader) is presented by considering the most effective perturbation acceleration forces on LEO satellites, i.e. the second zonal harmonic and the atmospheric drag. Subsequently, the 6-DOF coordinated control of spacecraft in formation is studied. During the mission, the spacecraft communicate with each other through a switching network topology in which the weights of its graph Laplacian matrix change adaptively based on a distance-based connectivity function between neighboring agents. Because some of the dynamical system parameters such as spacecraft masses and moments of inertia may vary with time, an adaptive law is developed to estimate the parameter values during the mission. Furthermore, for the case that there is no knowledge of the unknown and time-varying parameters of the system, a robust controller has been developed. It is proved that the stability of the closed-loop system coupled with adaptation in network topology structure and optimality and robustness in control is guaranteed by the robust contraction analysis as an incremental stability method for multiple synchronized systems. The simulation results show the effectiveness of each control method in the presence of uncertainties and parameter variations. The adaptive and robust controllers show their superiority in reducing the state error integral as well as decreasing the control effort and settling time.

60-Hz electric and magnetic fields generated by a distribution network.

PubMed

Héroux, P

1987-01-01

From a mobile unit, 60-Hz electric and magnetic fields generated by Hydro-Québec's distribution network were measured. Nine runs, representative of various human environments, were investigated. Typical values were 32 V/m and 0.16 microT. The electrical distribution networks investigated were major contributors to the electric and magnetic environments.

An adaptive grid scheme using the boundary element method

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

Munipalli, R.; Anderson, D.A.

1996-09-01

A technique to solve the Poisson grid generation equations by Green`s function related methods has been proposed, with the source terms being purely position dependent. The use of distributed singularities in the flow domain coupled with the boundary element method (BEM) formulation is presented in this paper as a natural extension of the Green`s function method. This scheme greatly simplifies the adaption process. The BEM reduces the dimensionality of the given problem by one. Internal grid-point placement can be achieved for a given boundary distribution by adding continuous and discrete source terms in the BEM formulation. A distribution of vortexmore » doublets is suggested as a means of controlling grid-point placement and grid-line orientation. Examples for sample adaption problems are presented and discussed. 15 refs., 20 figs.« less

ADAPT

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

Reynolds, John; Jankovsky, Zachary; Metzroth, Kyle G

2018-04-04

The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model various aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specifiedmore » times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at separate times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst-case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.« less

Execution time supports for adaptive scientific algorithms on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

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

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

PubMed

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-06-02

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems

PubMed Central

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G.; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-01-01

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named “CARMEN” are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances. PMID:28574426

The use of solution adaptive grids in solving partial differential equations

NASA Technical Reports Server (NTRS)

Anderson, D. A.; Rai, M. M.

1982-01-01

The grid point distribution used in solving a partial differential equation using a numerical method has a substantial influence on the quality of the solution. An adaptive grid which adjusts as the solution changes provides the best results when the number of grid points available for use during the calculation is fixed. Basic concepts used in generating and applying adaptive grids are reviewed in this paper, and examples illustrating applications of these concepts are presented.

The generation of side force by distributed suction

NASA Technical Reports Server (NTRS)

Roberts, Leonard; Hong, John

1993-01-01

This report provides an approximate analysis of the generation of side force on a cylinder placed horizontal to the flow direction by the application of distributed suction on the rearward side of the cylinder. Relationships are derived between the side force coefficients and the required suction coefficients necessary to maintain attached flow on one side of the cylinder, thereby inducing circulation around the cylinder and a corresponding side force.

Computer-generated forces in distributed interactive simulation

NASA Astrophysics Data System (ADS)

Petty, Mikel D.

1995-04-01

Distributed Interactive Simulation (DIS) is an architecture for building large-scale simulation models from a set of independent simulator nodes communicating via a common network protocol. DIS is most often used to create a simulated battlefield for military training. Computer Generated Forces (CGF) systems control large numbers of autonomous battlefield entities in a DIS simulation using computer equipment and software rather than humans in simulators. CGF entities serve as both enemy forces and supplemental friendly forces in a DIS exercise. Research into various aspects of CGF systems is ongoing. Several CGF systems have been implemented.

Effect of distributed generation installation on power loss using genetic algorithm method

NASA Astrophysics Data System (ADS)

Hasibuan, A.; Masri, S.; Othman, W. A. F. W. B.

2018-02-01

Injection of the generator distributed in the distribution network can affect the power system significantly. The effect that occurs depends on the allocation of DG on each part of the distribution network. Implementation of this approach has been made to the IEEE 30 bus standard and shows the optimum location and size of the DG which shows a decrease in power losses in the system. This paper aims to show the impact of distributed generation on the distribution system losses. The main purpose of installing DG on a distribution system is to reduce power losses on the power system.Some problems in power systems that can be solved with the installation of DG, one of which will be explored in the use of DG in this study is to reduce the power loss in the transmission line. Simulation results from case studies on the IEEE 30 bus standard system show that the system power loss decreased from 5.7781 MW to 1,5757 MW or just 27,27%. The simulated DG is injected to the bus with the lowest voltage drop on the bus number 8.

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

DTIC Science & Technology

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Generating Spatiotemporal Joint Torque Patterns from Dynamical Synchronization of Distributed Pattern Generators

PubMed Central

Pitti, Alexandre; Lungarella, Max; Kuniyoshi, Yasuo

2009-01-01

Pattern generators found in the spinal cord are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics giving to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitutes an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body's dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment). Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cord, and for exploring the motor synergies in robots. PMID:20011216

Adaptable Learning Pathway Generation with Ant Colony Optimization

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2009-01-01

One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation

PubMed Central

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2013-01-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method. PMID:23750314

Adaptive distributed video coding with correlation estimation using expectation propagation

NASA Astrophysics Data System (ADS)

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-01

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.

PubMed

Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel

2012-10-15

Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.

Molecular evolution and thermal adaptation

NASA Astrophysics Data System (ADS)

Chen, Peiqiu

2011-12-01

In this thesis, we address problems in molecular evolution, thermal adaptation, and the kinetics of adaptation of bacteria and viruses to elevated environmental temperatures. We use a nearly neutral fitness model where the replication speed of an organism is proportional to the copy number of folded proteins. Our model reproduces the distribution of stabilities of natural proteins in excellent agreement with experiment. We find that species with high mutation rates tend to have less stable proteins compared to species with low mutation rate. We found that a broad distribution of protein stabilities observed in the model and in experiment is the key determinant of thermal response for viruses and bacteria. Our results explain most of the earlier experimental observations: striking asymmetry of thermal response curves, the absence of evolutionary trade-off which was expected but not found in experiments, correlation between denaturation temperature for several protein families and the Optimal Growth Temperature (OGT) of their carrier organisms, and proximity of bacterial or viral OGTs to their evolutionary temperatures. Our theory quantitatively and with high accuracy described thermal response curves for 35 bacterial species. The model also addresses the key to adaptation is in weak-link genes (WLG), which encode least thermodynamically stable essential proteins in the proteome. We observe, as in experiment, a two-stage adaptation process. The first stage is a Luria-Delbruck type of selection, whereby rare WLG alleles, whose proteins are more stable than WLG proteins of the majority of the population (either due to standing genetic variation or due to an early acquired mutation), rapidly rise to fixation. The second stage constitutes subsequent slow accumulation of mutations in an adapted population. As adaptation progresses, selection regime changes from positive to neutral: Selection coefficient of beneficial mutations scales as a negative power of number of

Distributed generation of shared RSA keys in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Liu, Yi-Liang; Huang, Qin; Shen, Ying

2005-12-01

Mobile Ad Hoc Networks is a totally new concept in which mobile nodes are able to communicate together over wireless links in an independent manner, independent of fixed physical infrastructure and centralized administrative infrastructure. However, the nature of Ad Hoc Networks makes them very vulnerable to security threats. Generation and distribution of shared keys for CA (Certification Authority) is challenging for security solution based on distributed PKI(Public-Key Infrastructure)/CA. The solutions that have been proposed in the literature and some related issues are discussed in this paper. The solution of a distributed generation of shared threshold RSA keys for CA is proposed in the present paper. During the process of creating an RSA private key share, every CA node only has its own private security. Distributed arithmetic is used to create the CA's private share locally, and that the requirement of centralized management institution is eliminated. Based on fully considering the Mobile Ad Hoc network's characteristic of self-organization, it avoids the security hidden trouble that comes by holding an all private security share of CA, with which the security and robustness of system is enhanced.

On the generation of log-Lévy distributions and extreme randomness

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Klafter, Joseph

2011-10-01

The log-normal distribution is prevalent across the sciences, as it emerges from the combination of multiplicative processes and the central limit theorem (CLT). The CLT, beyond yielding the normal distribution, also yields the class of Lévy distributions. The log-Lévy distributions are the Lévy counterparts of the log-normal distribution, they appear in the context of ultraslow diffusion processes, and they are categorized by Mandelbrot as belonging to the class of extreme randomness. In this paper, we present a natural stochastic growth model from which both the log-normal distribution and the log-Lévy distributions emerge universally—the former in the case of deterministic underlying setting, and the latter in the case of stochastic underlying setting. In particular, we establish a stochastic growth model which universally generates Mandelbrot’s extreme randomness.

Long-term imaging of mouse embryos using adaptive harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Thayil, Anisha; Watanabe, Tomoko; Jesacher, Alexander; Wilson, Tony; Srinivas, Shankar; Booth, Martin

2011-04-01

We present a detailed description of an adaptive harmonic generation (HG) microscope and culture techniques that permit long-term, three-dimensional imaging of mouse embryos. HG signal from both pre- and postimplantation stage (0.5-5.5 day-old) mouse embryos are fully characterized. The second HG images reveal central spindles during cytokinesis whereas third HG images show several features, such as lipid droplets, nucleoli, and plasma membranes. The embryos are found to develop normally during one-day-long discontinuous HG imaging, permitting the observation of several dynamic events, such as morula compaction and blastocyst formation.

A new solution-adaptive grid generation method for transonic airfoil flow calculations

NASA Technical Reports Server (NTRS)

Nakamura, S.; Holst, T. L.

1981-01-01

The clustering algorithm is controlled by a second-order, ordinary differential equation which uses the airfoil surface density gradient as a forcing function. The solution to this differential equation produces a surface grid distribution which is automatically clustered in regions with large gradients. The interior grid points are established from this surface distribution by using an interpolation scheme which is fast and retains the desirable properties of the original grid generated from the standard elliptic equation approach.

Modeling of various heat adapter plate 4 and 6 array for optimization of thermoelectric generator element using modified diffusion equation

NASA Astrophysics Data System (ADS)

Defrianto; Tambunan, W.; Lazuardi

2017-07-01

The use of waste heat from exhaust gas and converting it to electricity is now an alternative to harvest a cheap and clean energy. Thermoelectric generator (TEG) has the ability to directly recover such waste heat and generate electricity. The aim of this study is to simulate the heat transfer on the aluminum adapter plate for homogeneity temperature distribution coupled with hot side of TEG type 40-40-10/100 from Firma Eureka and adjust their high temperatures to the TEG operating temperature to avoid the element damage. Modelling was carried out using MATLAB modified diffusion equation with Dirichlet boundary conditions at defined temperature which has been set at the ends of the heat source at 463K and 373K ± 10% on the hot side of the TEG element. The use of nylon insulated material is modeled after Neumann boundary condition in which the temperature gradient is ∂T/∂n = 0 out of boundary. Realization of the modelling is done by designing a heat conductive plate using software ACAD 2015 and converted into a binary file format of Mathlab to form a finite element mesh with geometry variations of solid model. The solid cubic model of aluminum adapter plate has a dimension of 40mm length, 40mm width and also 20mm, 30mm and 40mm thickness arranged in two arrays of 2×2 and 2×3 of TEG elements. Results showed a temperature decrease about 40.95% and 50.02% respectively from the initial source and appropriate with TEG temperature tolerance.

Distributed feedback laser diode integrated with distributed Bragg reflector for continuous-wave terahertz generation.

PubMed

Kim, Namje; Han, Sang-Pil; Ryu, Han-Cheol; Ko, Hyunsung; Park, Jeong-Woo; Lee, Donghun; Jeon, Min Yong; Park, Kyung Hyun

2012-07-30

A widely tunable dual mode laser diode with a single cavity structure is demonstrated. This novel device consists of a distributed feedback (DFB) laser diode and distributed Bragg reflector (DBR). Micro-heaters are integrated on the top of each section for continuous and independent wavelength tuning of each mode. By using a single gain medium in the DFB section, an effective common optical cavity and common modes are realized. The laser diode shows a wide tunability of the optical beat frequency, from 0.48 THz to over 2.36 THz. Continuous wave THz radiation is also successfully generated with low-temperature grown InGaAs photomixers from 0.48 GHz to 1.5 THz.

Future impacts of distributed power generation on ambient ozone and particulate matter concentrations in the San Joaquin Valley of California.

PubMed

Vutukuru, Satish; Carreras-Sospedra, Marc; Brouwer, Jacob; Dabdub, Donald

2011-12-01

Distributed power generation-electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin-has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.

Center for Adaptive Optics | Software

Science.gov Websites

Center for Adaptive Optics A University of California Science and Technology Center home Adaptive Optics Software The Center for Adaptive Optics acts as a clearing house for distributing Software to Institutes it gives specialists in Adaptive Optics a place to distribute their software. All software is

Adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope

NASA Astrophysics Data System (ADS)

Ma, Haotong; Hu, Haojun; Xie, Wenke; Zhao, Haichuan; Xu, Xiaojun; Chen, Jinbao

2013-08-01

We demonstrate the adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope based on the stochastic parallel gradient descent (SPGD) algorithm and dual phase only liquid crystal spatial light modulators (LC-SLMs). Adaptive pre-compensation the wavefront of projected laser beam at the transmitter telescope is chosen to improve the power coupling efficiency. One phase only LC-SLM adaptively optimizes phase distribution of the projected laser beam and the other generates turbulence phase screen. The intensity distributions of the dark hollow beam after passing through the turbulent atmosphere with and without adaptive beam shaping are analyzed in detail. The influence of propagation distance and aperture size of the Cassegrain-telescope on coupling efficiency are investigated theoretically and experimentally. These studies show that the power coupling can be significantly improved by adaptive beam shaping. The technique can be used in optical communication, deep space optical communication and relay mirror.

Adaptive Differentiation of Quantitative Traits in the Globally Distributed Weed, Wild Radish (Raphanus raphanistrum)

PubMed Central

Sahli, Heather F.; Conner, Jeffrey K.; Shaw, Frank H.; Howe, Stephen; Lale, Allison

2008-01-01

Weedy species with wide geographical distributions may face strong selection to adapt to new environments, which can lead to adaptive genetic differentiation among populations. However, genetic drift, particularly due to founder effects, will also commonly result in differentiation in colonizing species. To test whether selection has contributed to trait divergence, we compared differentiation at eight microsatellite loci (measured as FST) to differentiation of quantitative floral and phenological traits (measured as QST) of wild radish (Raphanus raphanistrum) across populations from three continents. We sampled eight populations: seven naturalized populations and one from its native range. By comparing estimates of QST and FST, we found that petal size was the only floral trait that may have diverged more than expected due to drift alone, but inflorescence height, flowering time, and rosette formation have greatly diverged between the native and nonnative populations. Our results suggest the loss of a rosette and the evolution of early flowering time may have been the key adaptations enabling wild radish to become a major agricultural weed. Floral adaptation to different pollinators does not seem to have been as necessary for the success of wild radish in new environments. PMID:18854585

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2008-01-01

A new approach for distribution of grid points on the surface and in the volume has been developed and implemented in the NASA unstructured grid generation code VGRID. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

NASA Technical Reports Server (NTRS)

Dunne, Rob; Schatz, Sae; Flore, Stephen M.; Nicholson, Denise

2011-01-01

Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

Adaptive unstructured triangular mesh generation and flow solvers for the Navier-Stokes equations at high Reynolds number

NASA Technical Reports Server (NTRS)

Ashford, Gregory A.; Powell, Kenneth G.

1995-01-01

A method for generating high quality unstructured triangular grids for high Reynolds number Navier-Stokes calculations about complex geometries is described. Careful attention is paid in the mesh generation process to resolving efficiently the disparate length scales which arise in these flows. First the surface mesh is constructed in a way which ensures that the geometry is faithfully represented. The volume mesh generation then proceeds in two phases thus allowing the viscous and inviscid regions of the flow to be meshed optimally. A solution-adaptive remeshing procedure which allows the mesh to adapt itself to flow features is also described. The procedure for tracking wakes and refinement criteria appropriate for shock detection are described. Although at present it has only been implemented in two dimensions, the grid generation process has been designed with the extension to three dimensions in mind. An implicit, higher-order, upwind method is also presented for computing compressible turbulent flows on these meshes. Two recently developed one-equation turbulence models have been implemented to simulate the effects of the fluid turbulence. Results for flow about a RAE 2822 airfoil and a Douglas three-element airfoil are presented which clearly show the improved resolution obtainable.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

Future Impacts of Distributed Power Generation on Ambient Ozone and Particulate Matter Concentrations in the San Joaquin Valley of California.

PubMed

Vutukuru, Satish; Carreras-Sospedra, Marc; Brouwer, Jacob; Dabdub, Donald

2011-12-01

Distributed power generation-electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin-has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region. [Box: see text].

76 FR 60006 - Joint Europe Africa Deployment & Distribution Conference 2011: “Adapting To Challenge and Change”

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... DEPARTMENT OF DEFENSE Office of the Secretary Joint Europe Africa Deployment & Distribution Conference 2011: ``Adapting To Challenge and Change'' AGENCY: United States Africa Command, Department of Defense (DoD). ACTION: Notice of conference. SUMMARY: This document announces that U.S. Africa Command...

Statistical Inference for Data Adaptive Target Parameters.

PubMed

Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

2016-05-01

Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

Modelling airway smooth muscle passive length adaptation via thick filament length distributions

PubMed Central

Donovan, Graham M.

2013-01-01

We present a new model of airway smooth muscle (ASM), which surrounds and constricts every airway in the lung and thus plays a central role in the airway constriction associated with asthma. This new model of ASM is based on an extension of sliding filament/crossbridge theory, which explicitly incorporates the length distribution of thick sliding filaments to account for a phenomenon known as dynamic passive length adaptation; the model exhibits good agreement with experimental data for ASM force–length behaviour across multiple scales. Principally these are (nonlinear) force–length loops at short timescales (seconds), parabolic force–length curves at medium timescales (minutes) and length adaptation at longer timescales. This represents a significant improvement on the widely-used cross-bridge models which work so well in or near the isometric regime, and may have significant implications for studies which rely on crossbridge or other dynamic airway smooth muscle models, and thus both airway and lung dynamics. PMID:23721681

Probabilistic #D data fusion for multiresolution surface generation

NASA Technical Reports Server (NTRS)

Manduchi, R.; Johnson, A. E.

2002-01-01

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation.

PubMed

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus F X

2007-08-30

Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from ftp://ftpmips.gsf.de/plants/apollo_webservice.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation

PubMed Central

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus FX

2007-01-01

Background Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. Results To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. Conclusion This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from . PMID:17760972

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

NASA Astrophysics Data System (ADS)

Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

2018-03-01

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

Small RNA Library Preparation Method for Next-Generation Sequencing Using Chemical Modifications to Prevent Adapter Dimer Formation.

PubMed

Shore, Sabrina; Henderson, Jordana M; Lebedev, Alexandre; Salcedo, Michelle P; Zon, Gerald; McCaffrey, Anton P; Paul, Natasha; Hogrefe, Richard I

2016-01-01

For most sample types, the automation of RNA and DNA sample preparation workflows enables high throughput next-generation sequencing (NGS) library preparation. Greater adoption of small RNA (sRNA) sequencing has been hindered by high sample input requirements and inherent ligation side products formed during library preparation. These side products, known as adapter dimer, are very similar in size to the tagged library. Most sRNA library preparation strategies thus employ a gel purification step to isolate tagged library from adapter dimer contaminants. At very low sample inputs, adapter dimer side products dominate the reaction and limit the sensitivity of this technique. Here we address the need for improved specificity of sRNA library preparation workflows with a novel library preparation approach that uses modified adapters to suppress adapter dimer formation. This workflow allows for lower sample inputs and elimination of the gel purification step, which in turn allows for an automatable sRNA library preparation protocol.

Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators

PubMed Central

2015-01-01

This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters. PMID:26451391

Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators.

PubMed

Chen, Ming-Hung

2015-01-01

This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters.

Distributed Generators Allocation in Radial Distribution Systems with Load Growth using Loss Sensitivity Approach

NASA Astrophysics Data System (ADS)

Kumar, Ashwani; Vijay Babu, P.; Murty, V. V. S. N.

2017-06-01

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of distributed generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. The objective of the paper is to reduce the power losses and improve the voltage profile of the radial distribution system with optimal allocation of the multiple DG in the system. The main contribution in this paper is (i) combined power loss sensitivity (CPLS) based method for multiple DG locations, (ii) determination of optimal sizes for multiple DG units at unity and lagging power factor, (iii) impact of DG installed at optimal, that is, combined load power factor on the system performance, (iv) impact of load growth on optimal DG planning, (v) Impact of DG integration in distribution systems on voltage stability index, (vi) Economic and technical Impact of DG integration in the distribution systems. The load growth factor has been considered in the study which is essential for planning and expansion of the existing systems. The technical and economic aspects are investigated in terms of improvement in voltage profile, reduction in total power losses, cost of energy loss, cost of power obtained from DG, cost of power intake from the substation, and savings in cost of energy loss. The results are obtained on IEEE 69-bus radial distribution systems and also compared with other existing methods.

Adaptive spatial filtering of daytime sky noise in a satellite quantum key distribution downlink receiver

NASA Astrophysics Data System (ADS)

Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.

2016-02-01

Spatial filtering is an important technique for reducing sky background noise in a satellite quantum key distribution downlink receiver. Atmospheric turbulence limits the extent to which spatial filtering can reduce sky noise without introducing signal losses. Using atmospheric propagation and compensation simulations, the potential benefit of adaptive optics (AO) to secure key generation (SKG) is quantified. Simulations are performed assuming optical propagation from a low-Earth-orbit satellite to a terrestrial receiver that includes AO. Higher-order AO correction is modeled assuming a Shack-Hartmann wavefront sensor and a continuous-face-sheet deformable mirror. The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain wave-optics hardware emulator. SKG rates are calculated for a decoy-state protocol as a function of the receiver field of view for various strengths of turbulence, sky radiances, and pointing angles. The results show that at fields of view smaller than those discussed by others, AO technologies can enhance SKG rates in daylight and enable SKG where it would otherwise be prohibited as a consequence of background optical noise and signal loss due to propagation and turbulence effects.

Adaptive Problem Solving

DTIC Science & Technology

2017-03-01

AFRL-AFOSR-JP-TR-2017-0026 Adaptive Problem Solving Michael Barley THE UNIVERSITY OF AUCKLAND Final Report 03/01/2017 DISTRIBUTION A: Distribution...May 2015 to 26 Nov 2016 4. TITLE AND SUBTITLE Adaptive Problem Solving 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386-15-1-4069 5c.  PROGRAM ELEMENT...Report for AOARD Grant FA2386-15-1-4069 “ Adaptive Problem Solving” 25 February 2017 Name of Principal Investigators (PI): Michael W. Barley - e

The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model.

