21,561 research outputs found
Frequency determination in control applications: Excitation based approach
New algorithms for estimation of the frequencies of oscillating waveform signals are described. Model of the signals is presented in the form of linear difference equation with unknown coefficients, which define the frequencies and amplitudes. Coefficients are estimated utilizing the property of the persistence of excitation of oscillating signals. Exponentially damped and oscillating signals are described in a unified framework. A property of excitation is proved for exponentially damped signal that contains a single frequency via diagonal dominance of an information matrix. Two applications of this frequency estimation technique are considered. The first one is filtering of the wind speed signal in wind turbine control applications, and the second one is the frequency estimation of exponentially damped signal motivated by the engine knock detection applications
Novel Adaptive Sampling Algorithm for POD-Based Non-Intrusive Reduced Order Model
The proper orthogonal decomposition (POD) based reduced-order model (ROM) has been an effective tool for flow field prediction in the engineering industry. The sample selection in the design space for POD basis construction affects the ROM performance sensitively. Adaptive sampling can significantly reduce the number of samples to achieve the required model accuracy. In this work, we propose a novel adaptive sampling algorithm, called conjunction sampling strategy, which is based on proven strategies. The conjunction sampling strategy is demonstrated on airfoil flow field prediction within the transonic regime. We demonstrate the performance of the proposed strategy by running 10 trials for each strategy for the robustness tests. Results show that the conjunction sampling strategy consistently achieves higher predictive accuracy compared with Latin hypercube sampling (LHS) and existing strategies. Specifically, under the same computational budget (40 training samples in total), the conjunction strategy reduced the L2 error by 56.7% compared with LHS. In addition, the conjunction strategy reduced the standard deviation of L2 errors by 62.1% with a 2.6% increase on the mean error compared with the best existing strategy
Desertification
IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL)
Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem
The 2005 AMI system for the transcription of speech in meetings
In this paper we describe the 2005 AMI system for the transcription\ud
of speech in meetings used for participation in the 2005 NIST\ud
RT evaluations. The system was designed for participation in the speech\ud
to text part of the evaluations, in particular for transcription of speech\ud
recorded with multiple distant microphones and independent headset\ud
microphones. System performance was tested on both conference room\ud
and lecture style meetings. Although input sources are processed using\ud
different front-ends, the recognition process is based on a unified system\ud
architecture. The system operates in multiple passes and makes use\ud
of state of the art technologies such as discriminative training, vocal\ud
tract length normalisation, heteroscedastic linear discriminant analysis,\ud
speaker adaptation with maximum likelihood linear regression and minimum\ud
word error rate decoding. In this paper we describe the system performance\ud
on the official development and test sets for the NIST RT05s\ud
evaluations. The system was jointly developed in less than 10 months\ud
by a multi-site team and was shown to achieve very competitive performance
Ecological models at fish community and species level to support effective river restoration
RESUMEN
Los peces nativos son indicadores de la salud de los ecosistemas acuĂĄticos, y se han
convertido en un elemento de calidad clave para evaluar el estado ecolĂłgico de los rĂos. La
comprensiĂłn de los factores que afectan a las especies nativas de peces es importante para la
gestiĂłn y conservaciĂłn de los ecosistemas acuĂĄticos. El objetivo general de esta tesis es analizar
las relaciones entre variables biológicas y de håbitat (incluyendo la conectividad) a través de
una variedad de escalas espaciales en los rĂos MediterrĂĄneos, con el desarrollo de herramientas
de modelaciĂłn para apoyar la toma de decisiones en la restauraciĂłn de rĂos.
Esta tesis se compone de cuatro artĂculos. El primero tiene como objetivos modelar la
relaciĂłn entre un conjunto de variables ambientales y la riqueza de especies nativas (NFSR), y
evaluar la eficacia de potenciales acciones de restauraciĂłn para mejorar la NFSR en la cuenca
del rĂo JĂșcar. Para ello se aplicĂł un enfoque de modelaciĂłn de red neuronal artificial (ANN),
utilizando en la fase de entrenamiento el algoritmo Levenberg-Marquardt. Se aplicó el método
de las derivadas parciales para determinar la importancia relativa de las variables ambientales.
SegĂșn los resultados, el modelo de ANN combina variables que describen la calidad de ribera,
la calidad del agua y el hĂĄbitat fĂsico, y ayudĂł a identificar los principales factores que
condicionan el patrĂłn de distribuciĂłn de la NFSR en los rĂos MediterrĂĄneos. En la segunda parte
del estudio, el modelo fue utilizado para evaluar la eficacia de dos acciones de restauraciĂłn en el
rĂo JĂșcar: la eliminaciĂłn de dos azudes abandonados, con el consiguiente incremento de la
proporciĂłn de corrientes. Estas simulaciones indican que la riqueza aumenta con el incremento
de la longitud libre de barreras artificiales y la proporciĂłn del mesohabitat de corriente, y
demostrĂł la utilidad de las ANN como una poderosa herramienta para apoyar la toma de
decisiones en el manejo y restauraciĂłn ecolĂłgica de los rĂos MediterrĂĄneos.