PubMed

Bateman, Randall J; Benzinger, Tammie L; Berry, Scott; Clifford, David B; Duggan, Cynthia; Fagan, Anne M; Fanning, Kathleen; Farlow, Martin R; Hassenstab, Jason; McDade, Eric M; Mills, Susan; Paumier, Katrina; Quintana, Melanie; Salloway, Stephen P; Santacruz, Anna; Schneider, Lon S; Wang, Guoqiao; Xiong, Chengjie

2017-01-01

The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer's disease in autosomal dominant Alzheimer's disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation (NexGen) prevention trial. In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the National Institutes of Health, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen prevention trial. Our expanded trial toolbox consists of a disease progression model for ADAD, primary end point DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD. Copyright © 2016 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Asian medaka fishes offer new models for studying mechanisms of seawater adaptation.

PubMed

Inoue, Koji; Takei, Yoshio

2003-12-01

Japanese medaka (Oryzias latipes) is a freshwater (FW) teleost that is popular throughout the world for laboratory use. In this paper, we discuss the utility of Japanese medaka and related species for studying mechanisms of seawater (SW) adaptation. In addition to general advantages as an experimental animal such as their daily spawning activity, transparency of embryos, short generation time and established transgenic techniques, Japanese medaka have some adaptability to SW unlike the strictly stenohaline zebrafish (Danio rerio). Since other species in the genus Oryzias exhibit different degrees of adaptability to SW, comparative studies between Japanese medaka, where molecular-biological and genetic information is abundant, and other Oryzias species are expected to present varying approaches to solving the problems of SW adaptation. We introduce some examples of interspecies comparison for SW adaptabilities both in adult fish and in embryos. Oryzias species are good models for evolutionary, ecological and zoogeographical studies and a relationship between SW adaptability and geographic distribution has been suggested. Medaka fishes may thus deliver new insights into our understanding of how fish have expanded their distribution to a wide variety of osmotic environments.

Organization of Distributed Adaptive Learning

ERIC Educational Resources Information Center

Vengerov, Alexander

2009-01-01

The growing sensitivity of various systems and parts of industry, society, and even everyday individual life leads to the increased volume of changes and needs for adaptation and learning. This creates a new situation where learning from being purely academic knowledge transfer procedure is becoming a ubiquitous always-on essential part of all…

A constrained Delaunay discretization method for adaptively meshing highly discontinuous geological media

NASA Astrophysics Data System (ADS)

Wang, Yang; Ma, Guowei; Ren, Feng; Li, Tuo

2017-12-01

A constrained Delaunay discretization method is developed to generate high-quality doubly adaptive meshes of highly discontinuous geological media. Complex features such as three-dimensional discrete fracture networks (DFNs), tunnels, shafts, slopes, boreholes, water curtains, and drainage systems are taken into account in the mesh generation. The constrained Delaunay triangulation method is used to create adaptive triangular elements on planar fractures. Persson's algorithm (Persson, 2005), based on an analogy between triangular elements and spring networks, is enriched to automatically discretize a planar fracture into mesh points with varying density and smooth-quality gradient. The triangulated planar fractures are treated as planar straight-line graphs (PSLGs) to construct piecewise-linear complex (PLC) for constrained Delaunay tetrahedralization. This guarantees the doubly adaptive characteristic of the resulted mesh: the mesh is adaptive not only along fractures but also in space. The quality of elements is compared with the results from an existing method. It is verified that the present method can generate smoother elements and a better distribution of element aspect ratios. Two numerical simulations are implemented to demonstrate that the present method can be applied to various simulations of complex geological media that contain a large number of discontinuities.

New Development of Power Distribution System Resulting from Dispersed Generations and Current Interruption

NASA Astrophysics Data System (ADS)

Yokomizu, Yasunobu

Dispersed generation systems, such as micro gas-turbines and fuel cells, have been installed on some of commercial facilities. Smaller dispersed generators like solar photovoltaics have been also located on the several of individual homes. The trends in the introduction of the these generation systems seem to continue in the future and to cause the power system to have the enormous number of the dispersed generation systems. The present report discusses the near-future power distribution systems.

State estimation for distributed systems with sensing delay

NASA Astrophysics Data System (ADS)

Alexander, Harold L.

1991-08-01

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

Optimized Power Generation and Distribution Unit for Mobile Applications

DTIC Science & Technology

2006-09-01

reference commands to the overall system. This would be consistent with exoskeleton usage . Power Generation (prime mover) Power Distribution...technologies i.e. technologies that as of yet have not been used in the same field. • Produce list(s) in order of ranking for different properties ...developments have come through material science and bearing technology – it is the material properties of a flywheel that determine the maximum energy that can

Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

PubMed

Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

2014-08-01

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

Problems and Prospects of Studying Immigrant Adaptation from the 1990 Population Census: From Generational Comparisons to the Process of "Becoming American."

ERIC Educational Resources Information Center

Hirschman, Charles

1994-01-01

Examines alternative methods to measure the status of "second-generation immigrants" using 1990 Census of Population data. Research of the variations in socioeconomic adaptation by duration of American residence among immigrants who arrived as children or teenagers reveals a dominant pattern of successful adaptation with greater exposure…

Multiwavelength generation in a random distributed feedback fiber laser using an all fiber Lyot filter.

PubMed

Sugavanam, S; Yan, Z; Kamynin, V; Kurkov, A S; Zhang, L; Churkin, D V

2014-02-10

Multiwavelength lasing in the random distributed feedback fiber laser is demonstrated by employing an all fiber Lyot filter. Stable multiwavelength generation is obtained, with each line exhibiting sub-nanometer line-widths. A flat power distribution over multiple lines is obtained, which indicates that the power between lines is redistributed in nonlinear mixing processes. The multiwavelength generation is observed both in first and second Stokes waves.

Passive acoustic measurement of bedload grain size distribution using self-generated noise

NASA Astrophysics Data System (ADS)

Petrut, Teodor; Geay, Thomas; Gervaise, Cédric; Belleudy, Philippe; Zanker, Sebastien

2018-01-01

Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport process description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload grain sizes involved in elastic impacts with the river bed treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model that predicts the acoustic field generated by the collision between rigid bodies. Here we proposed an analytic model of the acoustic energy spectrum generated by the impacts between a sphere and a slab. The proposed model computes the power spectral density of bedload noise using a linear system of analytic energy spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied to real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensure high spatial and temporal resolution measurements for sediment transport in rivers.

Thermodynamic method for generating random stress distributions on an earthquake fault

USGS Publications Warehouse

Barall, Michael; Harris, Ruth A.

2012-01-01

This report presents a new method for generating random stress distributions on an earthquake fault, suitable for use as initial conditions in a dynamic rupture simulation. The method employs concepts from thermodynamics and statistical mechanics. A pattern of fault slip is considered to be analogous to a micro-state of a thermodynamic system. The energy of the micro-state is taken to be the elastic energy stored in the surrounding medium. Then, the Boltzmann distribution gives the probability of a given pattern of fault slip and stress. We show how to decompose the system into independent degrees of freedom, which makes it computationally feasible to select a random state. However, due to the equipartition theorem, straightforward application of the Boltzmann distribution leads to a divergence which predicts infinite stress. To avoid equipartition, we show that the finite strength of the fault acts to restrict the possible states of the system. By analyzing a set of earthquake scaling relations, we derive a new formula for the expected power spectral density of the stress distribution, which allows us to construct a computer algorithm free of infinities. We then present a new technique for controlling the extent of the rupture by generating a random stress distribution thousands of times larger than the fault surface, and selecting a portion which, by chance, has a positive stress perturbation of the desired size. Finally, we present a new two-stage nucleation method that combines a small zone of forced rupture with a larger zone of reduced fracture energy.

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel.

PubMed

Varrone, C; Heggeset, T M B; Le, S B; Haugen, T; Markussen, S; Skiadas, I V; Gavala, H N

2015-01-01

Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs), able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable and stable MMC, trying to overcome inhibition problems and enhance substrate degradation efficiency, as well as generation of soluble fermentation products. Repeated transfers in small batches and fed-batch conditions have been applied, comparing the use of different inoculum, growth media, and Kinetic Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h) and different dominant metabolic products were obtained, depending on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate). On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1,3-propanediol and butyrate production. Changes in microbial composition were monitored by means of Next Generation Sequencing, revealing a dominance of glycerol consuming species, such as Clostridium, Klebsiella, and Escherichia.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

NASA Astrophysics Data System (ADS)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

Residential load and rooftop PV generation: an Australian distribution network dataset

NASA Astrophysics Data System (ADS)

Ratnam, Elizabeth L.; Weller, Steven R.; Kellett, Christopher M.; Murray, Alan T.

2017-09-01

Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting 'clean' dataset, we identify key customer-specific and aggregated characteristics of rooftop PV generation and residential load.

Distributed Generation: Challenges and Opportunities, 7. edition

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

NONE

2007-10-15

The report is a comprehensive study of the Distributed Generation (DG) industry. The report takes a wide-ranging look at the current and future state of DG and both individually and collectively addresses the technologies of Microturbines, Reciprocating Engines, Stirling Engines, Fuel Cells, Photovoltaics, Concentrating Solar, Wind, and Microgrids. Topics covered include: the key technologies being used or planned for DG; the uses of DG from utility, energy service provider, and customer viewpoints; the economics of DG; the benefits of DG from multiple perspectives; the barriers that exist to implementing DG; the government programs supporting the DG industry; and, an analysismore » of DG interconnection and net metering rules.« less

Four generations of sodium guide star lasers for adaptive optics in astronomy and space situational awareness

NASA Astrophysics Data System (ADS)

d'Orgeville, Céline; Fetzer, Gregory J.

2016-07-01

This paper recalls the history of sodium guide star laser systems used in astronomy and space situational awareness adaptive optics, analyzing the impact that sodium laser technology evolution has had on routine telescope operations. While it would not be practical to describe every single sodium guide star laser system developed to date, it is possible to characterize their evolution in broad technology terms. The first generation of sodium lasers used dye laser technology to create the first sodium laser guide stars in Hawaii, California, and Spain in the late 1980s and 1990s. These experimental systems were turned into the first laser guide star facilities to equip mediumto- large diameter adaptive optics telescopes, opening a new era of Laser Guide Star Adaptive Optics (LGS AO)-enabled diffraction-limited imaging from the ground. Although they produced exciting scientific results, these laser guide star facilities were large, power-hungry and messy. In the USA, a second-generation of sodium lasers was developed in the 2000s that used cleaner, yet still large and complex, solid-state laser technology. These are the systems in routine operation at the 8 to 10m-class astronomical telescopes and 4m-class satellite imaging facilities today. Meanwhile in Europe, a third generation of sodium lasers was being developed using inherently compact and efficient fiber laser technology, and resulting in the only commercially available sodium guide star laser system to date. Fiber-based sodium lasers are being or will soon be deployed at three astronomical telescopes and two space surveillance stations. These highly promising systems are still relatively large to install on telescopes and they remain significantly expensive to procure and maintain. We are thus proposing to develop a fourth generation of sodium lasers: based on semiconductor technology, these lasers could provide a definitive solution to the problem of sodium LGS AO laser sources for all astronomy and space

An Adaptive Mesh Algorithm: Mesh Structure and Generation

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

Scannapieco, Anthony J.

2016-06-21

The purpose of Adaptive Mesh Refinement is to minimize spatial errors over the computational space not to minimize the number of computational elements. The additional result of the technique is that it may reduce the number of computational elements needed to retain a given level of spatial accuracy. Adaptive mesh refinement is a computational technique used to dynamically select, over a region of space, a set of computational elements designed to minimize spatial error in the computational model of a physical process. The fundamental idea is to increase the mesh resolution in regions where the physical variables are represented bymore » a broad spectrum of modes in k-space, hence increasing the effective global spectral coverage of those physical variables. In addition, the selection of the spatially distributed elements is done dynamically by cyclically adjusting the mesh to follow the spectral evolution of the system. Over the years three types of AMR schemes have evolved; block, patch and locally refined AMR. In block and patch AMR logical blocks of various grid sizes are overlaid to span the physical space of interest, whereas in locally refined AMR no logical blocks are employed but locally nested mesh levels are used to span the physical space. The distinction between block and patch AMR is that in block AMR the original blocks refine and coarsen entirely in time, whereas in patch AMR the patches change location and zone size with time. The type of AMR described herein is a locally refi ned AMR. In the algorithm described, at any point in physical space only one zone exists at whatever level of mesh that is appropriate for that physical location. The dynamic creation of a locally refi ned computational mesh is made practical by a judicious selection of mesh rules. With these rules the mesh is evolved via a mesh potential designed to concentrate the nest mesh in regions where the physics is modally dense, and coarsen zones in regions where the physics is

Electron distribution function in a plasma generated by fission fragments

NASA Technical Reports Server (NTRS)

Hassan, H. A.; Deese, J. E.

1976-01-01

A Boltzmann equation formulation is presented for the determination of the electron distribution function in a plasma generated by fission fragments. The formulation takes into consideration ambipolar diffusion, elastic and inelastic collisions, recombination and ionization, and allows for the fact that the primary electrons are not monoenergetic. Calculations for He in a tube coated with fissionable material shows that, over a wide pressure and neutron flux range, the distribution function is non-Maxwellian, but the electrons are essentially thermal. Moreover, about a third of the energy of the primary electrons is transferred into the inelastic levels of He. This fraction of energy transfer is almost independent of pressure and neutron flux.

Historical and Current U.S. Strategies for Boosting Distributed Generation (Chinese Translation)

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

Lowder, Travis; Schwabe, Paul; Zhou, Ella

2015-08-01

This is the Chinese translation of NREL/TP-6A20-64843. This report seeks to introduce a variety of top-down and bottom-up practices that, in concert with the macro-environment of cost-reduction globally and early adoption in Europe, helped boost the distributed generation photovoltaic market in the United States. These experiences may serve as a reference in China's quest to promote distributed renewable energy.

Distributed wavefront reconstruction with SABRE for real-time large scale adaptive optics control

NASA Astrophysics Data System (ADS)

Brunner, Elisabeth; de Visser, Cornelis C.; Verhaegen, Michel

2014-08-01

We present advances on Spline based ABerration REconstruction (SABRE) from (Shack-)Hartmann (SH) wavefront measurements for large-scale adaptive optics systems. SABRE locally models the wavefront with simplex B-spline basis functions on triangular partitions which are defined on the SH subaperture array. This approach allows high accuracy through the possible use of nonlinear basis functions and great adaptability to any wavefront sensor and pupil geometry. The main contribution of this paper is a distributed wavefront reconstruction method, D-SABRE, which is a 2 stage procedure based on decomposing the sensor domain into sub-domains each supporting a local SABRE model. D-SABRE greatly decreases the computational complexity of the method and removes the need for centralized reconstruction while obtaining a reconstruction accuracy for simulated E-ELT turbulences within 1% of the global method's accuracy. Further, a generalization of the methodology is proposed making direct use of SH intensity measurements which leads to an improved accuracy of the reconstruction compared to centroid algorithms using spatial gradients.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

NASA Technical Reports Server (NTRS)

1999-01-01

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

Performance of finite order distribution-generated universal portfolios

NASA Astrophysics Data System (ADS)

Pang, Sook Theng; Liew, How Hui; Chang, Yun Fah

2017-04-01

A Constant Rebalanced Portfolio (CRP) is an investment strategy which reinvests by redistributing wealth equally among a set of stocks. The empirical performance of the distribution-generated universal portfolio strategies are analysed experimentally concerning 10 higher volume stocks from different categories in Kuala Lumpur Stock Exchange. The time interval of study is from January 2000 to December 2015, which includes the credit crisis from September 2008 to March 2009. The performance of the finite-order universal portfolio strategies has been shown to be better than Constant Rebalanced Portfolio with some selected parameters of proposed universal portfolios.

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling the Impacts of Solar Distributed Generation on U.S. Water Resources

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

Amanda, Smith; Omitaomu, Olufemi A; Jaron, Peck

2015-01-01

Distributed electric power generation technologies typically use little or no water per unit of electrical energy produced; in particular, renewable energy sources such as solar PV systems do not require cooling systems and present an opportunity to reduce water usage for power generation. Within the US, the fuel mix used for power generation varies regionally, and certain areas use more water for power generation than others. The need to reduce water usage for power generation is even more urgent in view of climate change uncertainties. In this paper, we present an example case within the state of Tennessee, one ofmore » the top four states in water consumption for power generation and one of the states with little or no potential for developing centralized renewable energy generations. The potential for developing PV generation within Knox County, Tennessee, is studied, along with the potential for reducing water withdrawal and consumption within the Tennessee Valley stream region. Electric power generation plants in the region are quantified for their electricity production and expected water withdrawal and consumption over one year, where electrical generation data is provided over one year and water usage is modeled based on the cooling system(s) in use. Potential solar PV electrical production is modeled based on LiDAR data and weather data for the same year. Our proposed methodology can be summarized as follows: First, the potential solar generation is compared against the local grid demand. Next, electrical generation reductions are specified that would result in a given reduction in water withdrawal and a given reduction in water consumption, and compared with the current water withdrawal and consumption rates for the existing fuel mix. The increase in solar PV development that would produce an equivalent amount of power, is determined. In this way, we consider how targeted local actions may affect the larger stream region through thoughtful energy

The Formative Method for Adapting Psychotherapy (FMAP): A community-based developmental approach to culturally adapting therapy

PubMed Central

Hwang, Wei-Chin

2010-01-01

How do we culturally adapt psychotherapy for ethnic minorities? Although there has been growing interest in doing so, few therapy adaptation frameworks have been developed. The majority of these frameworks take a top-down theoretical approach to adapting psychotherapy. The purpose of this paper is to introduce a community-based developmental approach to modifying psychotherapy for ethnic minorities. The Formative Method for Adapting Psychotherapy (FMAP) is a bottom-up approach that involves collaborating with consumers to generate and support ideas for therapy adaptation. It involves 5-phases that target developing, testing, and reformulating therapy modifications. These phases include: (a) generating knowledge and collaborating with stakeholders (b) integrating generated information with theory and empirical and clinical knowledge, (c) reviewing the initial culturally adapted clinical intervention with stakeholders and revising the culturally adapted intervention, (d) testing the culturally adapted intervention, and (e) finalizing the culturally adapted intervention. Application of the FMAP is illustrated using examples from a study adapting psychotherapy for Chinese Americans, but can also be readily applied to modify therapy for other ethnic groups. PMID:20625458

The DIAN-TU Next Generation Alzheimer’s prevention trial: adaptive design and disease progression model

PubMed Central

Bateman, Randall J.; Benzinger, Tammie L.; Berry, Scott; Clifford, David B.; Duggan, Cynthia; Fagan, Anne M.; Fanning, Kathleen; Farlow, Martin R.; Hassenstab, Jason; McDade, Eric M.; Mills, Susan; Paumier, Katrina; Quintana, Melanie; Salloway, Stephen P.; Santacruz, Anna; Schneider, Lon S.; Wang, Guoqiao; Xiong, Chengjie

2016-01-01

INTRODUCTION The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer’s disease in autosomal dominant Alzheimer’s disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation Prevention Trial (NexGen). METHODS In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the NIH, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen trial. RESULTS Our expanded trials toolbox consists of a Disease Progression Model for ADAD, primary endpoint DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD. PMID:27583651

Towards multifocal ultrasonic neural stimulation: pattern generation algorithms

NASA Astrophysics Data System (ADS)

Hertzberg, Yoni; Naor, Omer; Volovick, Alexander; Shoham, Shy

2010-10-01

Focused ultrasound (FUS) waves directed onto neural structures have been shown to dynamically modulate neural activity and excitability, opening up a range of possible systems and applications where the non-invasiveness, safety, mm-range resolution and other characteristics of FUS are advantageous. As in other neuro-stimulation and modulation modalities, the highly distributed and parallel nature of neural systems and neural information processing call for the development of appropriately patterned stimulation strategies which could simultaneously address multiple sites in flexible patterns. Here, we study the generation of sparse multi-focal ultrasonic distributions using phase-only modulation in ultrasonic phased arrays. We analyse the relative performance of an existing algorithm for generating multifocal ultrasonic distributions and new algorithms that we adapt from the field of optical digital holography, and find that generally the weighted Gerchberg-Saxton algorithm leads to overall superior efficiency and uniformity in the focal spots, without significantly increasing the computational burden. By combining phased-array FUS and magnetic-resonance thermometry we experimentally demonstrate the simultaneous generation of tightly focused multifocal distributions in a tissue phantom, a first step towards patterned FUS neuro-modulation systems and devices.

Observer-based distributed adaptive iterative learning control for linear multi-agent systems

NASA Astrophysics Data System (ADS)

Li, Jinsha; Liu, Sanyang; Li, Junmin

2017-10-01

This paper investigates the consensus problem for linear multi-agent systems from the viewpoint of two-dimensional systems when the state information of each agent is not available. Observer-based fully distributed adaptive iterative learning protocol is designed in this paper. A local observer is designed for each agent and it is shown that without using any global information about the communication graph, all agents achieve consensus perfectly for all undirected connected communication graph when the number of iterations tends to infinity. The Lyapunov-like energy function is employed to facilitate the learning protocol design and property analysis. Finally, simulation example is given to illustrate the theoretical analysis.

Methodological issues with adaptation of clinical trial design.

PubMed

Hung, H M James; Wang, Sue-Jane; O'Neill, Robert T

2006-01-01

Adaptation of clinical trial design generates many issues that have not been resolved for practical applications, though statistical methodology has advanced greatly. This paper focuses on some methodological issues. In one type of adaptation such as sample size re-estimation, only the postulated value of a parameter for planning the trial size may be altered. In another type, the originally intended hypothesis for testing may be modified using the internal data accumulated at an interim time of the trial, such as changing the primary endpoint and dropping a treatment arm. For sample size re-estimation, we make a contrast between an adaptive test weighting the two-stage test statistics with the statistical information given by the original design and the original sample mean test with a properly corrected critical value. We point out the difficulty in planning a confirmatory trial based on the crude information generated by exploratory trials. In regards to selecting a primary endpoint, we argue that the selection process that allows switching from one endpoint to the other with the internal data of the trial is not very likely to gain a power advantage over the simple process of selecting one from the two endpoints by testing them with an equal split of alpha (Bonferroni adjustment). For dropping a treatment arm, distributing the remaining sample size of the discontinued arm to other treatment arms can substantially improve the statistical power of identifying a superior treatment arm in the design. A common difficult methodological issue is that of how to select an adaptation rule in the trial planning stage. Pre-specification of the adaptation rule is important for the practicality consideration. Changing the originally intended hypothesis for testing with the internal data generates great concerns to clinical trial researchers.

A novel adaptive Cuckoo search for optimal query plan generation.

PubMed

Gomathi, Ramalingam; Sharmila, Dhandapani

2014-01-01

The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

Distributed adaptive diagnosis of sensor faults using structural response data

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-10-01

The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

Real-time generation of the Wigner distribution of complex functions using phase conjugation in photorefractive materials.

PubMed

Sun, P C; Fainman, Y

1990-09-01

An optical processor for real-time generation of the Wigner distribution of complex amplitude functions is introduced. The phase conjugation of the input signal is accomplished by a highly efficient self-pumped phase conjugator based on a 45 degrees -cut barium titanate photorefractive crystal. Experimental results on the real-time generation of Wigner distribution slices for complex amplitude two-dimensional optical functions are presented and discussed.

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

USGS Publications Warehouse

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

Ionic Liquids for Utilization of Waste Heat from Distributed Power Generation Systems

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

Joan F. Brennecke; Mihir Sen; Edward J. Maginn

2009-01-11

The objective of this research project was the development of ionic liquids to capture and utilize waste heat from distributed power generation systems. Ionic Liquids (ILs) are organic salts that are liquid at room temperature and they have the potential to make fundamental and far-reaching changes in the way we use energy. In particular, the focus of this project was fundamental research on the potential use of IL/CO2 mixtures in absorption-refrigeration systems. Such systems can provide cooling by utilizing waste heat from various sources, including distributed power generation. The basic objectives of the research were to design and synthesize ILsmore » appropriate for the task, to measure and model thermophysical properties and phase behavior of ILs and IL/CO2 mixtures, and to model the performance of IL/CO2 absorption-refrigeration systems.« less

Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF

NASA Astrophysics Data System (ADS)

Feng, Maoyuan; Liu, Pan; Guo, Shenglian; Shi, Liangsheng; Deng, Chao; Ming, Bo

2017-08-01

Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.

High speed and adaptable error correction for megabit/s rate quantum key distribution.

PubMed

Dixon, A R; Sato, H

2014-12-02

Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90-94% of the ideal secure key rate over all fibre distances from 0-80 km.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

Treesearch

R.A. Payn; M.N. Gooseff; B.L. McGlynn; K.E. Bencala; S.M. Wondzell

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores...

Adapt

NASA Astrophysics Data System (ADS)

Bargatze, L. F.

2015-12-01

Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

Random Distribution Pattern and Non-adaptivity of Genome Size in a Highly Variable Population of Festuca pallens

PubMed Central

Šmarda, Petr; Bureš, Petr; Horová, Lucie

2007-01-01

Background and Aims The spatial and statistical distribution of genome sizes and the adaptivity of genome size to some types of habitat, vegetation or microclimatic conditions were investigated in a tetraploid population of Festuca pallens. The population was previously documented to vary highly in genome size and is assumed as a model for the study of the initial stages of genome size differentiation. Methods Using DAPI flow cytometry, samples were measured repeatedly with diploid Festuca pallens as the internal standard. Altogether 172 plants from 57 plots (2·25 m2), distributed in contrasting habitats over the whole locality in South Moravia, Czech Republic, were sampled. The differences in DNA content were confirmed by the double peaks of simultaneously measured samples. Key Results At maximum, a 1·115-fold difference in genome size was observed. The statistical distribution of genome sizes was found to be continuous and best fits the extreme (Gumbel) distribution with rare occurrences of extremely large genomes (positive-skewed), as it is similar for the log-normal distribution of the whole Angiosperms. Even plants from the same plot frequently varied considerably in genome size and the spatial distribution of genome sizes was generally random and unautocorrelated (P > 0·05). The observed spatial pattern and the overall lack of correlations of genome size with recognized vegetation types or microclimatic conditions indicate the absence of ecological adaptivity of genome size in the studied population. Conclusions These experimental data on intraspecific genome size variability in Festuca pallens argue for the absence of natural selection and the selective non-significance of genome size in the initial stages of genome size differentiation, and corroborate the current hypothetical model of genome size evolution in Angiosperms (Bennetzen et al., 2005, Annals of Botany 95: 127–132). PMID:17565968

Development of gravity theory application in the internalregional inter-zone commodity movement distribution with the origin zone movement generation boundary

NASA Astrophysics Data System (ADS)

Akbardin, J.; Parikesit, D.; Riyanto, B.; TMulyono, A.

2018-05-01

Zones that produce land fishery commodity and its yields have characteristics that is limited in distribution capability because infrastructure conditions availability. High demand for fishery commodities caused to a growing distribution at inefficient distribution distance. The development of the gravity theory with the limitation of movement generation from the production zone can increase the interaction inter-zones by distribution distances effectively and efficiently with shorter movement distribution distances. Regression analysis method with multiple variable of transportation infrastructure condition based on service level and quantitative capacity is determined to estimate the 'mass' of movement generation that is formed. The resulting movement distribution (Tid) model has the equation Tid = 27.04 -0.49 tid. Based on barrier function of power model with calibration value β = 0.0496. In the way of development of the movement generation 'mass' boundary at production zone will shorten the distribution distance effectively with shorter distribution distances. Shorter distribution distances will increase the accessibility inter-zones to interact according to the magnitude of the movement generation 'mass'.

Adaptive functional systems: learning with chaos.

PubMed

Komarov, M A; Osipov, G V; Burtsev, M S

2010-12-01

We propose a new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems. The model consists of a complex network of nonlinear dynamical elements producing sequences of goal-directed actions. Each element describes dynamics and activity of the functional system which is supposed to be a distributed set of interacting physiological elements such as nerve or muscle that cooperates to obtain certain goal at the level of the whole organism. During "normal" behavior, the dynamics of the system follows heteroclinic channels, but in the novel situation chaotic search is activated and a new channel leading to the target state is gradually created simulating the process of learning. The model was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations. © 2010 American Institute of Physics.

Distributed gain in plasmonic reflectors and its use for terahertz generation.

PubMed

Sydoruk, O; Syms, R R A; Solymar, L

2012-08-27

Semiconductor plasmons have potential for terahertz generation. Because practical device formats may be quasi-optical, we studied theoretically distributed plasmonic reflectors that comprise multiple interfaces between cascaded two-dimensional electron channels. Employing a mode-matching technique, we show that transmission through and reflection from a single interface depend on the magnitude and direction of a dc current flowing in the channels. As a result, plasmons can be amplified at an interface, and the cumulative effect of multiple interfaces increases the total gain, leading to plasmonic reflection coefficients exceeding unity. Reversing the current direction in a distributed reflector, however, has the opposite effect of plasmonic deamplification. Consequently, we propose structurally asymmetric resonators comprising two different distributed reflectors and predict that they are capable of terahertz oscillations at low threshold currents.

Graphene Distributed Amplifiers: Generating Desirable Gain for Graphene Field-Effect Transistors

PubMed Central

Lyu, Hongming; Lu, Qi; Huang, Yilin; Ma, Teng; Zhang, Jinyu; Wu, Xiaoming; Yu, Zhiping; Ren, Wencai; Cheng, Hui-Ming; Wu, Huaqiang; Qian, He

2015-01-01

Ever since its discovery, graphene bears great expectations in high frequency electronics due to its irreplaceably high carrier mobility. However, it has long been blamed for the weakness in generating gains, which seriously limits its pace of development. Distributed amplification, on the other hand, has successfully been used in conventional semiconductors to increase the amplifiers’ gain-bandwidth product. In this paper, distributed amplification is first applied to graphene. Transmission lines phase-synchronize paralleled graphene field-effect transistors (GFETs), combining the gain of each stage in an additive manner. Simulations were based on fabricated GFETs whose fT ranged from 8.5 GHz to 10.5 GHz and fmax from 12 GHz to 14 GHz. A simulated four-stage graphene distributed amplifier achieved up to 4 dB gain and 3.5 GHz bandwidth, which could be realized with future IC processes. A PCB level graphene distributed amplifier was fabricated as a proof of circuit concept. PMID:26634442

Automatic generation of efficient array redistribution routines for distributed memory multicomputers

NASA Technical Reports Server (NTRS)

Ramaswamy, Shankar; Banerjee, Prithviraj

1994-01-01

Appropriate data distribution has been found to be critical for obtaining good performance on Distributed Memory Multicomputers like the CM-5, Intel Paragon and IBM SP-1. It has also been found that some programs need to change their distributions during execution for better performance (redistribution). This work focuses on automatically generating efficient routines for redistribution. We present a new mathematical representation for regular distributions called PITFALLS and then discuss algorithms for redistribution based on this representation. One of the significant contributions of this work is being able to handle arbitrary source and target processor sets while performing redistribution. Another important contribution is the ability to handle an arbitrary number of dimensions for the array involved in the redistribution in a scalable manner. Our implementation of these techniques is based on an MPI-like communication library. The results presented show the low overheads for our redistribution algorithm as compared to naive runtime methods.

Microtubule Actin Cross-linking Factor 1 regulates cardiomyocyte microtubule distribution and adaptation to hemodynamic overload.

PubMed

Fassett, John T; Xu, Xin; Kwak, Dongmin; Wang, Huan; Liu, Xiaoyu; Hu, Xinli; Bache, Robert J; Chen, Yingjie

2013-01-01

Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Factor 1 (MACF1/Acf7) is a 600 kd spectraplakin that stabilizes and guides microtubule growth along actin filaments. MACF1 is expressed in the heart, but its impact on cardiac microtubules, and how this influences cardiac structure, function, and adaptation to hemodynamic overload is unknown. Here we used inducible cardiac-specific MACF1 knockout mice (MACF1 KO) to determine the impact of MACF1 on cardiac microtubules and adaptation to pressure overload (transverse aortic constriction (TAC).In adult mouse hearts, MACF1 expression was low under basal conditions, but increased significantly in response to TAC. While MACF1 KO had no observable effect on heart size or function under basal conditions, MACF1 KO exacerbated TAC induced LV hypertrophy, LV dilation and contractile dysfunction. Interestingly, subcellular fractionation of ventricular lysates revealed that MACF1 KO altered microtubule distribution in response to TAC, so that more tubulin was associated with the cell membrane fraction. Moreover, TAC induced microtubule redistribution into this cell membrane fraction in both WT and MACF1 KO mice correlated strikingly with the level of contractile dysfunction (r(2) = 0.786, p<.001). MACF1 disruption also resulted in reduction of membrane caveolin 3 levels, and increased levels of membrane PKCα and β1 integrin after TAC, suggesting MACF1 function is important for spatial regulation of several physiologically relevant signaling proteins during hypertrophy. Together, these data identify for the first time, a role for MACF1 in cardiomyocyte microtubule distribution and in adaptation to hemodynamic overload.

Topology optimization of pressure adaptive honeycomb for a morphing flap

NASA Astrophysics Data System (ADS)

Vos, Roelof; Scheepstra, Jan; Barrett, Ron

2011-03-01

The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynamic shape changes from one flight state to the next. More modern pneumatic actuators, including FAA certified autopilot servoactuators are frequently used by aircraft around the world. Pneumatic artificial muscles (PAM) show good promise as aircraft actuators, but follow the traditional model of load concentration and distribution commonly found in aircraft. A new system is proposed which leaves distributed loads distributed and manipulates structures through a distributed actuator. By using Pressure Adaptive Honeycomb (PAH), it is shown that large structural deformations in excess of 50% strains can be achieved while maintaining full structural integrity and enabling secondary flight control mechanisms like flaps. The successful implementation of pressure-adaptive honeycomb in the trailing edge of a wing section sparked the motivation for subsequent research into the optimal topology of the pressure adaptive honeycomb within the trailing edge of a morphing flap. As an input for the optimization two known shapes are required: a desired shape in cruise configuration and a desired shape in landing configuration. In addition, the boundary conditions and load cases (including aerodynamic loads and internal pressure loads) should be specified for each condition. Finally, a set of six design variables is specified relating to the honeycomb and upper skin topology of the morphing flap. A finite-element model of the pressure-adaptive honeycomb structure is developed specifically tailored to generate fast but reliable results for a given combination of external loading, input variables, and boundary conditions. Based on two bench tests it is shown that this model correlates well

Transverse momentum dependent (TMD) parton distribution functions generated in the modified DGLAP formalism based on the valence-like distributions

NASA Astrophysics Data System (ADS)

Hosseinkhani, H.; Modarres, M.; Olanj, N.

2017-07-01

Transverse momentum dependent (TMD) parton distributions, also referred to as unintegrated parton distribution functions (UPDFs), are produced via the Kimber-Martin-Ryskin (KMR) prescription. The GJR08 set of parton distribution functions (PDFs) which are based on the valence-like distributions is used, at the leading order (LO) and the next-to-leading order (NLO) approximations, as inputs of the KMR formalism. The general and the relative behaviors of the generated TMD PDFs at LO and NLO and their ratios in a wide range of the transverse momentum values, i.e. kt2 = 10, 102, 104 and 108GeV2 are investigated. It is shown that the properties of the parent valence-like PDFs are imprinted on the daughter TMD PDFs. Imposing the angular ordering constraint (AOC) leads to the dynamical variable limits on the integrals which in turn increase the contributions from the lower scales at lower kt2. The results are compared with our previous studies based on the MSTW2008 input PDFs and it is shown that the present calculation gives flatter TMD PDFs. Finally, a comparison of longitudinal structure function (FL) is made by using the produced TMD PDFs and those that were generated through the MSTW2008-LO PDF from our previous work and the corresponding data from H1 and ZEUS collaborations and a reasonable agreement is found.

Bayesian adaptive bandit-based designs using the Gittins index for multi-armed trials with normally distributed endpoints.

PubMed

Smith, Adam L; Villar, Sofía S

2018-01-01

Adaptive designs for multi-armed clinical trials have become increasingly popular recently because of their potential to shorten development times and to increase patient response. However, developing response-adaptive designs that offer patient-benefit while ensuring the resulting trial provides a statistically rigorous and unbiased comparison of the different treatments included is highly challenging. In this paper, the theory of Multi-Armed Bandit Problems is used to define near optimal adaptive designs in the context of a clinical trial with a normally distributed endpoint with known variance. We report the operating characteristics (type I error, power, bias) and patient-benefit of these approaches and alternative designs using simulation studies based on an ongoing trial. These results are then compared to those recently published in the context of Bernoulli endpoints. Many limitations and advantages are similar in both cases but there are also important differences, specially with respect to type I error control. This paper proposes a simulation-based testing procedure to correct for the observed type I error inflation that bandit-based and adaptive rules can induce.

Adaptive scallop height tool path generation for robot-based incremental sheet metal forming

NASA Astrophysics Data System (ADS)

Seim, Patrick; Möllensiep, Dennis; Störkle, Denis Daniel; Thyssen, Lars; Kuhlenkötter, Bernd

2016-10-01

Incremental sheet metal forming is an emerging process for the production of individualized products or prototypes in low batch sizes and with short times to market. In these processes, the desired shape is produced by the incremental inward motion of the workpiece-independent forming tool in depth direction and its movement along the contour in lateral direction. Based on this shape production, the tool path generation is a key factor on e.g. the resulting geometric accuracy, the resulting surface quality, and the working time. This paper presents an innovative tool path generation based on a commercial milling CAM package considering the surface quality and working time. This approach offers the ability to define a specific scallop height as an indicator of the surface quality for specific faces of a component. Moreover, it decreases the required working time for the production of the entire component compared to the use of a commercial software package without this adaptive approach. Different forming experiments have been performed to verify the newly developed tool path generation. Mainly, this approach serves to solve the existing conflict of combining the working time and the surface quality within the process of incremental sheet metal forming.

Adaptation and visual salience

PubMed Central

McDermott, Kyle C.; Malkoc, Gokhan; Mulligan, Jeffrey B.; Webster, Michael A.

2011-01-01

We examined how the salience of color is affected by adaptation to different color distributions. Observers searched for a color target on a dense background of distractors varying along different directions in color space. Prior adaptation to the backgrounds enhanced search on the same background while adaptation to orthogonal background directions slowed detection. Advantages of adaptation were seen for both contrast adaptation (to different color axes) and chromatic adaptation (to different mean chromaticities). Control experiments, including analyses of eye movements during the search, suggest that these aftereffects are unlikely to reflect simple learning or changes in search strategies on familiar backgrounds, and instead result from how adaptation alters the relative salience of the target and background colors. Comparable effects were observed along different axes in the chromatic plane or for axes defined by different combinations of luminance and chromatic contrast, consistent with visual search and adaptation mediated by multiple color mechanisms. Similar effects also occurred for color distributions characteristic of natural environments with strongly selective color gamuts. Our results are consistent with the hypothesis that adaptation may play an important functional role in highlighting the salience of novel stimuli by discounting ambient properties of the visual environment. PMID:21106682

Command generator tracker based direct model reference adaptive tracking guidance for Mars atmospheric entry

NASA Astrophysics Data System (ADS)

Li, Shuang; Peng, Yuming

2012-01-01

In order to accurately deliver an entry vehicle through the Martian atmosphere to the prescribed parachute deployment point, active Mars entry guidance is essential. This paper addresses the issue of Mars atmospheric entry guidance using the command generator tracker (CGT) based direct model reference adaptive control to reduce the adverse effect of the bounded uncertainties on atmospheric density and aerodynamic coefficients. Firstly, the nominal drag acceleration profile meeting a variety of constraints is planned off-line in the longitudinal plane as the reference model to track. Then, the CGT based direct model reference adaptive controller and the feed-forward compensator are designed to robustly track the aforementioned reference drag acceleration profile and to effectively reduce the downrange error. Afterwards, the heading alignment logic is adopted in the lateral plane to reduce the crossrange error. Finally, the validity of the guidance algorithm proposed in this paper is confirmed by Monte Carlo simulation analysis.

Can multi-generational exposure to ocean warming and acidification lead to the adaptation of life history and physiology in a marine metazoan?

PubMed

Gibbin, Emma M; Chakravarti, Leela J; Jarrold, Michael D; Christen, Felix; Turpin, Vincent; Massamba N'Siala, Gloria; Blier, Pierre U; Calosi, Piero

2017-02-15

Ocean warming and acidification are concomitant global drivers that are currently threatening the survival of marine organisms. How species will respond to these changes depends on their capacity for plastic and adaptive responses. Little is known about the mechanisms that govern plasticity and adaptability or how global changes will influence these relationships across multiple generations. Here, we exposed the emerging model marine polychaete Ophryotrocha labronica to conditions simulating ocean warming and acidification, in isolation and in combination over five generations to identify: (i) how multiple versus single global change drivers alter both juvenile and adult life-history traits; (ii) the mechanistic link between adult physiological and fitness-related life-history traits; and (iii) whether the phenotypic changes observed over multiple generations are of plastic and/or adaptive origin. Two juvenile (developmental rate; survival to sexual maturity) and two adult (average reproductive body size; fecundity) life-history traits were measured in each generation, in addition to three physiological (cellular reactive oxygen species content, mitochondrial density, mitochondrial capacity) traits. We found that multi-generational exposure to warming alone caused an increase in juvenile developmental rate, reactive oxygen species production and mitochondrial density, decreases in average reproductive body size and fecundity, and fluctuations in mitochondrial capacity, relative to control conditions. Exposure to ocean acidification alone had only minor effects on juvenile developmental rate. Remarkably, when both drivers of global change were present, only mitochondrial capacity was significantly affected, suggesting that ocean warming and acidification act as opposing vectors of stress across multiple generations. © 2017. Published by The Company of Biologists Ltd.

Adaptation of BAp crystal orientation to stress distribution in rat mandible during bone growth

NASA Astrophysics Data System (ADS)

Nakano, T.; Fujitani, W.; Ishimoto, T.; Umakoshi, Y.

2009-05-01

Biological apatite (BAp) c-axis orientation strongly depends on stress distribution in vivo and tends to align along the principal stress direction in bones. Dentulous mandible is subjected to a complicated stress condition in vivo during chewing but few studies have been carried out on the BAp c-axis orientation; so the adaptation of BAp crystal orientation to stress distribution was examined in rat dentulous mandible during bone growth and mastication. Female SD rats 4 to 14 weeks old were prepared, and the bone mineral density (BMD) and BAp crystal orientation were analyzed in a cross-section of mandible across the first molar focusing on two positions: separated from and just under the tooth root on the same cross-section perpendicular to the mesiodistal axis. The degree of BAp orientation was analyzed by a microbeam X-ray diffractometer using Cu-Kα radiation equipped with a detector of curved one-dimensional PSPC and two-dimensional PSPC in the reflection and transmission optics, respectively. BMD quickly increased during bone growth up to 14 weeks, although it was independent of the position from the tooth root. In contrast, BAp crystal orientation strongly depended on the age and the position from the tooth root, even in the same cross-section and direction, especially along the mesiodistal and the biting axes. With increased biting stress during bone growth, the degree of BAp orientation increased along the mesiodistal axis in a position separated from the tooth root more than that near the tooth root. In contrast, BAp preferential alignment clearly appeared along the biting axis near the tooth root. We conclude that BAp orientation rather than BMD sensitively adapts to local stress distribution, especially from the chewing stress in vivo in the mandible.

Distributed generation capabilities of the national energy modeling system

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

LaCommare, Kristina Hamachi; Edwards, Jennifer L.; Marnay, Chris

2003-01-01

This report describes Berkeley Lab's exploration of how the National Energy Modeling System (NEMS) models distributed generation (DG) and presents possible approaches for improving how DG is modeled. The on-site electric generation capability has been available since the AEO2000 version of NEMS. Berkeley Lab has previously completed research on distributed energy resources (DER) adoption at individual sites and has developed a DER Customer Adoption Model called DER-CAM. Given interest in this area, Berkeley Lab set out to understand how NEMS models small-scale on-site generation to assess how adequately DG is treated in NEMS, and to propose improvements or alternatives. Themore » goal is to determine how well NEMS models the factors influencing DG adoption and to consider alternatives to the current approach. Most small-scale DG adoption takes place in the residential and commercial modules of NEMS. Investment in DG ultimately offsets purchases of electricity, which also eliminates the losses associated with transmission and distribution (T&D). If the DG technology that is chosen is photovoltaics (PV), NEMS assumes renewable energy consumption replaces the energy input to electric generators. If the DG technology is fuel consuming, consumption of fuel in the electric utility sector is replaced by residential or commercial fuel consumption. The waste heat generated from thermal technologies can be used to offset the water heating and space heating energy uses, but there is no thermally activated cooling capability. This study consists of a review of model documentation and a paper by EIA staff, a series of sensitivity runs performed by Berkeley Lab that exercise selected DG parameters in the AEO2002 version of NEMS, and a scoping effort of possible enhancements and alternatives to NEMS current DG capabilities. In general, the treatment of DG in NEMS is rudimentary. The penetration of DG is determined by an economic cash-flow analysis that determines adoption based

Solid Oxide Fuel Cell Hybrid System for Distributed Power Generation

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

David Deangelis; Rich Depuy; Debashis Dey

2004-09-30

This report summarizes the work performed by Hybrid Power Generation Systems, LLC (HPGS) during the April to October 2004 reporting period in Task 2.3 (SOFC Scaleup for Hybrid and Fuel Cell Systems) under Cooperative Agreement DE-FC26-01NT40779 for the U. S. Department of Energy, National Energy Technology Laboratory (DOE/NETL), entitled ''Solid Oxide Fuel Cell Hybrid System for Distributed Power Generation''. This study analyzes the performance and economics of power generation systems for central power generation application based on Solid Oxide Fuel Cell (SOFC) technology and fueled by natural gas. The main objective of this task is to develop credible scale upmore » strategies for large solid oxide fuel cell-gas turbine systems. System concepts that integrate a SOFC with a gas turbine were developed and analyzed for plant sizes in excess of 20 MW. A 25 MW plant configuration was selected with projected system efficiency of over 65% and a factory cost of under $400/kW. The plant design is modular and can be scaled to both higher and lower plant power ratings. Technology gaps and required engineering development efforts were identified and evaluated.« less

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

PubMed

Zhang, Yaping; Hu, Kaiqiang; Beumer, Jan H; Bakkenist, Christopher J; D'Argenio, David Z

2017-04-01

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation. Copyright © 2017 Elsevier B.V. All rights reserved.

High speed and adaptable error correction for megabit/s rate quantum key distribution

PubMed Central

Dixon, A. R.; Sato, H.

2014-01-01

Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90–94% of the ideal secure key rate over all fibre distances from 0–80 km. PMID:25450416

Different spatial distributions of sodium channels in the slowly and rapidly adapting stretch receptor neuron of the crayfish.

PubMed

Lin, J H; Rydqvist, B

1999-06-05

Inward Na+ currents were studied, using a two-microelectrode intracellular voltage-clamp technique, in the slowly adapting (SA) and rapidly adapting (RA) stretch receptor neurons of the crayfish after the axons were cut at different distances from the soma. In the SA neuron, inward Na+ currents were recorded in the soma even when the axon was cut as close as 100 microm from the center of the soma, indicating the presence of Na+ channels in these parts. Also, two populations of Na+ channels seem to exist in the SA neuron. In the RA neuron, only minute Na+ currents were observed if the axon was shorter than 250 microm. The results strongly indicate that the voltage-gated Na+ channels in the SA and RA neurons have different distributions and that the difference in the spatial distribution of Na+ channel types may be important for the difference in firing properties in the two types of neurons. Copyright 1999 Elsevier Science B.V.

Rapid thermal adaptation in a marine diatom reveals constraints and tradeoffs.

PubMed

O'Donnell, Daniel R; Hamman, Carolyn R; Johnson, Evan C; Kremer, Colin T; Klausmeier, Christopher A; Litchman, Elena

2018-06-25

Rapid evolution in response to environmental change will likely be a driving force determining the distribution of species across the biosphere in coming decades. This is especially true of microorganisms, many of which may evolve in step with warming, including phytoplankton, the diverse photosynthetic microbes forming the foundation of most aquatic food webs. Here we tested the capacity of a globally important, model marine diatom Thalassiosira pseudonana, for rapid evolution in response to temperature. Selection at 16 and 31°C for 350 generations led to significant divergence in several temperature response traits, demonstrating local adaptation and the existence of tradeoffs associated with adaptation to different temperatures. In contrast, competitive ability for nitrogen (commonly limiting in marine systems), measured after 450 generations of temperature selection, did not diverge in a systematic way between temperatures. This study shows how rapid thermal adaptation affects key temperature and nutrient traits and, thus, a population's long-term physiological, ecological, and biogeographic response to climate change. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar

2010-01-01

A new approach for distribution of grid points on the surface and in the volume has been developed. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Air quality impacts of projections of natural gas-fired distributed generation

NASA Astrophysics Data System (ADS)

Horne, Jeremy R.; Carreras-Sospedra, Marc; Dabdub, Donald; Lemar, Paul; Nopmongcol, Uarporn; Shah, Tejas; Yarwood, Greg; Young, David; Shaw, Stephanie L.; Knipping, Eladio M.

2017-11-01

This study assesses the potential impacts on emissions and air quality from the increased adoption of natural gas-fired distributed generation of electricity (DG), including displacement of power from central power generation, in the contiguous United States. The study includes four major tasks: (1) modeling of distributed generation market penetration; (2) modeling of central power generation systems; (3) modeling of spatially and temporally resolved emissions; and (4) photochemical grid modeling to evaluate the potential air quality impacts of increased DG penetration, which includes both power-only DG and combined heat and power (CHP) units, for 2030. Low and high DG penetration scenarios estimate the largest penetration of future DG units in three regions - New England, New York, and California. Projections of DG penetration in the contiguous United States estimate 6.3 GW and 24 GW of market adoption in 2030 for the low DG penetration and high DG penetration scenarios, respectively. High DG penetration (all of which is natural gas-fired) serves to offset 8 GW of new natural gas combined cycle (NGCC) units, and 19 GW of solar photovoltaic (PV) installations by 2030. In all scenarios, air quality in the central United States and the northwest remains unaffected as there is little to no DG penetration in those states. California and several states in the northeast are the most impacted by emissions from DG units. Peak increases in maximum daily 8-h average ozone concentrations exceed 5 ppb, which may impede attainment of ambient air quality standards. Overall, air quality impacts from DG vary greatly based on meteorological conditions, proximity to emissions sources, the number and type of DG installations, and the emissions factors used for DG units.

Adaptation, migration or extirpation: climate change outcomes for tree populations

PubMed Central

Aitken, Sally N; Yeaman, Sam; Holliday, Jason A; Wang, Tongli; Curtis-McLane, Sierra

2008-01-01

Abstract Species distribution models predict a wholesale redistribution of trees in the next century, yet migratory responses necessary to spatially track climates far exceed maximum post-glacial rates. The extent to which populations will adapt will depend upon phenotypic variation, strength of selection, fecundity, interspecific competition, and biotic interactions. Populations of temperate and boreal trees show moderate to strong clines in phenology and growth along temperature gradients, indicating substantial local adaptation. Traits involved in local adaptation appear to be the product of small effects of many genes, and the resulting genotypic redundancy combined with high fecundity may facilitate rapid local adaptation despite high gene flow. Gene flow with preadapted alleles from warmer climates may promote adaptation and migration at the leading edge, while populations at the rear will likely face extirpation. Widespread species with large populations and high fecundity are likely to persist and adapt, but will likely suffer adaptational lag for a few generations. As all tree species will be suffering lags, interspecific competition may weaken, facilitating persistence under suboptimal conditions. Species with small populations, fragmented ranges, low fecundity, or suffering declines due to introduced insects or diseases should be candidates for facilitated migration. PMID:25567494

Connectivity-Preserving Approach for Distributed Adaptive Synchronized Tracking of Networked Uncertain Nonholonomic Mobile Robots.

PubMed

Yoo, Sung Jin; Park, Bong Seok

2017-09-06

This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.

High level continuity for coordinate generation with precise controls

NASA Technical Reports Server (NTRS)

Eiseman, P. R.

1982-01-01

Coordinate generation techniques with precise local controls have been derived and analyzed for continuity requirements up to both the first and second derivatives, and have been projected to higher level continuity requirements from the established pattern. The desired local control precision was obtained when a family of coordinate surfaces could be uniformly distributed without a consequent creation of flat spots on the coordinate curves transverse to the family. Relative to the uniform distribution, the family could be redistributed from an a priori distribution function or from a solution adaptive approach, both without distortion from the underlying transformation which may be independently chosen to fit a nontrivial geometry and topology.

The environmental genomics of metazoan thermal adaptation

PubMed Central

Porcelli, D; Butlin, R K; Gaston, K J; Joly, D; Snook, R R

2015-01-01

Continued and accelerating change in the thermal environment places an ever-greater priority on understanding how organisms are going to respond. The paradigm of ‘move, adapt or die', regarding ways in which organisms can respond to environmental stressors, stimulates intense efforts to predict the future of biodiversity. Assuming that extinction is an unpalatable outcome, researchers have focussed attention on how organisms can shift in their distribution to stay in the same thermal conditions or can stay in the same place by adapting to a changing thermal environment. How likely these respective outcomes might be depends on the answer to a fundamental evolutionary question, namely what genetic changes underpin adaptation to the thermal environment. The increasing access to and decreasing costs of next-generation sequencing (NGS) technologies, which can be applied to both model and non-model systems, provide a much-needed tool for understanding thermal adaptation. Here we consider broadly what is already known from non-NGS studies about thermal adaptation, then discuss the benefits and challenges of different NGS methodologies to add to this knowledge base. We then review published NGS genomics and transcriptomics studies of thermal adaptation to heat stress in metazoans and compare these results with previous non-NGS patterns. We conclude by summarising emerging patterns of genetic response and discussing future directions using these increasingly common techniques. PMID:25735594

Recognizing the Effects of Comprehension Language Barriers and Adaptability Cultural Barriers on Selected First-Generation Undergraduate Vietnamese Students

ERIC Educational Resources Information Center

Phan, Christian Phuoc-Lanh

2009-01-01

This investigation is about recognizing the effects of comprehension language barriers and adaptability cultural barriers on selected first-generation Vietnamese undergraduate students in the Puget Sound region of Washington State. Most Vietnamese students know little or no English before immigrating to the United States; as such, language and…

A multigrid method for steady Euler equations on unstructured adaptive grids

NASA Technical Reports Server (NTRS)

Riemslagh, Kris; Dick, Erik

1993-01-01

A flux-difference splitting type algorithm is formulated for the steady Euler equations on unstructured grids. The polynomial flux-difference splitting technique is used. A vertex-centered finite volume method is employed on a triangular mesh. The multigrid method is in defect-correction form. A relaxation procedure with a first order accurate inner iteration and a second-order correction performed only on the finest grid, is used. A multi-stage Jacobi relaxation method is employed as a smoother. Since the grid is unstructured a Jacobi type is chosen. The multi-staging is necessary to provide sufficient smoothing properties. The domain is discretized using a Delaunay triangular mesh generator. Three grids with more or less uniform distribution of nodes but with different resolution are generated by successive refinement of the coarsest grid. Nodes of coarser grids appear in the finer grids. The multigrid method is started on these grids. As soon as the residual drops below a threshold value, an adaptive refinement is started. The solution on the adaptively refined grid is accelerated by a multigrid procedure. The coarser multigrid grids are generated by successive coarsening through point removement. The adaption cycle is repeated a few times. Results are given for the transonic flow over a NACA-0012 airfoil.

Microtubule Actin Cross-Linking Factor 1 Regulates Cardiomyocyte Microtubule Distribution and Adaptation to Hemodynamic Overload

PubMed Central

Kwak, Dongmin; Wang, Huan; Liu, Xiaoyu; Hu, Xinli; Bache, Robert J.; Chen, Yingjie

2013-01-01

Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Factor 1 (MACF1/Acf7) is a 600 kd spectraplakin that stabilizes and guides microtubule growth along actin filaments. MACF1 is expressed in the heart, but its impact on cardiac microtubules, and how this influences cardiac structure, function, and adaptation to hemodynamic overload is unknown. Here we used inducible cardiac-specific MACF1 knockout mice (MACF1 KO) to determine the impact of MACF1 on cardiac microtubules and adaptation to pressure overload (transverse aortic constriction (TAC).In adult mouse hearts, MACF1 expression was low under basal conditions, but increased significantly in response to TAC. While MACF1 KO had no observable effect on heart size or function under basal conditions, MACF1 KO exacerbated TAC induced LV hypertrophy, LV dilation and contractile dysfunction. Interestingly, subcellular fractionation of ventricular lysates revealed that MACF1 KO altered microtubule distribution in response to TAC, so that more tubulin was associated with the cell membrane fraction. Moreover, TAC induced microtubule redistribution into this cell membrane fraction in both WT and MACF1 KO mice correlated strikingly with the level of contractile dysfunction (r2 = 0.786, p<.001). MACF1 disruption also resulted in reduction of membrane caveolin 3 levels, and increased levels of membrane PKCα and β1 integrin after TAC, suggesting MACF1 function is important for spatial regulation of several physiologically relevant signaling proteins during hypertrophy. Together, these data identify for the first time, a role for MACF1 in cardiomyocyte microtubule distribution and in adaptation to hemodynamic overload. PMID:24086300

NeuroTessMesh: A Tool for the Generation and Visualization of Neuron Meshes and Adaptive On-the-Fly Refinement.

PubMed

Garcia-Cantero, Juan J; Brito, Juan P; Mata, Susana; Bayona, Sofia; Pastor, Luis

2017-01-01

Gaining a better understanding of the human brain continues to be one of the greatest challenges for science, largely because of the overwhelming complexity of the brain and the difficulty of analyzing the features and behavior of dense neural networks. Regarding analysis, 3D visualization has proven to be a useful tool for the evaluation of complex systems. However, the large number of neurons in non-trivial circuits, together with their intricate geometry, makes the visualization of a neuronal scenario an extremely challenging computational problem. Previous work in this area dealt with the generation of 3D polygonal meshes that approximated the cells' overall anatomy but did not attempt to deal with the extremely high storage and computational cost required to manage a complex scene. This paper presents NeuroTessMesh, a tool specifically designed to cope with many of the problems associated with the visualization of neural circuits that are comprised of large numbers of cells. In addition, this method facilitates the recovery and visualization of the 3D geometry of cells included in databases, such as NeuroMorpho, and provides the tools needed to approximate missing information such as the soma's morphology. This method takes as its only input the available compact, yet incomplete, morphological tracings of the cells as acquired by neuroscientists. It uses a multiresolution approach that combines an initial, coarse mesh generation with subsequent on-the-fly adaptive mesh refinement stages using tessellation shaders. For the coarse mesh generation, a novel approach, based on the Finite Element Method, allows approximation of the 3D shape of the soma from its incomplete description. Subsequently, the adaptive refinement process performed in the graphic card generates meshes that provide good visual quality geometries at a reasonable computational cost, both in terms of memory and rendering time. All the described techniques have been integrated into Neuro

NeuroTessMesh: A Tool for the Generation and Visualization of Neuron Meshes and Adaptive On-the-Fly Refinement

PubMed Central

Garcia-Cantero, Juan J.; Brito, Juan P.; Mata, Susana; Bayona, Sofia; Pastor, Luis

2017-01-01

Gaining a better understanding of the human brain continues to be one of the greatest challenges for science, largely because of the overwhelming complexity of the brain and the difficulty of analyzing the features and behavior of dense neural networks. Regarding analysis, 3D visualization has proven to be a useful tool for the evaluation of complex systems. However, the large number of neurons in non-trivial circuits, together with their intricate geometry, makes the visualization of a neuronal scenario an extremely challenging computational problem. Previous work in this area dealt with the generation of 3D polygonal meshes that approximated the cells’ overall anatomy but did not attempt to deal with the extremely high storage and computational cost required to manage a complex scene. This paper presents NeuroTessMesh, a tool specifically designed to cope with many of the problems associated with the visualization of neural circuits that are comprised of large numbers of cells. In addition, this method facilitates the recovery and visualization of the 3D geometry of cells included in databases, such as NeuroMorpho, and provides the tools needed to approximate missing information such as the soma’s morphology. This method takes as its only input the available compact, yet incomplete, morphological tracings of the cells as acquired by neuroscientists. It uses a multiresolution approach that combines an initial, coarse mesh generation with subsequent on-the-fly adaptive mesh refinement stages using tessellation shaders. For the coarse mesh generation, a novel approach, based on the Finite Element Method, allows approximation of the 3D shape of the soma from its incomplete description. Subsequently, the adaptive refinement process performed in the graphic card generates meshes that provide good visual quality geometries at a reasonable computational cost, both in terms of memory and rendering time. All the described techniques have been integrated into Neuro

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Generation of dark hollow beam via coherent combination based on adaptive optics.

PubMed

Zheng, Yi; Wang, Xiaohua; Shen, Feng; Li, Xinyang

2010-12-20

A novel method for generating a dark hollow beam (DHB) is proposed and studied both theoretically and experimentally. A coherent combination technique for laser arrays is implemented based on adaptive optics (AO). A beam arraying structure and an active segmented mirror are designed and described. Piston errors are extracted by a zero-order interference detection system with the help of a custom-made photo-detectors array. An algorithm called the extremum approach is adopted to calculate feedback control signals. A dynamic piston error is imported by LiNbO₃ to test the capability of the AO servo. In a closed loop the stable and clear DHB is obtained. The experimental results confirm the feasibility of the concept.

A new generation of real-time DOS technology for mission-oriented system integration and operation

NASA Technical Reports Server (NTRS)

Jensen, E. Douglas

1988-01-01

Information is given on system integration and operation (SIO) requirements and a new generation of technical approaches for SIO. Real-time, distribution, survivability, and adaptability requirements and technical approaches are covered. An Alpha operating system program management overview is outlined.

Angular dependence of multiangle dynamic light scattering for particle size distribution inversion using a self-adapting regularization algorithm

NASA Astrophysics Data System (ADS)

Li, Lei; Yu, Long; Yang, Kecheng; Li, Wei; Li, Kai; Xia, Min

2018-04-01

The multiangle dynamic light scattering (MDLS) technique can better estimate particle size distributions (PSDs) than single-angle dynamic light scattering. However, determining the inversion range, angular weighting coefficients, and scattering angle combination is difficult but fundamental to the reconstruction for both unimodal and multimodal distributions. In this paper, we propose a self-adapting regularization method called the wavelet iterative recursion nonnegative Tikhonov-Phillips-Twomey (WIRNNT-PT) algorithm. This algorithm combines a wavelet multiscale strategy with an appropriate inversion method and could self-adaptively optimize several noteworthy issues containing the choices of the weighting coefficients, the inversion range and the optimal inversion method from two regularization algorithms for estimating the PSD from MDLS measurements. In addition, the angular dependence of the MDLS for estimating the PSDs of polymeric latexes is thoroughly analyzed. The dependence of the results on the number and range of measurement angles was analyzed in depth to identify the optimal scattering angle combination. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity of the WIRNNT-PT algorithm and the angular dependence of MDLS and show that the proposed algorithm with a six-angle analysis in the 30-130° range can be satisfactorily applied to retrieve PSDs from MDLS measurements.

Distributed source model for the full-wave electromagnetic simulation of nonlinear terahertz generation.

PubMed

Fumeaux, Christophe; Lin, Hungyen; Serita, Kazunori; Withayachumnankul, Withawat; Kaufmann, Thomas; Tonouchi, Masayoshi; Abbott, Derek

2012-07-30

The process of terahertz generation through optical rectification in a nonlinear crystal is modeled using discretized equivalent current sources. The equivalent terahertz sources are distributed in the active volume and computed based on a separately modeled near-infrared pump beam. This approach can be used to define an appropriate excitation for full-wave electromagnetic numerical simulations of the generated terahertz radiation. This enables predictive modeling of the near-field interactions of the terahertz beam with micro-structured samples, e.g. in a near-field time-resolved microscopy system. The distributed source model is described in detail, and an implementation in a particular full-wave simulation tool is presented. The numerical results are then validated through a series of measurements on square apertures. The general principle can be applied to other nonlinear processes with possible implementation in any full-wave numerical electromagnetic solver.

The Status and Outlook of Distributed Generation Public Policy in Mexico

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

Zinaman, Owen; Aznar, Alexandra Y.; Flores-Espino, Francisco

Mexico is a regional leader in setting goals for reducing greenhouse gas emissions (GHG) and distributed generation (DG) development is a key priority for the country's policymakers. Current DG policies have fostered growth but need to be modernized to serve current needs and accommodate higher penetration levels. In this report, NREL summarizes international DG policy experiences and best practices and identifies the potential opportunities for policy reform.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

NASA Astrophysics Data System (ADS)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

Optimum Boundaries of Signal-to-Noise Ratio for Adaptive Code Modulations

DTIC Science & Technology

2017-11-14

1510–1521, Feb. 2015. [2]. Pursley, M. B. and Royster, T. C., “Adaptive-rate nonbinary LDPC coding for frequency - hop communications ,” IEEE...and this can cause a very narrowband noise near the center frequency during USRP signal acquisition and generation. This can cause a high BER...Final Report APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED. AIR FORCE RESEARCH LABORATORY Space Vehicles Directorate 3550 Aberdeen Ave

A distributed parameter model of transmission line transformer for high voltage nanosecond pulse generation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Zheng; Li, Longjie; He, Jiaxin; Li, Chenjie; Wang, Yifeng; Su, Can

2017-09-01

A transmission line transformer has potential advantages for nanosecond pulse generation including excellent frequency response and no leakage inductance. The wave propagation process in a secondary mode line is indispensable due to an obvious inside transient electromagnetic transition in this scenario. The equivalent model of the transmission line transformer is crucial for predicting the output waveform and evaluating the effects of magnetic cores on output performance. However, traditional lumped parameter models are not sufficient for nanosecond pulse generation due to the natural neglect of wave propagations in secondary mode lines based on a lumped parameter assumption. In this paper, a distributed parameter model of transmission line transformer was established to investigate wave propagation in the secondary mode line and its influential factors through theoretical analysis and experimental verification. The wave propagation discontinuity in the secondary mode line induced by magnetic cores is emphasized. Characteristics of the magnetic core under a nanosecond pulse were obtained by experiments. Distribution and formation of the secondary mode current were determined for revealing essential wave propagation processes in secondary mode lines. The output waveform and efficiency were found to be affected dramatically by wave propagation discontinuity in secondary mode lines induced by magnetic cores. The proposed distributed parameter model was proved more suitable for nanosecond pulse generation in aspects of secondary mode current, output efficiency, and output waveform. In depth, comprehension of underlying mechanisms and a broader view of the working principle of the transmission line transformer for nanosecond pulse generation can be obtained through this research.

A distributed parameter model of transmission line transformer for high voltage nanosecond pulse generation.

PubMed

Li, Jiangtao; Zhao, Zheng; Li, Longjie; He, Jiaxin; Li, Chenjie; Wang, Yifeng; Su, Can

2017-09-01

A transmission line transformer has potential advantages for nanosecond pulse generation including excellent frequency response and no leakage inductance. The wave propagation process in a secondary mode line is indispensable due to an obvious inside transient electromagnetic transition in this scenario. The equivalent model of the transmission line transformer is crucial for predicting the output waveform and evaluating the effects of magnetic cores on output performance. However, traditional lumped parameter models are not sufficient for nanosecond pulse generation due to the natural neglect of wave propagations in secondary mode lines based on a lumped parameter assumption. In this paper, a distributed parameter model of transmission line transformer was established to investigate wave propagation in the secondary mode line and its influential factors through theoretical analysis and experimental verification. The wave propagation discontinuity in the secondary mode line induced by magnetic cores is emphasized. Characteristics of the magnetic core under a nanosecond pulse were obtained by experiments. Distribution and formation of the secondary mode current were determined for revealing essential wave propagation processes in secondary mode lines. The output waveform and efficiency were found to be affected dramatically by wave propagation discontinuity in secondary mode lines induced by magnetic cores. The proposed distributed parameter model was proved more suitable for nanosecond pulse generation in aspects of secondary mode current, output efficiency, and output waveform. In depth, comprehension of underlying mechanisms and a broader view of the working principle of the transmission line transformer for nanosecond pulse generation can be obtained through this research.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Modified Shuffled Frog Leaping Optimization Algorithm Based Distributed Generation Rescheduling for Loss Minimization

NASA Astrophysics Data System (ADS)

Arya, L. D.; Koshti, Atul

2018-05-01

This paper investigates the Distributed Generation (DG) capacity optimization at location based on the incremental voltage sensitivity criteria for sub-transmission network. The Modified Shuffled Frog Leaping optimization Algorithm (MSFLA) has been used to optimize the DG capacity. Induction generator model of DG (wind based generating units) has been considered for study. Standard test system IEEE-30 bus has been considered for the above study. The obtained results are also validated by shuffled frog leaping algorithm and modified version of bare bones particle swarm optimization (BBExp). The performance of MSFLA has been found more efficient than the other two algorithms for real power loss minimization problem.

Evidence for a distributed respiratory rhythm generating network in the goldfish (Carsssius auratus).

PubMed

Duchcherer, Maryana; Kottick, Andrew; Wilson, R J A

2010-01-01

Central pattern generators located in the brainstem regulate ventilatory behaviors in vertebrates. The development of the isolated brainstem preparation has allowed these neural networks to be characterized in a number of aquatic species. The aim of this study was to explore the architecture of the respiratory rhythm-generating site in the goldfish (Carassius auratus) and to determine the utility of a newly developed isolated brainstem preparation, the Sheep Dip. Here we provide evidence for a distributed organization of respiratory rhythm generating neurons along the rostrocaudal axis of the goldfish brainstem and outline the advantages of the Sheep Dip as a tool used to survey neural networks.

Are adaptation costs necessary to build up a local adaptation pattern?

PubMed

Magalhães, Sara; Blanchet, Elodie; Egas, Martijn; Olivieri, Isabelle

2009-08-03

Ecological specialization is pervasive in phytophagous arthropods. In such specialization mode, limits to host range are imposed by trade-offs preventing adaptation to several hosts. The occurrence of such trade-offs is inferred by a pattern of local adaptation, i.e., a negative correlation between relative performance on different hosts. To establish a causal link between local adaptation and trade-offs, we performed experimental evolution of spider mites on cucumber, tomato and pepper, starting from a population adapted to cucumber. Spider mites adapted to each novel host within 15 generations and no further evolution was observed at generation 25. A pattern of local adaptation was found, as lines evolving on a novel host performed better on that host than lines evolving on other hosts. However, costs of adaptation were absent. Indeed, lines adapted to tomato had similar or higher performance on pepper than lines evolving on the ancestral host (which represent the initial performance of all lines) and the converse was also true, e.g. negatively correlated responses were not observed on the alternative novel host. Moreover, adapting to novel hosts did not result in decreased performance on the ancestral host. Adaptation did not modify host ranking, as all lines performed best on the ancestral host. Furthermore, mites from all lines preferred the ancestral to novel hosts. Mate choice experiments indicated that crosses between individuals from the same or from a different selection regime were equally likely, hence development of reproductive isolation among lines adapted to different hosts is unlikely. Therefore, performance and preference are not expected to impose limits to host range in our study species. Our results show that the evolution of a local adaptation pattern is not necessarily associated with the evolution of an adaptation cost.

Adaptive Distributed Environment for Procedure Training (ADEPT)

NASA Technical Reports Server (NTRS)

Domeshek, Eric; Ong, James; Mohammed, John

2013-01-01

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive? instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Measured and predicted pressure distributions on the AFTI/F-111 mission adaptive wing

NASA Technical Reports Server (NTRS)

Webb, Lannie D.; Mccain, William E.; Rose, Lucinda A.

1988-01-01

Flight tests have been conducted using an F-111 aircraft modified with a mission adaptive wing (MAW). The MAW has variable-camber leading and trailing edge surfaces that can change the wing camber in flight, while preserving smooth upper surface contours. This paper contains wing surface pressure measurements obtained during flight tests at Dryden Flight Research Facility of NASA Ames Research Center. Upper and lower surface steady pressure distributions were measured along four streamwise rows of static pressure orifices on the right wing for a leading-edge sweep angle of 26 deg. The airplane, wing, instrumentation, and test conditions are discussed. Steady pressure results are presented for selected wing camber deflections flown at subsonic Mach numbers up to 0.90 and an angle-of-attack range of 5 to 12 deg. The Reynolds number was 26 million, based on the mean aerodynamic chord. The MAW flight data are compared to MAW wind tunnel data, transonic aircraft technology (TACT) flight data, and predicted pressure distributions. The results provide a unique database for a smooth, variable-camber, advanced supercritical wing.

Transient sequences in a hypernetwork generated by an adaptive network of spiking neurons.

PubMed

Maslennikov, Oleg V; Shchapin, Dmitry S; Nekorkin, Vladimir I

2017-06-28

We propose a model of an adaptive network of spiking neurons that gives rise to a hypernetwork of its dynamic states at the upper level of description. Left to itself, the network exhibits a sequence of transient clustering which relates to a traffic in the hypernetwork in the form of a random walk. Receiving inputs the system is able to generate reproducible sequences corresponding to stimulus-specific paths in the hypernetwork. We illustrate these basic notions by a simple network of discrete-time spiking neurons together with its FPGA realization and analyse their properties.This article is part of the themed issue 'Mathematical methods in medicine: neuroscience, cardiology and pathology'. © 2017 The Author(s).

Limits and Economic Effects of Distributed PV Generation in North and South Carolina

NASA Astrophysics Data System (ADS)

Holt, Kyra Moore

The variability of renewable sources, such as wind and solar, when integrated into the electrical system must be compensated by traditional generation sources in-order to maintain the constant balance of supply and demand required for grid stability. The goal of this study is to analyze the effects of increasing large levels of solar Photovoltaic (PV) penetration (in terms of a percentage of annual energy production) on a test grid with similar characteristics to the Duke Energy Carolinas (DEC) and Progress Energy Carolinas (PEC) regions of North and South Carolina. PV production is modeled entering the system at the distribution level and regional PV capacity is based on household density. A gridded hourly global horizontal irradiance (GHI) dataset is used to capture the variable nature of PV generation. A unit commitment model (UCM) is then used determine the hourly dispatch of generators based on generator parameters and costs to supply generation to meet demand. Annual modeled results for six different scenarios are evaluated to determine technical, environmental and economic effects of varying levels of distributed PV penetration on the system. This study finds that the main limiting factor for PV integration in the DEC and PEC balancing authority regions is defined by the large generating capacity of base-load nuclear plants within the system. This threshold starts to affect system stability at integration levels of 5.7%. System errors, defined by imbalances caused by over or under generation with respect to demand, are identified in the model however the validity of these errors in real world context needs further examination due to the lack of high frequency irradiance data and modeling limitations. Operational system costs decreased as expected with PV integration although further research is needed to explore the impacts of the capital costs required to achieve the penetration levels found in this study. PV system generation was found to mainly displace

Distributed reinforcement learning for adaptive and robust network intrusion response

NASA Astrophysics Data System (ADS)

Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

2015-07-01

Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

Transverse circular-polarized Bessel beam generation by inward cylindrical aperture distribution.

PubMed

Pavone, S C; Ettorre, M; Casaletti, M; Albani, M

2016-05-16

In this paper the focusing capability of a radiating aperture implementing an inward cylindrical traveling wave tangential electric field distribution directed along a fixed polarization unit vector is investigated. In particular, it is shown that such an aperture distribution generates a non-diffractive Bessel beam whose transverse component (with respect to the normal of the radiating aperture) of the electric field takes the form of a zero-th order Bessel function. As a practical implementation of the theoretical analysis, a circular-polarized Bessel beam launcher, made by a radial parallel plate waveguide loaded with several slot pairs, arranged on a spiral pattern, is designed and optimized. The proposed launcher performance agrees with the theoretical model and exhibits an excellent polarization purity.

Scenario generation for stochastic optimization problems via the sparse grid method

DOE PAGES

Chen, Michael; Mehrotra, Sanjay; Papp, David

2015-04-19

We study the use of sparse grids in the scenario generation (or discretization) problem in stochastic programming problems where the uncertainty is modeled using a continuous multivariate distribution. We show that, under a regularity assumption on the random function involved, the sequence of optimal objective function values of the sparse grid approximations converges to the true optimal objective function values as the number of scenarios increases. The rate of convergence is also established. We treat separately the special case when the underlying distribution is an affine transform of a product of univariate distributions, and show how the sparse grid methodmore » can be adapted to the distribution by the use of quadrature formulas tailored to the distribution. We numerically compare the performance of the sparse grid method using different quadrature rules with classic quasi-Monte Carlo (QMC) methods, optimal rank-one lattice rules, and Monte Carlo (MC) scenario generation, using a series of utility maximization problems with up to 160 random variables. The results show that the sparse grid method is very efficient, especially if the integrand is sufficiently smooth. In such problems the sparse grid scenario generation method is found to need several orders of magnitude fewer scenarios than MC and QMC scenario generation to achieve the same accuracy. As a result, it is indicated that the method scales well with the dimension of the distribution--especially when the underlying distribution is an affine transform of a product of univariate distributions, in which case the method appears scalable to thousands of random variables.« less

Transposable element islands facilitate adaptation to novel environments in an invasive species

PubMed Central

Schrader, Lukas; Kim, Jay W.; Ence, Daniel; Zimin, Aleksey; Klein, Antonia; Wyschetzki, Katharina; Weichselgartner, Tobias; Kemena, Carsten; Stökl, Johannes; Schultner, Eva; Wurm, Yannick; Smith, Christopher D.; Yandell, Mark; Heinze, Jürgen; Gadau, Jürgen; Oettler, Jan

2014-01-01

Adaptation requires genetic variation, but founder populations are generally genetically depleted. Here we sequence two populations of an inbred ant that diverge in phenotype to determine how variability is generated. Cardiocondyla obscurior has the smallest of the sequenced ant genomes and its structure suggests a fundamental role of transposable elements (TEs) in adaptive evolution. Accumulations of TEs (TE islands) comprising 7.18% of the genome evolve faster than other regions with regard to single-nucleotide variants, gene/exon duplications and deletions and gene homology. A non-random distribution of gene families, larvae/adult specific gene expression and signs of differential methylation in TE islands indicate intragenomic differences in regulation, evolutionary rates and coalescent effective population size. Our study reveals a tripartite interplay between TEs, life history and adaptation in an invasive species. PMID:25510865

Distributed parameter system coupled ARMA expansion identification and adaptive parallel IIR filtering - A unified problem statement. [Auto Regressive Moving-Average

NASA Technical Reports Server (NTRS)

Johnson, C. R., Jr.; Balas, M. J.

1980-01-01

A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.

SPANG: a SPARQL client supporting generation and reuse of queries for distributed RDF databases.

PubMed

Chiba, Hirokazu; Uchiyama, Ikuo

2017-02-08

Toward improved interoperability of distributed biological databases, an increasing number of datasets have been published in the standardized Resource Description Framework (RDF). Although the powerful SPARQL Protocol and RDF Query Language (SPARQL) provides a basis for exploiting RDF databases, writing SPARQL code is burdensome for users including bioinformaticians. Thus, an easy-to-use interface is necessary. We developed SPANG, a SPARQL client that has unique features for querying RDF datasets. SPANG dynamically generates typical SPARQL queries according to specified arguments. It can also call SPARQL template libraries constructed in a local system or published on the Web. Further, it enables combinatorial execution of multiple queries, each with a distinct target database. These features facilitate easy and effective access to RDF datasets and integrative analysis of distributed data. SPANG helps users to exploit RDF datasets by generation and reuse of SPARQL queries through a simple interface. This client will enhance integrative exploitation of biological RDF datasets distributed across the Web. This software package is freely available at http://purl.org/net/spang .

Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy.

PubMed

Masia, Lorenzo; Frascarelli, Flaminia; Morasso, Pietro; Di Rosa, Giuseppe; Petrarca, Maurizio; Castelli, Enrico; Cappa, Paolo

2011-05-21

It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Spatial abnormalities in children affected by cerebral palsy may be related not only to disturbance in

Autonomous Decentralized Control of Supply and Demand by Inverter Based Distributed Generations in Isolated Microgrid

NASA Astrophysics Data System (ADS)

Shiki, Akira; Yokoyama, Akihiko; Baba, Jyunpei; Takano, Tomihiro; Gouda, Takahiro; Izui, Yoshio

Recently, because of the environmental burden mitigation, energy conservations, energy security, and cost reductions, distributed generations are attracting our strong attention. These distributed generations (DGs) have been already installed to the distribution system, and much more DGs will be expected to be connected in the future. On the other hand, a new concept called “Microgrid” which is a small power supply network consisting of only DGs was proposed and some prototype projects are ongoing in Japan. The purpose of this paper is to develop the three-phase instantaneous valued digital simulator of microgrid consisting of a lot of inverter based DGs and to develop a supply and demand control method in isolated microgrid. First, microgrid is modeled using MATLAB/SIMULINK. We develop models of three-phase instantaneous valued inverter type CVCF generator, PQ specified generator, PV specified generator, PQ specified load as storage battery, photovoltaic generation, fuel cell and inverter load respectively. Then we propose an autonomous decentralized control method of supply and demand in isolated microgrid where storage batteries, fuel cells, photovoltaic generations and loads are connected. It is proposed here that the system frequency is used as a means to control DG output. By changing the frequency of the storage battery due to unbalance of supply and demand, all inverter based DGs detect the frequency fluctuation and change their own outputs. Finally, a new frequency control method in autonomous decentralized control of supply and demand is proposed. Though the frequency is used to transmit the information on the supply and demand unbalance to DGs, after the frequency plays the role, the frequency finally has to return to a standard value. To return the frequency to the standard value, the characteristic curve of the fuel cell is shifted in parallel. This control is carried out corresponding to the fluctuation of the load. The simulation shows that the

Generation of realistic scene using illuminant estimation and mixed chromatic adaptation

NASA Astrophysics Data System (ADS)

Kim, Jae-Chul; Hong, Sang-Gi; Kim, Dong-Ho; Park, Jong-Hyun

2003-12-01

The algorithm of combining a real image with a virtual model was proposed to increase the reality of synthesized images. Currently, synthesizing a real image with a virtual model facilitated the surface reflection model and various geometric techniques. In the current methods, the characteristics of various illuminants in the real image are not sufficiently considered. In addition, despite the chromatic adaptation plays a vital role for accommodating different illuminants in the two media viewing conditions, it is not taken into account in the existing methods. Thus, it is hardly to get high-quality synthesized images. In this paper, we proposed the two-phase image synthesis algorithm. First, the surface reflectance of the maximum high-light region (MHR) was estimated using the three eigenvectors obtained from the principal component analysis (PCA) applied to the surface reflectances of 1269 Munsell samples. The combined spectral value, i.e., the product of surface reflectance and the spectral power distributions (SPDs) of an illuminant, of MHR was then estimated using the three eigenvectors obtained from PCA applied to the products of surface reflectances of Munsell 1269 samples and the SPDs of four CIE Standard Illuminants (A, C, D50, D65). By dividing the average combined spectral values of MHR by the average surface reflectances of MHR, we could estimate the illuminant of a real image. Second, the mixed chromatic adaptation (S-LMS) using an estimated and an external illuminants was applied to the virtual-model image. For evaluating the proposed algorithm, experiments with synthetic and real scenes were performed. It was shown that the proposed method was effective in synthesizing the real and the virtual scenes under various illuminants.

Cyberwar XXI: quantifying the unquantifiable: adaptive AI for next-generation conflict simulations

NASA Astrophysics Data System (ADS)

Miranda, Joseph; von Kleinsmid, Peter; Zalewski, Tony

2004-08-01

The era of the "Revolution in Military Affairs," "4th Generation Warfare" and "Asymmetric War" requires novel approaches to modeling warfare at the operational and strategic level of modern conflict. For example, "What if, in response to our planned actions, the adversary reacts in such-and-such a manner? What will our response be? What are the possible unintended consequences?" Next generation conflict simulation tools are required to help create and test novel courses of action (COA's) in support of real-world operations. Conflict simulations allow non-lethal and cost-effective exploration of the "what-if" of COA development. The challenge has been to develop an automated decision-support software tool which allows competing COA"s to be compared in simulated dynamic environments. Principal Investigator Joseph Miranda's research is based on modeling an integrated military, economic, social, infrastructure and information (PMESII) environment. The main effort was to develop an adaptive AI engine which models agents operating within an operational-strategic conflict environment. This was implemented in Cyberwar XXI - a simulation which models COA selection in a PMESII environment. Within this framework, agents simulate decision-making processes and provide predictive capability of the potential behavior of Command Entities. The 2003 Iraq is the first scenario ready for V&V testing.

Distribution of cold adaptation proteins in microbial mats in Lake Joyce, Antarctica: Analysis of metagenomic data by using two bioinformatics tools.

PubMed

Koo, Hyunmin; Hakim, Joseph A; Fisher, Phillip R E; Grueneberg, Alexander; Andersen, Dale T; Bej, Asim K

2016-01-01

In this study, we report the distribution and abundance of cold-adaptation proteins in microbial mat communities in the perennially ice-covered Lake Joyce, located in the McMurdo Dry Valleys, Antarctica. We have used MG-RAST and R code bioinformatics tools on Illumina HiSeq2000 shotgun metagenomic data and compared the filtering efficacy of these two methods on cold-adaptation proteins. Overall, the abundance of cold-shock DEAD-box protein A (CSDA), antifreeze proteins (AFPs), fatty acid desaturase (FAD), trehalose synthase (TS), and cold-shock family of proteins (CSPs) were present in all mat samples at high, moderate, or low levels, whereas the ice nucleation protein (INP) was present only in the ice and bulbous mat samples at insignificant levels. Considering the near homogeneous temperature profile of Lake Joyce (0.08-0.29 °C), the distribution and abundance of these proteins across various mat samples predictively correlated with known functional attributes necessary for microbial communities to thrive in this ecosystem. The comparison of the MG-RAST and the R code methods showed dissimilar occurrences of the cold-adaptation protein sequences, though with insignificant ANOSIM (R = 0.357; p-value = 0.012), ADONIS (R(2) = 0.274; p-value = 0.03) and STAMP (p-values = 0.521-0.984) statistical analyses. Furthermore, filtering targeted sequences using the R code accounted for taxonomic groups by avoiding sequence redundancies, whereas the MG-RAST provided total counts resulting in a higher sequence output. The results from this study revealed for the first time the distribution of cold-adaptation proteins in six different types of microbial mats in Lake Joyce, while suggesting a simpler and more manageable user-defined method of R code, as compared to a web-based MG-RAST pipeline.

Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

NASA Astrophysics Data System (ADS)

Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

2017-08-01

With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

NASA Astrophysics Data System (ADS)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.

A visual basic program to generate sediment grain-size statistics and to extrapolate particle distributions

USGS Publications Warehouse

Poppe, L.J.; Eliason, A.H.; Hastings, M.E.

2004-01-01

Measures that describe and summarize sediment grain-size distributions are important to geologists because of the large amount of information contained in textural data sets. Statistical methods are usually employed to simplify the necessary comparisons among samples and quantify the observed differences. The two statistical methods most commonly used by sedimentologists to describe particle distributions are mathematical moments (Krumbein and Pettijohn, 1938) and inclusive graphics (Folk, 1974). The choice of which of these statistical measures to use is typically governed by the amount of data available (Royse, 1970). If the entire distribution is known, the method of moments may be used; if the next to last accumulated percent is greater than 95, inclusive graphics statistics can be generated. Unfortunately, earlier programs designed to describe sediment grain-size distributions statistically do not run in a Windows environment, do not allow extrapolation of the distribution's tails, or do not generate both moment and graphic statistics (Kane and Hubert, 1963; Collias et al., 1963; Schlee and Webster, 1967; Poppe et al., 2000)1.Owing to analytical limitations, electro-resistance multichannel particle-size analyzers, such as Coulter Counters, commonly truncate the tails of the fine-fraction part of grain-size distributions. These devices do not detect fine clay in the 0.6–0.1 μm range (part of the 11-phi and all of the 12-phi and 13-phi fractions). Although size analyses performed down to 0.6 μm microns are adequate for most freshwater and near shore marine sediments, samples from many deeper water marine environments (e.g. rise and abyssal plain) may contain significant material in the fine clay fraction, and these analyses benefit from extrapolation.The program (GSSTAT) described herein generates statistics to characterize sediment grain-size distributions and can extrapolate the fine-grained end of the particle distribution. It is written in Microsoft

Multiscale mechanobiology of de novo bone generation, remodeling and adaptation of autograft in a common ovine femur model.

PubMed

Knothe Tate, Melissa L; Dolejs, Scott; McBride, Sarah H; Matthew Miller, R; Knothe, Ulf R

2011-08-01

The link between mechanics and biology in the generation and the adaptation of bone has been studied for more than a century in the context of skeletal development and fracture healing. However, the interplay between mechanics and biology in de novo generation of bone in postnatal defects as well as healing of morcellized bone graft or massive cortical bone autografts is less well understood. To address this, here we integrate insights from our previously published studies describing the mechanobiology on both de novo bone generation and graft healing in a common ovine femoral defect model. Studying these effects in a common experimental model provides a unique opportunity to elucidate factors conducive to harnessing the regenerative power of the periosteum, and ultimately, to provide mechanistic insights into the multiscale mechanobiology of bone generation, remodeling and adaptation. Taken together, the studies indicate that, as long as adequate, directional transport of cells and molecules can be insured (e.g. with periosteum in situ or a delivery device), biological factors intrinsic to the periosteum suffice to bridge critical sized bone defects, even in the absence of a patent blood supply. Furthermore, mechanical stimuli are crucial for the success of periosteal bone generation and bone graft healing. Interestingly, areas of highest periosteal strain around defects correlate with greatest amounts albeit not greatest mineralization of newly generated bone. This may indicate a role for convection enhanced transport of cells and molecules in modulation of tissue generation by pluripotent cells that ingress into the defect center, away from the periosteum and toward the surface of the intramedullary nail that fills the medullary cavity. These insights bring us much closer to understanding the mechanobiological environment and stimuli that stimulate the proliferation and differentiation of periosteum-derived progenitor cells and ultimately drive the generation of

Local climatic adaptation in a widespread microorganism.

PubMed

Leducq, Jean-Baptiste; Charron, Guillaume; Samani, Pedram; Dubé, Alexandre K; Sylvester, Kayla; James, Brielle; Almeida, Pedro; Sampaio, José Paulo; Hittinger, Chris Todd; Bell, Graham; Landry, Christian R

2014-02-22

Exploring the ability of organisms to locally adapt is critical for determining the outcome of rapid climate changes, yet few studies have addressed this question in microorganisms. We investigated the role of a heterogeneous climate on adaptation of North American populations of the wild yeast Saccharomyces paradoxus. We found abundant among-strain variation for fitness components across a range of temperatures, but this variation was only partially explained by climatic variation in the distribution area. Most of fitness variation was explained by the divergence of genetically distinct groups, distributed along a north-south cline, suggesting that these groups have adapted to distinct climatic conditions. Within-group fitness components were correlated with climatic conditions, illustrating that even ubiquitous microorganisms locally adapt and harbour standing genetic variation for climate-related traits. Our results suggest that global climatic changes could lead to adaptation to new conditions within groups, or changes in their geographical distributions.

Projected Growth in Small-Scale, Fossil-Fueled Distributed Generation: Potential Implications for the U.S. Greenhouse Gas Inventory

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

Eberle, Annika; Heath, Garvin A

The generation capacity of small-scale (less than one megawatt) fossil-fueled electricity in the United States is anticipated to grow by threefold to twenty-fold from 2015 to 2040. However, in adherence with internationally agreed upon carbon accounting methods, the Environmental Protection Agency's (EPA's) U.S. Greenhouse Inventory (GHGI) does not currently attribute greenhouse gases (GHGs) from these small-scale distributed generation sources to the electric power sector and instead accounts for these emissions in the sector that uses the distributed generation (e.g., the commercial sector). In addition, no other federal electric-sector GHG emission data product produced by the EPA or the U.S. Energymore » Information Administration (EIA) can attribute these emissions to electricity. We reviewed the technical documentation for eight federal electric-sector GHG emission data products, interviewed the data product owners, collected their GHG emission estimates, and analyzed projections for growth in fossil-fueled distributed generation. We show that, by 2040, these small-scale generators could account for at least about 1%- 5% of total CO2 emissions from the U.S. electric power sector. If these emissions fall outside the electric power sector, the United States may not be able to completely and accurately track changes in electricity-related CO2 emissions, which could impact how the country sets GHG reduction targets and allocates mitigation resources. Because small-scale, fossil-fueled distributed generation is expected to grow in other countries as well, the results of this work also have implications for global carbon accounting.« less

Synthetic consciousness: the distributed adaptive control perspective

PubMed Central

2016-01-01

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID

Synthetic consciousness: the distributed adaptive control perspective.

PubMed

Verschure, Paul F M J

2016-08-19

Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The

Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng

2017-06-01

Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

Distributed optical fiber vibration sensing using phase-generated carrier demodulation algorithm

NASA Astrophysics Data System (ADS)

Yu, Zhihua; Zhang, Qi; Zhang, Mingyu; Dai, Haolong; Zhang, Jingjing; Liu, Li; Zhang, Lijun; Jin, Xing; Wang, Gaifang; Qi, Guang

2018-05-01

A novel optical fiber-distributed vibration-sensing system is proposed, which is based on self-interference of Rayleigh backscattering with phase-generated carrier (PGC) demodulation algorithm. Pulsed lights are sent into the sensing fiber and the Rayleigh backscattering light from a certain position along the sensing fiber would interfere through an unbalanced Michelson interferometry to generate the interference light. An improved PGC demodulation algorithm is carried out to recover the phase information of the interference signal, which carries the sensing information. Three vibration events were applied simultaneously to different positions over 2000 m sensing fiber and demodulated correctly. The spatial resolution is 10 m, and the noise level of the Φ-OTDR system we proposed is about 10-3 rad/\\surd {Hz}, and the signal-to-noise ratio is about 30.34 dB.

Stable Adaptive Inertial Control of a Doubly-Fed Induction Generator

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

Kang, Moses; Muljadi, Eduard; Hur, Kyeon

2016-11-01

This paper proposes a stable adaptive inertial control scheme of a doubly-fed induction generator. The proposed power reference is defined in two sections: the deceleration period and the acceleration period. The power reference in the deceleration period consists of a constant and the reference for maximum power point tracking (MPPT) operation. The latter contributes to preventing a second frequency dip (SFD) in this period because its reduction rate is large at the early stage of an event but quickly decreases with time. To improve the frequency nadir (FN), the constant value is set to be proportional to the rotor speedmore » prior to an event. The reference ensures that the rotor speed converges to a stable operating region. To accelerate the rotor speed while causing a small SFD, when the rotor speed converges, the power reference is reduced by a small amount and maintained until it meets the MPPT reference. The results show that the scheme causes a small SFD while improving the FN and the rate of change of frequency in any wind conditions, even in a grid that has a high penetration of wind power.« less

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

Multi-peak structure of generation spectrum of random distributed feedback fiber Raman lasers.

PubMed

Vatnik, I D; Zlobina, E A; Kablukov, S I; Babin, S A

2017-02-06

We study spectral features of the generation of random distributed feedback fiber Raman laser arising from two-peak shape of the Raman gain spectral profile realized in the germanosilicate fibers. We demonstrate that number of peaks can be calculated using power balance model considering different subcomponents within each Stokes component.

Testing the shape of distributions of weather data

NASA Astrophysics Data System (ADS)

Baccon, Ana L. P.; Lunardi, José T.

2016-08-01

The characterization of the statistical distributions of observed weather data is of crucial importance both for the construction and for the validation of weather models, such as weather generators (WG's). An important class of WG's (e.g., the Richardson-type generators) reduce the time series of each variable to a time series of its residual elements, and the residuals are often assumed to be normally distributed. In this work we propose an approach to investigate if the shape assumed for the distribution of residuals is consistent or not with the observed data of a given site. Specifically, this procedure tests if the same distribution shape for the residuals noise is maintained along the time. The proposed approach is an adaptation to climate time series of a procedure first introduced to test the shapes of distributions of growth rates of business firms aggregated in large panels of short time series. We illustrate the procedure by applying it to the residuals time series of maximum temperature in a given location, and investigate the empirical consistency of two assumptions, namely i) the most common assumption that the distribution of the residuals is Gaussian and ii) that the residuals noise has a time invariant shape which coincides with the empirical distribution of all the residuals noise of the whole time series pooled together.

Experimental comparison of PV-smoothing controllers using distributed generators

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

Johnson, Jay Dean; Ellis, Abraham; Denda, Atsushi

The power output variability of photovoltaic systems can affect local electrical grids in locations with high renewable energy penetrations or weak distribution or transmission systems. In those rare cases, quick controllable generators (e.g., energy storage systems) or loads can counteract the destabilizing effects by compensating for the power fluctuations. Previously, control algorithms for coordinated and uncoordinated operation of a small natural gas engine-generator (genset) and a battery for smoothing PV plant output were optimized using MATLAB/Simulink simulations. The simulations demonstrated that a traditional generation resource such as a natural gas genset in combination with a battery would smooth the photovoltaicmore » output while using a smaller battery state of charge (SOC) range and extending the life of the battery. This paper reports on the experimental implementation of the coordinated and uncoordinated controllers to verify the simulations and determine the differences in the controllers. The experiments were performed with the PNM PV and energy storage Prosperity site and a gas engine-generator located at the Aperture Center at Mesa Del Sol in Albuquerque, New Mexico. Two field demonstrations were performed to compare the different PV smoothing control algorithms: (1) implementing the coordinated and uncoordinated controls while switching off a subsection of the PV array at precise times on successive clear days, and (2) comparing the results of the battery and genset outputs for the coordinated control on a high variability day with simulations of the coordinated and uncoordinated controls. It was found that for certain PV power profiles the SOC range of the battery may be larger with the coordinated control, but the total amp-hours through the battery-which approximates battery wear-will always be smaller with the coordinated control.« less

The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species

Treesearch

Keith B. Aubry; Catherine M. Raley; Kevin S. McKelvey

2017-01-01

The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated...

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

PubMed

Whitacre, James M; Bender, Axel

2010-06-15

A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

Two dimensional distribution measurement of electric current generated in a polymer electrolyte fuel cell using 49 NMR surface coils.

PubMed

Ogawa, Kuniyasu; Sasaki, Tatsuyoshi; Yoneda, Shigeki; Tsujinaka, Kumiko; Asai, Ritsuko

2018-05-17

In order to increase the current density generated in a PEFC (polymer electrolyte fuel cell), a method for measuring the spatial distribution of both the current and the water content of the MEA (membrane electrode assembly) is necessary. Based on the frequency shifts of NMR (nuclear magnetic resonance) signals acquired from the water contained in the MEA using 49 NMR coils in a 7 × 7 arrangement inserted in the PEFC, a method for measuring the two-dimensional spatial distribution of electric current generated in a unit cell with a power generation area of 140 mm × 160 mm was devised. We also developed an inverse analysis method to determine the two-dimensional electric current distribution that can be applied to actual PEFC connections. Two analytical techniques, namely coarse graining of segments and stepwise search, were used to shorten the calculation time required for inverse analysis of the electric current map. Using this method and techniques, spatial distributions of electric current and water content in the MEA were obtained when the PEFC generated electric power at 100 A. Copyright © 2018 Elsevier Inc. All rights reserved.

Self-correcting random number generator

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

Humble, Travis S.; Pooser, Raphael C.

2016-09-06

A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, tomore » provide a random number according to one or more performance criteria.« less

A Distributed Fuzzy Associative Classifier for Big Data.

PubMed

Segatori, Armando; Bechini, Alessio; Ducange, Pietro; Marcelloni, Francesco

2017-09-19

Fuzzy associative classification has not been widely analyzed in the literature, although associative classifiers (ACs) have proved to be very effective in different real domain applications. The main reason is that learning fuzzy ACs is a very heavy task, especially when dealing with large datasets. To overcome this drawback, in this paper, we propose an efficient distributed fuzzy associative classification approach based on the MapReduce paradigm. The approach exploits a novel distributed discretizer based on fuzzy entropy for efficiently generating fuzzy partitions of the attributes. Then, a set of candidate fuzzy association rules is generated by employing a distributed fuzzy extension of the well-known FP-Growth algorithm. Finally, this set is pruned by using three purposely adapted types of pruning. We implemented our approach on the popular Hadoop framework. Hadoop allows distributing storage and processing of very large data sets on computer clusters built from commodity hardware. We have performed an extensive experimentation and a detailed analysis of the results using six very large datasets with up to 11,000,000 instances. We have also experimented different types of reasoning methods. Focusing on accuracy, model complexity, computation time, and scalability, we compare the results achieved by our approach with those obtained by two distributed nonfuzzy ACs recently proposed in the literature. We highlight that, although the accuracies result to be comparable, the complexity, evaluated in terms of number of rules, of the classifiers generated by the fuzzy distributed approach is lower than the one of the nonfuzzy classifiers.

Modular high-voltage bias generator powered by dual-looped self-adaptive wireless power transmission.

PubMed

Xie, Kai; Huang, An-Feng; Li, Xiao-Ping; Guo, Shi-Zhong; Zhang, Han-Lu

2015-04-01

We proposed a modular high-voltage (HV) bias generator powered by a novel transmitter-sharing inductive coupled wireless power transmission technology, aimed to extend the generator's flexibility and configurability. To solve the problems caused through an uncertain number of modules, a dual-looped self-adaptive control method is proposed that is capable of tracking resonance frequency while maintaining a relatively stable induction voltage for each HV module. The method combines a phase-locked loop and a current feedback loop, which ensures an accurate resonance state and a relatively constant boost ratio for each module, simplifying the architecture of the boost stage and improving the total efficiency. The prototype was built and tested. The input voltage drop of each module is less than 14% if the module number varies from 3 to 10; resonance tracking is completed within 60 ms. The efficiency of the coupling structure reaches up to 95%, whereas the total efficiency approaches 73% for a rated output. Furthermore, this technology can be used in various multi-load wireless power supply applications.

On the angular and energy distribution of solar neutrons generated in P-P reactions

NASA Technical Reports Server (NTRS)

Efimov, Y. E.; Kocharov, G. E.

1985-01-01

The problem of high energy neutron generation in P-P reactions in the solar atmosphere is reconsidered. It is shown that the angular distribution of emitted neutrons is anisotropic and the energy spectrum of neutrons depends on the angle of neutron emission.

Tunable microwave generation of a monolithic dual-wavelength distributed feedback laser.

PubMed

Lo, Yen-Hua; Wu, Yu-Chang; Hsu, Shun-Chieh; Hwang, Yi-Chia; Chen, Bai-Ci; Lin, Chien-Chung

2014-06-02

The dynamic behavior of a monolithic dual-wavelength distributed feedback laser was fully investigated and mapped. The combination of different driving currents for master and slave lasers can generate a wide range of different operational modes, from single mode, period 1 to chaos. Both the optical and microwave spectrum were recorded and analyzed. The detected single mode signal can continuously cover from 15GHz to 50GHz, limited by photodetector bandwidth. The measured optical four-wave-mixing pattern indicates that a 70GHz signal can be generated by this device. By applying rate equation analysis, the important laser parameters can be extracted from the spectrum. The extracted relaxation resonant frequency is found to be 8.96GHz. With the full operational map at hand, the suitable current combination can be applied to the device for proper applications.

Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation.

PubMed

Miocinovic, Svjetlana; Lempka, Scott F; Russo, Gary S; Maks, Christopher B; Butson, Christopher R; Sakaie, Ken E; Vitek, Jerrold L; McIntyre, Cameron C

2009-03-01

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks.

PubMed

Li, Zhijun; Ge, Shuzhi Sam; Liu, Sibang

2014-08-01

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

Low-cost distributed solar-thermal-electric power generation

NASA Astrophysics Data System (ADS)

Der Minassians, Artin; Aschenbach, Konrad H.; Sanders, Seth R.

2004-01-01

Due to their high relative cost, solar electric energy systems have yet to be exploited on a widespread basis. It is believed in the energy community that a technology similar to photovoltaic (PV), but offered at about $1/W would lead to widespread deployment at residential and commercial sites. This paper addresses the investigation and feasibility study of a low-cost solar thermal electricity generation technology, suitable for distributed deployment. Specifically, we discuss a system based on nonimaging solar concentrators, integrated with free-piston Stirling engine devices incorporating integrated electric generation. We target concentrator-collector operation at moderate temperatures, in the range of 125°C to 150°C. This temperature is consistent with use of optical concentrators with concentration ratios on the order of 1-2. These low ratio concentrators admit wide angles of radiation acceptance and are thus compatible with no diurnal tracking, and no or only a few seasonal adjustments. Thus, costs and reliability hazards associated with tracking hardware systems are avoided. Further, we note that in the intended application, there is no shortage of incident solar energy, but rather it is the capital cost of the solar-electric system that is most precious. Thus, we outline a strategy for exploiting solar resources in a cost constrained manner. The paper outlines design issues, and a specific design for an appropriately dimensioned free-piston Stirling engine. Only standard low-cost materials and manufacturing methods are required to realize such a machine.

Evolving Distributed Generation Support Mechanisms: Case Studies from United States, Germany, United Kingdom, and Australia

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

Lowder, Travis; Zhou, Ella; Tian, Tian

This report expands on a previous National Renewable Energy Laboratory (NREL) technical report (Lowder et al. 2015) that focused on the United States' unique approach to distributed generation photovoltaics (DGPV) support policies and business models. While the focus of that report was largely historical (i.e., detailing the policies and market developments that led to the growth of DGPV in the United States), this report looks forward, narrating recent changes to laws and regulations as well as the ongoing dialogues over how to incorporate distributed generation (DG) resources onto the electric grid. This report also broadens the scope of Lowder etmore » al. (2015) to include additional countries and technologies. DGPV and storage are the principal technologies under consideration (owing to market readiness and deployment volumes), but the report also contemplates any generation resource that is (1) on the customer side of the meter, (2) used to, at least partly, offset a host's energy consumption, and/or (3) potentially available to provide grid support (e.g., through peak shaving and load shifting, ancillary services, and other means).« less

Applying Adaptive Variables in Computerised Adaptive Testing

ERIC Educational Resources Information Center

Triantafillou, Evangelos; Georgiadou, Elissavet; Economides, Anastasios A.

2007-01-01

Current research in computerised adaptive testing (CAT) focuses on applications, in small and large scale, that address self assessment, training, employment, teacher professional development for schools, industry, military, assessment of non-cognitive skills, etc. Dynamic item generation tools and automated scoring of complex, constructed…

Influence of the external and internal parameters on the characteristics of generator PV

NASA Astrophysics Data System (ADS)

Zouli, Mounir; Ghoudelbourk, Sihem; Ouari, Ahmed; Dib, Djallel

2017-02-01

The growing demand for electric power and inevitable future depletion of conventional sources require major research on the alternative sources, like renewable energies. Among which, solar energy is the most largely used because of its many applications. And as Algeria comprises an exceptional solar layer thanks to its large surfaces, therefore it represents an important source of photovoltaic energy. The objective of this work is to be ensured that the energy produced by the photovoltaic plant supplies the electrical distribution network. The configuration of this system comprises a photovoltaic generator, connected to a chopper booster. For an optimal operation of the system, one must connect in cascades partial generators each one connected to a chopper booster adapted by an order MPPT by the method of Disturbance and Observation (P&O) to ensure the operation of their maximum powers whatever the climatic conditions, and also allows to raise the output voltage of these photovoltaic generators. The adaptation between the photovoltaic generator and the load was carried out with the help of converter DC/DC.

Belowground adaptation and resilience to drought conditions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Gentine, P.; Bras, R. L.

2012-12-01

The most expansive drought in 50 years stretched across the Midwest in 2012. In light of predicted increases in the variability of climate, this type of event can no longer be considered extreme. Understanding the resilience of both managed and natural vegetation and how these systems may adapt to this new climate reality is critical in predicting changes to the global carbon, energy and water balance. An eco-hydrological model (tRIBS+VEGGIE) was employed to model the sensitivity of vegetation to varying drought intensities. Point scale simulations were carried out using two vertical root distribution schemes: (i) Static - a temporally invariant root distribution; and (ii) Dynamic - a temporally variable root carbon allocation scheme. A stochastic climate generator was used to create a series of synthetic climate realizations varying the drought characteristics - in particular the interstorm period. This change in the seasonal distribution of precipitation impacts the spatial (soil layers) and temporal distribution of soil moisture which directly impacts the water resource niche for vegetation. This change in resource niche is reflected in a shift in the optimal static rooting strategy further highlighting the need for the incorporation of a dynamic scheme that responds to local conditions.

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid; Sohn, Andrew

1996-01-01

Dynamic mesh adaptation on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load inbalances among processors on a parallel machine. This paper described the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution coast is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35 percent of the mesh is randomly adapted. For large scale scientific computations, our load balancing strategy gives an almost sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remappier yields processor assignments that are less than 3 percent of the optimal solutions, but requires only 1 percent of the computational time.

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid; Sohn, Andrew

1996-01-01

Dynamic mesh adaption on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load imbalance among processors on a parallel machine. This paper describes the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution cost is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35% of the mesh is randomly adapted. For large-scale scientific computations, our load balancing strategy gives almost a sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remapper yields processor assignments that are less than 3% off the optimal solutions but requires only 1% of the computational time.

A distributed multichannel demand-adaptive P2P VoD system with optimized caching and neighbor-selection

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Minghua; Parekh, Abhay; Ramchandran, Kannan

2011-09-01

We design a distributed multi-channel P2P Video-on-Demand (VoD) system using "plug-and-play" helpers. Helpers are heterogenous "micro-servers" with limited storage, bandwidth and number of users they can serve simultaneously. Our proposed system has the following salient features: (1) it jointly optimizes over helper-user connection topology, video storage distribution and transmission bandwidth allocation; (2) it minimizes server load, and is adaptable to varying supply and demand patterns across multiple video channels irrespective of video popularity; and (3) it is fully distributed and requires little or no maintenance overhead. The combinatorial nature of the problem and the system demand for distributed algorithms makes the problem uniquely challenging. By utilizing Lagrangian decomposition and Markov chain approximation based arguments, we address this challenge by designing two distributed algorithms running in tandem: a primal-dual storage and bandwidth allocation algorithm and a "soft-worst-neighbor-choking" topology-building algorithm. Our scheme provably converges to a near-optimal solution, and is easy to implement in practice. Packet-level simulation results show that the proposed scheme achieves minimum sever load under highly heterogeneous combinations of supply and demand patterns, and is robust to system dynamics of user/helper churn, user/helper asynchrony, and random delays in the network.

Adaptive Detector Arrays for Optical Communications Receivers

NASA Technical Reports Server (NTRS)

Vilnrotter, V.; Srinivasan, M.

2000-01-01

The structure of an optimal adaptive array receiver for ground-based optical communications is described and its performance investigated. Kolmogorov phase screen simulations are used to model the sample functions of the focal-plane signal distribution due to turbulence and to generate realistic spatial distributions of the received optical field. This novel array detector concept reduces interference from background radiation by effectively assigning higher confidence levels at each instant of time to those detector elements that contain significant signal energy and suppressing those that do not. A simpler suboptimum structure that replaces the continuous weighting function of the optimal receiver by a hard decision on the selection of the signal detector elements also is described and evaluated. Approximations and bounds to the error probability are derived and compared with the exact calculations and receiver simulation results. It is shown that, for photon-counting receivers observing Poisson-distributed signals, performance improvements of approximately 5 dB can be obtained over conventional single-detector photon-counting receivers, when operating in high background environments.

The Role of Distributed Generation and Combined Heat and Power (CHP) Systems in Data Centers

EPA Pesticide Factsheets

This report reviews how distributed generation (DG) resources such as fuel cells, reciprocating engines, and gas turbines can offer powerful energy efficiency savings in data centers, particularly when configured in combined heat and power (CHP) mode.

Assessment of new-generation high-power electronic nicotine delivery system as thermal aerosol generation device for inhaled bronchodilators.

PubMed

Pourchez, Jérémie; de Oliveira, Fabien; Perinel-Ragey, Sophie; Basset, Thierry; Vergnon, Jean-Michel; Prévôt, Nathalie

2017-02-25

A need remains for alternative devices for aerosol drug delivery that are low cost, convenient and easy to use for the patient, but also capable of producing small-sized aerosol particles. This study investigated the potential of recent high power electronic nicotine delivery systems (ENDS) as aerosol generation devices for inhaled bronchodilators. The particle size distribution was measured using a cascade impactor. The delivery of terbutaline sulfate, a current bronchodilator used for asthma or COPD therapy by inhalation, was studied. This drug was quantified by liquid chromatography coupled with tandem mass spectrometry. The particle size distribution in terms of mass frequency (in two ways, gravimetrically and quantitatively through drug assay on each stage) and the terbutaline sulfate concentration in the aerosol were elucidated. The mass median aerodynamic diameter (MMAD) and the drug delivery rose when the power level increased, to reach 5.6±0.4μg/puff with a MMAD of 0.78±0.03μm at 25W. New generation high-power ENDS are very efficient to generate carrier-droplets in the submicron range containing drug molecules with a constant drug concentration whatever the size-fractions. ENDS appear to be highly patient-adaptive. Copyright © 2017 Elsevier B.V. All rights reserved.

Evolution of adaptation mechanisms: Adaptation energy, stress, and oscillating death.

PubMed

Gorban, Alexander N; Tyukina, Tatiana A; Smirnova, Elena V; Pokidysheva, Lyudmila I

2016-09-21

In 1938, Selye proposed the notion of adaptation energy and published 'Experimental evidence supporting the conception of adaptation energy.' Adaptation of an animal to different factors appears as the spending of one resource. Adaptation energy is a hypothetical extensive quantity spent for adaptation. This term causes much debate when one takes it literally, as a physical quantity, i.e. a sort of energy. The controversial points of view impede the systematic use of the notion of adaptation energy despite experimental evidence. Nevertheless, the response to many harmful factors often has general non-specific form and we suggest that the mechanisms of physiological adaptation admit a very general and nonspecific description. We aim to demonstrate that Selye׳s adaptation energy is the cornerstone of the top-down approach to modelling of non-specific adaptation processes. We analyze Selye׳s axioms of adaptation energy together with Goldstone׳s modifications and propose a series of models for interpretation of these axioms. Adaptation energy is considered as an internal coordinate on the 'dominant path' in the model of adaptation. The phenomena of 'oscillating death' and 'oscillating remission' are predicted on the base of the dynamical models of adaptation. Natural selection plays a key role in the evolution of mechanisms of physiological adaptation. We use the fitness optimization approach to study of the distribution of resources for neutralization of harmful factors, during adaptation to a multifactor environment, and analyze the optimal strategies for different systems of factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dust generation in powders: Effect of particle size distribution

NASA Astrophysics Data System (ADS)

Chakravarty, Somik; Le Bihan, Olivier; Fischer, Marc; Morgeneyer, Martin

2017-06-01

This study explores the relationship between the bulk and grain-scale properties of powders and dust generation. A vortex shaker dustiness tester was used to evaluate 8 calcium carbonate test powders with median particle sizes ranging from 2μm to 136μm. Respirable aerosols released from the powder samples were characterised by their particle number and mass concentrations. All the powder samples were found to release respirable fractions of dust particles which end up decreasing with time. The variation of powder dustiness as a function of the particle size distribution was analysed for the powders, which were classified into three groups based on the fraction of particles within the respirable range. The trends we observe might be due to the interplay of several mechanisms like de-agglomeration and attrition and their relative importance.

Time-dependent grid adaptation for meshes of triangles and tetrahedra

NASA Technical Reports Server (NTRS)

Rausch, Russ D.

1993-01-01

This paper presents in viewgraph form a method of optimizing grid generation for unsteady CFD flow calculations that distributes the numerical error evenly throughout the mesh. Adaptive meshing is used to locally enrich in regions of relatively large errors and to locally coarsen in regions of relatively small errors. The enrichment/coarsening procedures are robust for isotropic cells; however, enrichment of high aspect ratio cells may fail near boundary surfaces with relatively large curvature. The enrichment indicator worked well for the cases shown, but in general requires user supervision for a more efficient solution.

Evaluation of an adaptive detector collimation for prospectively ECG-triggered coronary CT angiography with third-generation dual-source CT.

PubMed

Messerli, Michael; Dewes, Patricia; Scholtz, Jan-Erik; Arendt, Christophe; Wildermuth, Simon; Vogl, Thomas J; Bauer, Ralf W

2018-05-01

To investigate the impact of an adaptive detector collimation on the dose parameters and accurateness of scan length adaption at prospectively ECG-triggered sequential cardiac CT with a wide-detector third-generation dual-source CT. Ideal scan lengths for human hearts were retrospectively derived from 103 triple-rule-out examinations. These measures were entered into the new scanner operated in prospectively ECG-triggered sequential cardiac scan mode with three different detector settings: (1) adaptive collimation, (2) fixed 64 × 0.6-mm collimation, and (3) fixed 96 × 0.6-mm collimation. Differences in effective scan length and deviation from the ideal scan length and dose parameters (CTDIvol, DLP) were documented. The ideal cardiac scan length could be matched by the adaptive collimation in every case while the mean scanned length was longer by 15.4% with the 64 × 0.6 mm and by 27.2% with the fixed 96 × 0.6-mm collimation. While the DLP was almost identical between the adaptive and the 64 × 0.6-mm collimation (83 vs. 89 mGycm at 120 kV), it was 62.7% higher with the 96 × 0.6-mm collimation (135 mGycm), p < 0.001. The adaptive detector collimation for prospectively ECG-triggered sequential acquisition allows for adjusting the scan length as accurate as this can only be achieved with a spiral acquisition. This technique allows keeping patient exposure low where patient dose would significantly increase with the traditional step-and-shoot mode. • Adaptive detector collimation allows keeping patient exposure low in cardiac CT. • With novel detectors the desired scan length can be accurately matched. • Differences in detector settings may cause 62.7% of excessive dose.

Estimating Skin Cancer Risk: Evaluating Mobile Computer-Adaptive Testing.

PubMed

Djaja, Ngadiman; Janda, Monika; Olsen, Catherine M; Whiteman, David C; Chien, Tsair-Wei

2016-01-22

Response burden is a major detriment to questionnaire completion rates. Computer adaptive testing may offer advantages over non-adaptive testing, including reduction of numbers of items required for precise measurement. Our aim was to compare the efficiency of non-adaptive (NAT) and computer adaptive testing (CAT) facilitated by Partial Credit Model (PCM)-derived calibration to estimate skin cancer risk. We used a random sample from a population-based Australian cohort study of skin cancer risk (N=43,794). All 30 items of the skin cancer risk scale were calibrated with the Rasch PCM. A total of 1000 cases generated following a normal distribution (mean [SD] 0 [1]) were simulated using three Rasch models with three fixed-item (dichotomous, rating scale, and partial credit) scenarios, respectively. We calculated the comparative efficiency and precision of CAT and NAT (shortening of questionnaire length and the count difference number ratio less than 5% using independent t tests). We found that use of CAT led to smaller person standard error of the estimated measure than NAT, with substantially higher efficiency but no loss of precision, reducing response burden by 48%, 66%, and 66% for dichotomous, Rating Scale Model, and PCM models, respectively. CAT-based administrations of the skin cancer risk scale could substantially reduce participant burden without compromising measurement precision. A mobile computer adaptive test was developed to help people efficiently assess their skin cancer risk.

Processes affecting altitudinal distribution of invasive Ageratina adenophora in western Himalaya: The role of local adaptation and the importance of different life-cycle stages

PubMed Central

Kühn, Ingolf; Ahmad, Mustaqeem; Michalski, Stefan; Auge, Harald

2017-01-01

The spread of invasive plants along elevational gradients is considered a threat to fragile mountain ecosystems, but it can also provide the opportunity to better understand some of the basic processes driving the success of invasive species. Ageratina adenophora (Asteraceae) is an invasive plant of global importance and has a broad distribution along elevational gradients in the Western Himalayas. Our study aimed at understanding the role of evolutionary processes (e.g. local adaptation and clinal differentiation) and different life history stages in shaping the distribution pattern of the invasive plant along an elevational gradient in the Western Himalaya. We carried out extensive distributional surveys, established a reciprocal transplant experiment with common gardens at three elevational levels, and measured a suite of traits related to germination, growth, reproduction and phenology. Our results showed a lack of local adaptation, and we did not find any evidence for clinal differentiation in any measured trait except a rather weak signal for plant height. We found that seed germination was the crucial life-cycle transition in determining the lower range limit while winter mortality of plants shaped the upper range limit in our study area, thus explaining the hump shaped distribution pattern. Differences in trait values between gardens for most traits indicated a high degree of phenotypic plasticity. Possible causes such as apomixis, seed dispersal among sites, and pre-adaptation might have confounded evolutionary processes to act upon. Our results suggest that the success and spread of Ageratina adenophora are dependent on different life history stages at different elevations that are controlled by abiotic conditions. PMID:29125852

Processes affecting altitudinal distribution of invasive Ageratina adenophora in western Himalaya: The role of local adaptation and the importance of different life-cycle stages.

PubMed

Datta, Arunava; Kühn, Ingolf; Ahmad, Mustaqeem; Michalski, Stefan; Auge, Harald

2017-01-01

The spread of invasive plants along elevational gradients is considered a threat to fragile mountain ecosystems, but it can also provide the opportunity to better understand some of the basic processes driving the success of invasive species. Ageratina adenophora (Asteraceae) is an invasive plant of global importance and has a broad distribution along elevational gradients in the Western Himalayas. Our study aimed at understanding the role of evolutionary processes (e.g. local adaptation and clinal differentiation) and different life history stages in shaping the distribution pattern of the invasive plant along an elevational gradient in the Western Himalaya. We carried out extensive distributional surveys, established a reciprocal transplant experiment with common gardens at three elevational levels, and measured a suite of traits related to germination, growth, reproduction and phenology. Our results showed a lack of local adaptation, and we did not find any evidence for clinal differentiation in any measured trait except a rather weak signal for plant height. We found that seed germination was the crucial life-cycle transition in determining the lower range limit while winter mortality of plants shaped the upper range limit in our study area, thus explaining the hump shaped distribution pattern. Differences in trait values between gardens for most traits indicated a high degree of phenotypic plasticity. Possible causes such as apomixis, seed dispersal among sites, and pre-adaptation might have confounded evolutionary processes to act upon. Our results suggest that the success and spread of Ageratina adenophora are dependent on different life history stages at different elevations that are controlled by abiotic conditions.

Mitigation of Power Quality Problems in Grid-Interactive Distributed Generation System

NASA Astrophysics Data System (ADS)

Bhende, C. N.; Kalam, A.; Malla, S. G.

2016-04-01

Having an inter-tie between low/medium voltage grid and distributed generation (DG), both exposes to power quality (PQ) problems created by each other. This paper addresses various PQ problems arise due to integration of DG with grid. The major PQ problems are due to unbalanced and non-linear load connected at DG, unbalanced voltage variations on transmission line and unbalanced grid voltages which severely affect the performance of the system. To mitigate the above mentioned PQ problems, a novel integrated control of distribution static shunt compensator (DSTATCOM) is presented in this paper. DSTATCOM control helps in reducing the unbalance factor of PCC voltage. It also eliminates harmonics from line currents and makes them balanced. Moreover, DSTATCOM supplies the reactive power required by the load locally and hence, grid need not to supply the reactive power. To show the efficacy of the proposed controller, several operating conditions are considered and verified through simulation using MATLAB/SIMULINK.

Power System Concepts for the Lunar Outpost: A Review of the Power Generation, Energy Storage, Power Management and Distribution (PMAD) System Requirements and Potential Technologies for Development of the Lunar Outpost

NASA Technical Reports Server (NTRS)

Khan, Z.; Vranis, A.; Zavoico, A.; Freid, S.; Manners, B.

2006-01-01

This paper will review potential power system concepts for the development of the lunar outpost including power generation, energy storage, and power management and distribution (PMAD). In particular, the requirements of the initial robotic missions will be discussed and the technologies considered will include cryogenics and regenerative fuel cells (RFC), AC and DC transmission line technology, high voltage and low voltage power transmission, conductor materials of construction and power beaming concepts for transmitting power to difficult to access locations such as at the bottom of craters. Operating conditions, component characteristics, reliability, maintainability, constructability, system safety, technology gaps/risk and adaptability for future lunar missions will be discussed for the technologies considered.

The acoustic adaptation hypothesis in a widely distributed South American frog: Southernmost signals propagate better.

PubMed

Velásquez, Nelson A; Moreno-Gómez, Felipe N; Brunetti, Enzo; Penna, Mario

2018-05-03

Animal communication occurs in environments that affect the properties of signals as they propagate from senders to receivers. We studied the geographic variation of the advertisement calls of male Pleurodema thaul individuals from eight localities in Chile. Furthermore, by means of signal propagation experiments, we tested the hypothesis that local calls are better transmitted and less degraded than foreign calls (i.e. acoustic adaptation hypothesis). Overall, the advertisement calls varied greatly along the distribution of P. thaul in Chile, and it was possible to discriminate localities grouped into northern, central and southern stocks. Propagation distance affected signal amplitude and spectral degradation in all localities, but temporal degradation was only affected by propagation distance in one out of seven localities. Call origin affected signal amplitude in five out of seven localities and affected spectral and temporal degradation in six out of seven localities. In addition, in northern localities, local calls degraded more than foreign calls, and in southern localities the opposite was observed. The lack of a strict optimal relationship between signal characteristics and environment indicates partial concordance with the acoustic adaptation hypothesis. Inter-population differences in selectivity for call patterns may compensate for such environmental constraints on acoustic communication.

Spacecraft Formation Flying near Sun-Earth L2 Lagrange Point: Trajectory Generation and Adaptive Full-State Feedback Control

NASA Technical Reports Server (NTRS)

Wong, Hong; Kapila, Vikram

2004-01-01

In this paper, we present a method for trajectory generation and adaptive full-state feedback control to facilitate spacecraft formation flying near the Sun-Earth L2 Lagrange point. Specifically, the dynamics of a spacecraft in the neighborhood of a Halo orbit reveals that there exist quasi-periodic orbits surrounding the Halo orbit. Thus, a spacecraft formation is created by placing a leader spacecraft on a desired Halo orbit and placing follower spacecraft on desired quasi-periodic orbits. To produce a formation maintenance controller, we first develop the nonlinear dynamics of a follower spacecraft relative to the leader spacecraft. We assume that the leader spacecraft is on a desired Halo orbit trajectory and the follower spacecraft is to track a desired quasi-periodic orbit surrounding the Halo orbit. Then, we design an adaptive, full-state feedback position tracking controller for the follower spacecraft providing an adaptive compensation for the unknown mass of the follower spacecraft. The proposed control law is simulated for the case of the leader and follower spacecraft pair and is shown to yield global, asymptotic convergence of the relative position tracking errors.

What is adapted in face adaptation? The neural representations of expression in the human visual system.

PubMed

Fox, Christopher J; Barton, Jason J S

2007-01-05

The neural representation of facial expression within the human visual system is not well defined. Using an adaptation paradigm, we examined aftereffects on expression perception produced by various stimuli. Adapting to a face, which was used to create morphs between two expressions, substantially biased expression perception within the morphed faces away from the adapting expression. This adaptation was not based on low-level image properties, as a different image of the same person displaying that expression produced equally robust aftereffects. Smaller but significant aftereffects were generated by images of different individuals, irrespective of gender. Non-face visual, auditory, or verbal representations of emotion did not generate significant aftereffects. These results suggest that adaptation affects at least two neural representations of expression: one specific to the individual (not the image), and one that represents expression across different facial identities. The identity-independent aftereffect suggests the existence of a 'visual semantic' for facial expression in the human visual system.

The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres

NASA Astrophysics Data System (ADS)

Ming-Huang Chiang, David; Lin, Chia-Ping; Chen, Mu-Chen

2011-05-01

Among distribution centre operations, order picking has been reported to be the most labour-intensive activity. Sophisticated storage assignment policies adopted to reduce the travel distance of order picking have been explored in the literature. Unfortunately, previous research has been devoted to locating entire products from scratch. Instead, this study intends to propose an adaptive approach, a Data Mining-based Storage Assignment approach (DMSA), to find the optimal storage assignment for newly delivered products that need to be put away when there is vacant shelf space in a distribution centre. In the DMSA, a new association index (AIX) is developed to evaluate the fitness between the put away products and the unassigned storage locations by applying association rule mining. With AIX, the storage location assignment problem (SLAP) can be formulated and solved as a binary integer programming. To evaluate the performance of DMSA, a real-world order database of a distribution centre is obtained and used to compare the results from DMSA with a random assignment approach. It turns out that DMSA outperforms random assignment as the number of put away products and the proportion of put away products with high turnover rates increase.

Particle systems for adaptive, isotropic meshing of CAD models

PubMed Central

Levine, Joshua A.; Whitaker, Ross T.

2012-01-01

We present a particle-based approach for generating adaptive triangular surface and tetrahedral volume meshes from computer-aided design models. Input shapes are treated as a collection of smooth, parametric surface patches that can meet non-smoothly on boundaries. Our approach uses a hierarchical sampling scheme that places particles on features in order of increasing dimensionality. These particles reach a good distribution by minimizing an energy computed in 3D world space, with movements occurring in the parametric space of each surface patch. Rather than using a pre-computed measure of feature size, our system automatically adapts to both curvature as well as a notion of topological separation. It also enforces a measure of smoothness on these constraints to construct a sizing field that acts as a proxy to piecewise-smooth feature size. We evaluate our technique with comparisons against other popular triangular meshing techniques for this domain. PMID:23162181

Turbo-generator control with variable valve actuation

DOEpatents

Vuk, Carl T [Denver, IA

2011-02-22

An internal combustion engine incorporating a turbo-generator and one or more variably activated exhaust valves. The exhaust valves are adapted to variably release exhaust gases from a combustion cylinder during a combustion cycle to an exhaust system. The turbo-generator is adapted to receive exhaust gases from the exhaust system and rotationally harness energy therefrom to produce electrical power. A controller is adapted to command the exhaust valve to variably open in response to a desired output for the turbo-generator.

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE PAGES

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.; ...

2018-02-06

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

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

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

2nd & 3rd Generation Vehicle Subsystems

NASA Technical Reports Server (NTRS)

2000-01-01

This paper contains viewgraph presentation on the "2nd & 3rd Generation Vehicle Subsystems" project. The objective behind this project is to design, develop and test advanced avionics, power systems, power control and distribution components and subsystems for insertion into a highly reliable and low-cost system for a Reusable Launch Vehicles (RLV). The project is divided into two sections: 3rd Generation Vehicle Subsystems and 2nd Generation Vehicle Subsystems. The following topics are discussed under the first section, 3rd Generation Vehicle Subsystems: supporting the NASA RLV program; high-performance guidance & control adaptation for future RLVs; Evolvable Hardware (EHW) for 3rd generation avionics description; Scaleable, Fault-tolerant Intelligent Network or X(trans)ducers (SFINIX); advance electric actuation devices and subsystem technology; hybrid power sources and regeneration technology for electric actuators; and intelligent internal thermal control. Topics discussed in the 2nd Generation Vehicle Subsystems program include: design, development and test of a robust, low-maintenance avionics with no active cooling requirements and autonomous rendezvous and docking systems; design and development of a low maintenance, high reliability, intelligent power systems (fuel cells and battery); and design of a low cost, low maintenance high horsepower actuation systems (actuators).

Origins of adaptive immunity.

PubMed

Liongue, Clifford; John, Liza B; Ward, Alister

2011-01-01

Adaptive immunity, involving distinctive antibody- and cell-mediated responses to specific antigens based on "memory" of previous exposure, is a hallmark of higher vertebrates. It has been argued that adaptive immunity arose rapidly, as articulated in the "big bang theory" surrounding its origins, which stresses the importance of coincident whole-genome duplications. Through a close examination of the key molecules and molecular processes underpinning adaptive immunity, this review suggests a less-extreme model, in which adaptive immunity emerged as part of longer evolutionary journey. Clearly, whole-genome duplications provided additional raw genetic materials that were vital to the emergence of adaptive immunity, but a variety of other genetic events were also required to generate some of the key molecules, whereas others were preexisting and simply co-opted into adaptive immunity.

Generation of Hermite-Gaussian modes and vortex arrays based on two-dimensional gain distribution controlled microchip laser.

PubMed

Kong, Weipeng; Sugita, Atsushi; Taira, Takunori

2012-07-01

We have demonstrated high-order Hermite-Gaussian (HG) mode generation based on 2D gain distribution control edge-pumped, composite all-ceramic Yb:YAG/YAG microchip lasers using a V-type cavity. Several hundred milliwatts to several watts HG(mn) modes are achieved. We also generated different kinds of vortex arrays directly from the oscillator with the same power level. In addition, a more than 7 W doughnut-shape mode can be generated in the same cavity.

Adaptive Optics Communications Performance Analysis

NASA Technical Reports Server (NTRS)

Srinivasan, M.; Vilnrotter, V.; Troy, M.; Wilson, K.

2004-01-01

The performance improvement obtained through the use of adaptive optics for deep-space communications in the presence of atmospheric turbulence is analyzed. Using simulated focal-plane signal-intensity distributions, uncoded pulse-position modulation (PPM) bit-error probabilities are calculated assuming the use of an adaptive focal-plane detector array as well as an adaptively sized single detector. It is demonstrated that current practical adaptive optics systems can yield performance gains over an uncompensated system ranging from approximately 1 dB to 6 dB depending upon the PPM order and background radiation level.

Adaptive control for accelerators

DOEpatents

Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

1991-01-01

An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

Distributed plug-and-play optimal generator and load control for power system frequency regulation

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

Zhao, Changhong; Mallada, Enrique; Low, Steven H.

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Distributed plug-and-play optimal generator and load control for power system frequency regulation

DOE PAGES

Zhao, Changhong; Mallada, Enrique; Low, Steven H.; ...

2018-03-14

A distributed control scheme, which can be implemented on generators and controllable loads in a plug-and-play manner, is proposed for power system frequency regulation. The proposed scheme is based on local measurements, local computation, and neighborhood information exchanges over a communication network with an arbitrary (but connected) topology. In the event of a sudden change in generation or load, the proposed scheme can restore the nominal frequency and the reference inter-area power flows, while minimizing the total cost of control for participating generators and loads. Power network stability under the proposed control is proved with a relatively realistic model whichmore » includes nonlinear power flow and a generic (potentially nonlinear or high-order) turbine-governor model, and further with first- and second-order turbine-governor models as special cases. Finally, in simulations, the proposed control scheme shows a comparable performance to the existing automatic generation control (AGC) when implemented only on the generator side, and demonstrates better dynamic characteristics than AGC when each scheme is implemented on both generators and controllable loads. Simulation results also show robustness of the proposed scheme to communication link failure.« less

Instabilities and Turbulence Generation by Pick-Up Ion Distributions in the Outer Heliosheath

NASA Astrophysics Data System (ADS)

Weichman, K.; Roytershteyn, V.; Delzanno, G. L.; Pogorelov, N.

2017-12-01

Pick-up ions (PUIs) play a significant role in the dynamics of the heliosphere. One problem that has attracted significant attention is the stability of ring-like distributions of PUIs and the electromagnetic fluctuations that could be generated by PUI distributions. For example, PUI stability is relevant to theories attempting to identify the origins of the IBEX ribbon. PUIs have previously been investigated by linear stability analysis of model (e.g. Gaussian) rings and corresponding computer simulations. The majority of these simulations utilized particle-in-cell methods which suffer from accuracy limitations imposed by the statistical noise associated with representing the plasma by a relatively small number of computational particles. In this work, we utilize highly accurate spectral Vlasov simulations conducted using the fully kinetic implicit code SPS (Spectral Plasma Solver) to investigate the PUI distributions inferred from a global heliospheric model (Heerikhuisen et al., 2016). Results are compared with those obtained by hybrid and fully kinetic particle-in-cell methods.

Experimental study of an adaptive CFRC reflector for high order wave-front error correction

NASA Astrophysics Data System (ADS)

Lan, Lan; Fang, Houfei; Wu, Ke; Jiang, Shuidong; Zhou, Yang

2018-03-01

The recent radio frequency communication system developments are generating the need for creating space antennas with lightweight and high precision. The carbon fiber reinforced composite (CFRC) materials have been used to manufacture the high precision reflector. The wave-front errors caused by fabrication and on-orbit distortion are inevitable. The adaptive CFRC reflector has received much attention to do the wave-front error correction. Due to uneven stress distribution that is introduced by actuation force and fabrication, the high order wave-front errors such as print-through error is found on the reflector surface. However, the adaptive CFRC reflector with PZT actuators basically has no control authority over the high order wave-front errors. A new design architecture assembled secondary ribs at the weak triangular surfaces is presented in this paper. The virtual experimental study of the new adaptive CFRC reflector has conducted. The controllability of the original adaptive CFRC reflector and the new adaptive CFRC reflector with secondary ribs are investigated. The virtual experimental investigation shows that the new adaptive CFRC reflector is feasible and efficient to diminish the high order wave-front error.

Teaching Millennials and Generation Z: Bridging the Generational Divide.

PubMed

Shatto, Bobbi; Erwin, Kelly

2017-02-01

Most undergraduate students today are part of the millennial generation. However, the next wave of students-Generation Z-are just beginning to enter universities. Although these groups share many similarities, they each have unique characteristics that create challenges in the classroom. Incorporating technology, engaging students with adaptive learning activities, and understanding basic generational differences are ways to limit the effects of generational conflict while keeping both millennials and Generation Z students engaged in learning. It is important to understand basic differences and distinctions across generations for developing pedagogy that reaches these unique student populations.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

NASA Astrophysics Data System (ADS)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids

DOE PAGES

Chen, Bo; Chen, Chen; Wang, Jianhui; ...

2017-07-07

The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distributionmore » systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. Furthermore, the SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.« less

Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids

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

Chen, Bo; Chen, Chen; Wang, Jianhui

The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distributionmore » systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. Furthermore, the SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.« less

Adaptive powertrain control for plugin hybrid electric vehicles

DOEpatents

Kedar-Dongarkar, Gurunath; Weslati, Feisel

2013-10-15

A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

NASA Astrophysics Data System (ADS)

Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

2018-06-01

This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

Temperature, energy metabolism, and adaptive divergence in two oyster subspecies.

PubMed

Li, Ao; Li, Li; Song, Kai; Wang, Wei; Zhang, Guofan

2017-08-01

Comparisons of related species that have diverse spatial distributions provide an efficient way to investigate adaptive evolution in face of increasing global warming. The oyster subjected to high environmental selections is a model species as sessile marine invertebrate. This study aimed to detect the adaptive divergence of energy metabolism in two oyster subspecies from the genus Crassostrea - C. gigas gigas and C. gigas angulata -which are broadly distributed along the northern and southern coasts of China, respectively. We examined the effects of acute thermal stress on energy metabolism in two oyster subspecies after being common gardened for one generation in identical conditions. Thermal responses were assessed by incorporating physiological, molecular, and genomic approaches. Southern oysters exhibited higher fluctuations in metabolic rate, activities of key energetic enzymes, and levels of thermally induced gene expression than northern oysters. For genes involved in energy metabolism, the former displayed higher basal levels of gene expression and a more pronounced downregulation of thermally induced expression, while the later exhibited lower basal levels and a less pronounced downregulation of gene expression. Contrary expression pattern was observed in oxidative stress gene. Besides, energy metabolic tradeoffs were detected in both subspecies. Furthermore, the genetic divergence of a nonsynonymous SNP ( SOD-132 ) and five synonymous SNPs in other genes was identified and validated in these two subspecies, which possibly affects downstream functions and explains the aforementioned phenotypic variations. Our study demonstrates that differentiations in energy metabolism underlie the plasticity of adaptive divergence in two oyster subspecies and suggest C. gigas angulata with moderate phenotypic plasticity has higher adaptive potential to cope with exacerbated global warming.

Generating the Local Oscillator "Locally" in Continuous-Variable Quantum Key Distribution Based on Coherent Detection

NASA Astrophysics Data System (ADS)

Qi, Bing; Lougovski, Pavel; Pooser, Raphael; Grice, Warren; Bobrek, Miljko

2015-10-01

Continuous-variable quantum key distribution (CV-QKD) protocols based on coherent detection have been studied extensively in both theory and experiment. In all the existing implementations of CV-QKD, both the quantum signal and the local oscillator (LO) are generated from the same laser and propagate through the insecure quantum channel. This arrangement may open security loopholes and limit the potential applications of CV-QKD. In this paper, we propose and demonstrate a pilot-aided feedforward data recovery scheme that enables reliable coherent detection using a "locally" generated LO. Using two independent commercial laser sources and a spool of 25-km optical fiber, we construct a coherent communication system. The variance of the phase noise introduced by the proposed scheme is measured to be 0.04 (rad2 ), which is small enough to enable secure key distribution. This technology also opens the door for other quantum communication protocols, such as the recently proposed measurement-device-independent CV-QKD, where independent light sources are employed by different users.

Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems

NASA Astrophysics Data System (ADS)

Rabl, Tilmann; Lang, Andreas; Hackl, Thomas; Sick, Bernhard; Kosch, Harald

A large body of research concerns the adaptability of database systems. Many commercial systems already contain autonomic processes that adapt configurations as well as data structures and data organization. Yet there is virtually no possibility for a just measurement of the quality of such optimizations. While standard benchmarks have been developed that simulate real-world database applications very precisely, none of them considers variations in workloads produced by human factors. Today’s benchmarks test the performance of database systems by measuring peak performance on homogeneous request streams. Nevertheless, in systems with user interaction access patterns are constantly shifting. We present a benchmark that simulates a web information system with interaction of large user groups. It is based on the analysis of a real online eLearning management system with 15,000 users. The benchmark considers the temporal dependency of user interaction. Main focus is to measure the adaptability of a database management system according to shifting workloads. We will give details on our design approach that uses sophisticated pattern analysis and data mining techniques.

Adaptive and Adaptable Automation Design: A Critical Review of the Literature and Recommendations for Future Research

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Kaber, David B.

2006-01-01

This report presents a review of literature on approaches to adaptive and adaptable task/function allocation and adaptive interface technologies for effective human management of complex systems that are likely to be issues for the Next Generation Air Transportation System, and a focus of research under the Aviation Safety Program, Integrated Intelligent Flight Deck Project. Contemporary literature retrieved from an online database search is summarized and integrated. The major topics include the effects of delegation-type, adaptable automation on human performance, workload and situation awareness, the effectiveness of various automation invocation philosophies and strategies to function allocation in adaptive systems, and the role of user modeling in adaptive interface design and the performance implications of adaptive interface technology.

Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

NASA Astrophysics Data System (ADS)

Danilov, A. A.; Kramarenko, V. K.; Nikolaev, D. V.; Rudnev, S. G.; Salamatova, V. Yu; Smirnov, A. V.; Vassilevski, Yu V.

2013-04-01

In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

Adaptive protection algorithm and system

DOEpatents

Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

2009-04-28

An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

Mutational jackpot events generate effective frequency-dependent selection in adapting populations

NASA Astrophysics Data System (ADS)

Hallatschek, Oskar

The site-frequency spectrum is one the most easily measurable quantities that characterize the genetic diversity of a population. While most neutral models predict that site frequency spectra should decay with increasing frequency, a high-frequency uptick has been reported in many populations. Anomalies in the high-frequency tail are particularly unsettling because the highest frequencies can be measured with greatest accuracy. Here, we show that an uptick in the spectrum of neutral mutations generally arises when mutant frequencies are dominated by rare jackpot events, mutational events with large descendant numbers. This leads to an effective pattern of frequency-dependent selection (or unstable internal equilibrium at one half frequency) that causes an accumulation of high-frequency polymorphic sites. We reproduce the known uptick occurring for recurrent hitchhiking (genetic draft) as well as rapid adaptation, and (in the future) generalize the shape of the high-frequency tail to other scenarios that are dominated by jackpot events, such as frequent range expansions. We also tackle (in the future) the inverse approach to use the high-frequency uptick for learning about the tail of the offspring number distribution. Positively selected alleles need to surpass, typically, an u NSF Career Award (PoLS), NIH NIGMS R01, Simons Foundation.

Dynamic Courseware Generation on the WWW.

ERIC Educational Resources Information Center

Vassileva, Julita; Deters, Ralph

1998-01-01

The Dynamic Courseware Generator (DCG), which runs on a Web server, was developed for the authoring of adaptive computer-assisted learning courses. It generates an individual course according to the learner's goals and previous knowledge, and dynamically adapts the course according to the learner's success in knowledge acquisition. The tool may be…

Unveiling adaptation using high-resolution lineage tracking

NASA Astrophysics Data System (ADS)

Blundell, Jamie; Levy, Sasha; Fisher, Daniel; Petrov, Dmitri; Sherlock, Gavin

2013-03-01

Human diseases such as cancer and microbial infections are adaptive processes inside the human body with enormous population sizes: between 106 -1012 cells. In spite of this our understanding of adaptation in large populations is limited. The key problem is the difficulty in identifying anything more than a handful of rare, large-effect beneficial mutations. The development and use of molecular barcodes allows us to uniquely tag hundreds of thousands of cells and enable us to track tens of thousands of adaptive mutations in large yeast populations. We use this system to test some of the key theories on which our understanding of adaptation in large populations is based. We (i) measure the fitness distribution in an evolving population at different times, (ii) identify when an appreciable fraction of clones in the population have at most a single adaptive mutation and isolate a large number of clones with independent single adaptive mutations, and (iii) use this clone collection to determine the distribution of fitness effects of single beneficial mutations.

Modeling a space-based quantum link that includes an adaptive optics system

NASA Astrophysics Data System (ADS)

Duchane, Alexander W.; Hodson, Douglas D.; Mailloux, Logan O.

2017-10-01

Quantum Key Distribution uses optical pulses to generate shared random bit strings between two locations. If a high percentage of the optical pulses are comprised of single photons, then the statistical nature of light and information theory can be used to generate secure shared random bit strings which can then be converted to keys for encryption systems. When these keys are incorporated along with symmetric encryption techniques such as a one-time pad, then this method of key generation and encryption is resistant to future advances in quantum computing which will significantly degrade the effectiveness of current asymmetric key sharing techniques. This research first reviews the transition of Quantum Key Distribution free-space experiments from the laboratory environment to field experiments, and finally, ongoing space experiments. Next, a propagation model for an optical pulse from low-earth orbit to ground and the effects of turbulence on the transmitted optical pulse is described. An Adaptive Optics system is modeled to correct for the aberrations caused by the atmosphere. The long-term point spread function of the completed low-earth orbit to ground optical system is explored in the results section. Finally, the impact of this optical system and its point spread function on an overall quantum key distribution system as well as the future work necessary to show this impact is described.

Effects of generation mode in fMRI adaptations of semantic fluency: Paced production and overt speech

PubMed Central

Basho, Surina; Palmer, Erica D.; Rubio, Miguel A.; Wulfeck, Beverly; Müller, Ralph-Axel

2007-01-01

Verbal fluency is a widely used neuropsychological paradigm. In fMRI implementations, conventional unpaced (self-paced) versions are suboptimal due to uncontrolled timing of responses, and overt responses carry the risk of motion artifact. We investigated the behavioral and neurofunctional effects of response pacing and overt speech in semantic category-driven word generation. Twelve right-handed adults (8 female) ages 21–37 were scanned in four conditions each: Paced-Overt, Paced-Covert, Unpaced-Overt, and Unpaced-Covert. There was no significant difference in the number of exemplars generated between overt versions of the paced and unpaced conditions. Imaging results for category-driven word generation overall showed left-hemispheric activation in inferior frontal cortex, premotor cortex, cingulate gyrus, thalamus, and basal ganglia. Direct comparison of generation modes revealed significantly greater activation for the paced compared to unpaced conditions in right superior temporal, bilateral middle frontal, and bilateral anterior cingulate cortex, including regions associated with sustained attention, motor planning, and response inhibition. Covert (compared to overt) conditions showed significantly greater effects in right parietal and anterior cingulate, as well as left middle temporal and superior frontal regions. We conclude that paced overt paradigms are useful adaptations of conventional semantic fluency in fMRI, given their superiority with regard to control over and monitoring of behavioral responses. However, response pacing is associated with additional non-linguistic effects related to response inhibition, motor preparation, and sustained attention. PMID:17292926

A Cost to Benefit Analysis of a Next Generation Electric Power Distribution System

NASA Astrophysics Data System (ADS)

Raman, Apurva

This thesis provides a cost to benefit analysis of the proposed next generation of distribution systems- the Future Renewable Electric Energy Distribution Management (FREEDM) system. With the increasing penetration of renewable energy sources onto the grid, it becomes necessary to have an infrastructure that allows for easy integration of these resources coupled with features like enhanced reliability of the system and fast protection from faults. The Solid State Transformer (SST) and the Fault Isolation Device (FID) make for the core of the FREEDM system and have huge investment costs. Some key features of the FREEDM system include improved power flow control, compact design and unity power factor operation. Customers may observe a reduction in the electricity bill by a certain fraction for using renewable sources of generation. There is also a possibility of huge subsidies given to encourage use of renewable energy. This thesis is an attempt to quantify the benefits offered by the FREEDM system in monetary terms and to calculate the time in years required to gain a return on investments made. The elevated cost of FIDs needs to be justified by the advantages they offer. The result of different rates of interest and how they influence the payback period is also studied. The payback periods calculated are observed for viability. A comparison is made between the active power losses on a certain distribution feeder that makes use of distribution level magnetic transformers versus one that makes use of SSTs. The reduction in the annual active power losses in the case of the feeder using SSTs is translated onto annual savings in terms of cost when compared to the conventional case with magnetic transformers. Since the FREEDM system encourages operation at unity power factor, the need for installing capacitor banks for improving the power factor is eliminated and this reflects in savings in terms of cost. The FREEDM system offers enhanced reliability when compared to a

Independent Orbiter Assessment (IOA): Analysis of the electrical power distribution and control/electrical power generation subsystem

NASA Technical Reports Server (NTRS)

Patton, Jeff A.

1986-01-01

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter Electrical Power Distribution and Control (EPD and C)/Electrical Power Generation (EPG) hardware. The EPD and C/EPG hardware is required for performing critical functions of cryogenic reactant storage, electrical power generation and product water distribution in the Orbiter. Specifically, the EPD and C/EPG hardware consists of the following components: Power Section Assembly (PSA); Reactant Control Subsystem (RCS); Thermal Control Subsystem (TCS); Water Removal Subsystem (WRS); and Power Reactant Storage and Distribution System (PRSDS). The IOA analysis process utilized available EPD and C/EPG hardware drawings and schematics for defining hardware assemblies, components, and hardware items. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Combined online and offline adaptive radiation therapy: a dosimetric feasibility study.

PubMed

Yang, Chengliang; Liu, Feng; Ahunbay, Ergun; Chang, Yu-Wen; Lawton, Colleen; Schultz, Christopher; Wang, Dian; Firat, Selim; Erickson, Beth; Li, X Allen

2014-01-01

The purpose of this work is to explore a new adaptive radiation therapy (ART) strategy, combined "online and offline" ART, that can fully account for interfraction variations similar to the existing online ART but with substantially reduced online effort. The concept for the combined ART is to perform online ART only for the fractions with obvious interfraction variations and to deliver the ART plan for that online fraction as well as the subsequent fractions until the next online fraction needs to be adapted. To demonstrate the idea, the daily computed tomographic (CT) data acquired during image guided radiation therapy (IGRT) with an in-room CT (CTVision, Siemens Healthcare, Amarillo, TX) for 6 representative patients (including 2 prostate, 1 head-and-neck, and 1 pancreatic cancer, 1 adrenal carcinoma, and 1 craniopharyngioma patients) were analyzed. Three types of plans were generated based on the following selected daily CTs: (1) IGRT repositioning plan, generated by applying the repositioning shifts to the original plan (representing the current IGRT practice); (2) Re-Opt plan, generated with full-scope optimization; and (3) ART plan, either online ART plan generated with an online ART tool (RealArt, Prowess Inc, Concord, CA) or offline ART plan generated with shifts from the online ART plan. Various dose-volume parameters were compared with measure dosimetric benefits of the ART plans based on daily dose distributions and the cumulative dose maps obtained with deformable image registration. In general, for all the cases studied, the ART (with 3-5 online ART) and Re-Opt plans provide comparable plan quality and offer significantly better target coverage and normal tissue sparing when compared with the repositioning plans. This improvement is statistically significant. The combined online and offline ART is dosimetrically equivalent to the online ART but with substantially reduced online effort, and enables immediate delivery of the adaptive plan when an

Co-Adaptive Aiding and Automation Enhance Operator Performance

DTIC Science & Technology

2013-03-01

activation system. There is a close relation between physiologically activated adaptive aiding and brain- computer interfaces ( BCI ). BCI here refers...classification of EEG signals (Farwell & Donchin, 1988). Physiologically activated adaptive aiding is, in a sense, a special case of BCI wherein the...as passive BCI , e.g. Zander, Kothe, Jatzev, & 3 Distribution A: Approved for public release; distribution unlimited. 88 ABW Cleared 05/13/2013

Optimal Bayesian Adaptive Design for Test-Item Calibration.

PubMed

van der Linden, Wim J; Ren, Hao

2015-06-01

An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

Distributed Traffic Complexity Management by Preserving Trajectory Flexibility

NASA Technical Reports Server (NTRS)

Idris, Husni; Vivona, Robert A.; Garcia-Chico, Jose-Luis; Wing, David J.

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which groundbased service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory-oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.

Distributed Adaptive Containment Control for a Class of Nonlinear Multiagent Systems With Input Quantization.

PubMed

Wang, Chenliang; Wen, Changyun; Hu, Qinglei; Wang, Wei; Zhang, Xiuyu

2018-06-01

This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.

Adaptation in Collaborative Governance Regimes

NASA Astrophysics Data System (ADS)

Emerson, Kirk; Gerlak, Andrea K.

2014-10-01

Adaptation and the adaptive capacity of human and environmental systems have been of central concern to natural and social science scholars, many of whom characterize and promote the need for collaborative cross-boundary systems that are seen as flexible and adaptive by definition. Researchers who study collaborative governance systems in the public administration, planning and policy literature have paid less attention to adaptive capacity specifically and institutional adaptation in general. This paper bridges the two literatures and finds four common dimensions of capacity, including structural arrangements, leadership, knowledge and learning, and resources. In this paper, we focus on institutional adaptation in the context of collaborative governance regimes and try to clarify and distinguish collaborative capacity from adaptive capacity and their contributions to adaptive action. We posit further that collaborative capacities generate associated adaptive capacities thereby enabling institutional adaptation within collaborative governance regimes. We develop these distinctions and linkages between collaborative and adaptive capacities with the help of an illustrative case study in watershed management within the National Estuary Program.

From Dye Laser Factory to Portable Semiconductor Laser: Four Generations of Sodium Guide Star Lasers for Adaptive Optics in Astronomy and Space Situational Awareness

NASA Astrophysics Data System (ADS)

d'Orgeville, C.; Fetzer, G.

This presentation recalls the history of sodium guide star laser systems used in astronomy and space situational awareness adaptive optics, analysing the impact that sodium laser technology evolution has had on routine telescope operations. While it would not be practical to describe every single sodium guide star laser system developed to date, it is possible to characterize their evolution in broad technology terms. The first generation of sodium lasers used dye laser technology to create the first sodium laser guide stars in Hawaii, California, and Spain in the late 1980's and 1990's. These experimental systems were turned into the first laser guide star facilities to equip medium-to-large diameter adaptive optics telescopes, opening a new era of LGS AO-enabled diffraction-limited imaging from the ground. Although they produced exciting scientific results, these laser guide star facilities were large, power-hungry and messy. In the USA, a second-generation of sodium lasers was developed in the 2000's that used cleaner, yet still large and complex, solid-state laser technology. These are the systems in routine operation at the 8-10m class astronomical telescopes and 4m-class satellite imaging facilities today. Meanwhile in Europe, a third generation of sodium lasers was being developed using inherently compact and efficient fiber laser technology, and resulting in the only commercially available sodium guide star laser system to date. Fiber-based sodium lasers will be deployed at two astronomical telescopes and at least one space debris tracking station this year. Although highly promising, these systems remain significantly expensive and they have yet to demonstrate high performance in the field. We are proposing to develop a fourth generation of sodium lasers: based on semiconductor technology, these lasers could provide the final solution to the problem of sodium laser guide star adaptive optics for all astronomy and space situational awareness applications.

Influence of ventilation structure on air flow distribution of large turbo-generator

NASA Astrophysics Data System (ADS)

Zhang, Liying; Ding, Shuye; Zhao, Zhijun; Yang, Jingmo

2018-04-01

For the 350 MW air - cooled turbo—generator, the rotor body is ventilated by sub -slots and 94 radial ventilation ducts and the end adopts arc segment and the straight section to acquire the wind. The stator is ventilated with five inlets and eight outlet air branches. In order to analyze the cooling effect of different ventilation schemes, a global physical model including the stator, rotor, casing and fan is established, and the assumptions and boundary conditions of the solution domain are given. the finite volume method is used to solve the problem, and the air flow distribution characteristics of each part of the motor under different ventilation schemes are obtained. The results show that the baffle at the end of the rotor can eliminate the eddy current at the end of the rotor, and make the flow distribution of cooling air more uniform and reasonable. The conclusions can provide reference for the design of motor ventilation structure.

Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists.

PubMed

Neal, Craig M; Hunter, Angus M; Brennan, Lorraine; O'Sullivan, Aifric; Hamilton, D Lee; De Vito, Giuseppe; Galloway, Stuart D R

2013-02-15

This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.

Toward Adaptive X-Ray Telescopes

NASA Technical Reports Server (NTRS)

O'Dell, Stephen L.; Atkins, Carolyn; Button, Tim W.; Cotroneo, Vincenzo; Davis, William N.; Doel, Peer; Feldman, Charlotte H.; Freeman, Mark D.; Gubarev, Mikhail V.; Kolodziejczak, Jeffrey J.;

A distributed big data storage and data mining framework for solar-generated electricity quantity forecasting

NASA Astrophysics Data System (ADS)

Wang, Jianzong; Chen, Yanjun; Hua, Rui; Wang, Peng; Fu, Jia

2012-02-01

Photovoltaic is a method of generating electrical power by converting solar radiation into direct current electricity using semiconductors that exhibit the photovoltaic effect. Photovoltaic power generation employs solar panels composed of a number of solar cells containing a photovoltaic material. Due to the growing demand for renewable energy sources, the manufacturing of solar cells and photovoltaic arrays has advanced considerably in recent years. Solar photovoltaics are growing rapidly, albeit from a small base, to a total global capacity of 40,000 MW at the end of 2010. More than 100 countries use solar photovoltaics. Driven by advances in technology and increases in manufacturing scale and sophistication, the cost of photovoltaic has declined steadily since the first solar cells were manufactured. Net metering and financial incentives, such as preferential feed-in tariffs for solar-generated electricity; have supported solar photovoltaics installations in many countries. However, the power that generated by solar photovoltaics is affected by the weather and other natural factors dramatically. To predict the photovoltaic energy accurately is of importance for the entire power intelligent dispatch in order to reduce the energy dissipation and maintain the security of power grid. In this paper, we have proposed a big data system--the Solar Photovoltaic Power Forecasting System, called SPPFS to calculate and predict the power according the real-time conditions. In this system, we utilized the distributed mixed database to speed up the rate of collecting, storing and analysis the meteorological data. In order to improve the accuracy of power prediction, the given neural network algorithm has been imported into SPPFS.By adopting abundant experiments, we shows that the framework can provide higher forecast accuracy-error rate less than 15% and obtain low latency of computing by deploying the mixed distributed database architecture for solar-generated electricity.

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

Adaptive sequential controller

DOEpatents

El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

1994-01-01

An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

Cross-adaptation between Olfactory Responses Induced by Two Subgroups of Odorant Molecules

PubMed Central

Takeuchi, Hiroko; Imanaka, Yukie; Hirono, Junzo; Kurahashi, Takashi

2003-01-01

It has long been believed that vertebrate olfactory signal transduction is mediated by independent multiple pathways (using cAMP and InsP3 as second messengers). However, the dual presence of parallel pathways in the olfactory receptor cell is still controversial, mainly because of the lack of information regarding the single-cell response induced by odorants that have been shown to produce InsP3 exclusively (but not cAMP) in the olfactory cilia. In this study, we recorded activities of transduction channels of single olfactory receptor cells to InsP3-producing odorants. When the membrane potential was held at −54 mV, application of InsP3-producing odorants to the ciliary region caused an inward current. The reversal potential was 0 ± 7 mV (mean ± SD, n = 10). Actually, InsP3-producing odorants generated responses in a smaller fraction of cells (lilial, 3.4%; lyral, 1.7%) than the cAMP-producing odorant (cineole, 26%). But, fundamental properties of responses were surprisingly homologous; namely, spatial distribution of the sensitivity, waveforms, I-V relation, and reversal potential, dose dependence, time integration of stimulus period, adaptation, and recovery. By applying both types of odorants alternatively to the same cell, furthermore, we observed cells to exhibit symmetrical cross-adaptation. It seems likely that even with odorants with different modalities adaptation occurs completely depending on the amount of current flow. The data will also provide evidence showing that olfactory response generation and adaptation are regulated by a uniform mechanism for a wide variety of odorants. PMID:12939391

Cross-adaptation between olfactory responses induced by two subgroups of odorant molecules.

PubMed

Takeuchi, Hiroko; Imanaka, Yukie; Hirono, Junzo; Kurahashi, Takashi

2003-09-01

It has long been believed that vertebrate olfactory signal transduction is mediated by independent multiple pathways (using cAMP and InsP3 as second messengers). However, the dual presence of parallel pathways in the olfactory receptor cell is still controversial, mainly because of the lack of information regarding the single-cell response induced by odorants that have been shown to produce InsP3 exclusively (but not cAMP) in the olfactory cilia. In this study, we recorded activities of transduction channels of single olfactory receptor cells to InsP3-producing odorants. When the membrane potential was held at -54 mV, application of InsP3-producing odorants to the ciliary region caused an inward current. The reversal potential was 0 +/- 7 mV (mean +/- SD, n = 10). Actually, InsP3-producing odorants generated responses in a smaller fraction of cells (lilial, 3.4%; lyral, 1.7%) than the cAMP-producing odorant (cineole, 26%). But, fundamental properties of responses were surprisingly homologous; namely, spatial distribution of the sensitivity, waveforms, I-V relation, and reversal potential, dose dependence, time integration of stimulus period, adaptation, and recovery. By applying both types of odorants alternatively to the same cell, furthermore, we observed cells to exhibit symmetrical cross-adaptation. It seems likely that even with odorants with different modalities adaptation occurs completely depending on the amount of current flow. The data will also provide evidence showing that olfactory response generation and adaptation are regulated by a uniform mechanism for a wide variety of odorants.