El segundo artĂculo tiene como objetivo determinar la importancia relativa de los dos
principales factores que controlan la reducciĂłn de la riqueza de peces (NFSR), es decir, las
interacciones entre las especies acuĂĄticas, variables del hĂĄbitat (incluyendo la conectividad
fluvial) y biolĂłgicas (incluidas las especies invasoras) en los rĂos JĂșcar, Cabriel y Turia. Con
este fin, tres modelos de ANN fueron analizados: el primero fue construido solamente con
variables biolĂłgicas, el segundo se construyĂł Ășnicamente con variables de hĂĄbitat y el tercero
con la combinaciĂłn de estos dos grupos de variables. Los resultados muestran que las variables
de hĂĄbitat son los ÂżdriversÂż mĂĄs importantes para la distribuciĂłn de NFSR, y demuestran la
importancia ecolĂłgica de los modelos desarrollados. Los resultados de este estudio destacan la
necesidad de proponer medidas de mitigaciĂłn relacionadas con la mejora del hĂĄbitat
(incluyendo la variabilidad de caudales en el rĂo) como medida para conservar y restaurar los
rĂos MediterrĂĄneos.
El tercer artĂculo busca comparar la fiabilidad y relevancia ecolĂłgica de dos modelos
predictivos de NFSR, basados en redes neuronales artificiales (ANN) y random forests (RF). La
relevancia de las variables seleccionadas por cada modelo se evaluĂł a partir del conocimiento
ecolĂłgico y apoyado por otras investigaciones. Los dos modelos fueron desarrollados utilizando
validaciĂłn cruzada k-fold y su desempeño fue evaluado a travĂ©s de tres Ăndices: el coeficiente de determinaciĂłn (R2
), el error cuadrĂĄtico medio (MSE) y el coeficiente de determinaciĂłn ajustado
(R2
adj). SegĂșn los resultados, RF obtuvo el mejor desempeño en entrenamiento. Pero, el
procedimiento de validación cruzada reveló que ambas técnicas generaron resultados similares
(R2
= 68% para RF y R2
= 66% para ANN). La comparación de diferentes métodos de machine
learning es muy Ăștil para el anĂĄlisis crĂtico de los resultados obtenidos a travĂ©s de los modelos.
El cuarto artĂculo tiene como objetivo evaluar la capacidad de las ANN para identificar los
factores que afectan a la densidad y la presencia/ausencia de Luciobarbus guiraonis en la
demarcaciĂłn hidrogrĂĄfica del JĂșcar. Se utilizĂł una red neuronal artificial multicapa de tipo feedforward (ANN) para representar relaciones no lineales entre descriptores de L. guiraonis con
variables biolĂłgicas y de hĂĄbitat. El poder predictivo de los modelos se evaluĂł con base en el
Ăndice Kappa (k), la proporciĂłn de casos correctamente clasificados (CCI) y el ĂĄrea bajo la curva
(AUC) caracterĂstica operativa del receptor (ROC). La presencia/ausencia de L. guiraonis fue
bien predicha por el modelo ANN (CCI = 87%, AUC = 0.85 y k = 0.66). La predicciĂłn de la
densidad fue moderada (CCI = 62%, AUC = 0.71 y k = 0.43). Las variables mĂĄs importantes
que describen la presencia/ausencia fueron: radiaciĂłn solar, ĂĄrea de drenaje y la proporciĂłn de
especies exĂłticas de peces con un peso relativo del 27.8%, 24.53% y 13.60% respectivamente.
En el modelo de densidad, las variables mĂĄs importantes fueron el coeficiente de variaciĂłn de
los caudales medios anuales con una importancia relativa del 50.5% y la proporciĂłn de especies
exĂłticas de peces con el 24.4%. Los modelos proporcionan informaciĂłn importante acerca de la
relaciĂłn de L. guiraonis con variables biĂłticas y de hĂĄbitat, este nuevo conocimiento podrĂa
utilizarse para apoyar futuros estudios y para contribuir en la toma de decisiones para la
conservaciĂłn y manejo de especies en los en los rĂos JĂșcar, Cabriel y Turia.Olaya MarĂn, EJ. (2013). Ecological models at fish community and species level to support effective river restoration [Tesis doctoral no publicada]. Universitat PolitĂšcnica de ValĂšncia. https://doi.org/10.4995/Thesis/10251/28853TESI
Stellar populations -- the next ten years
The study of stellar populations is a discipline that is highly dependent on
both imaging and spectroscopy. I discuss techniques in different regimes of
resolving power: broadband imaging (R~4), intermediate band imaging (R~16, 64),
narrowband spectral imaging (R~256, 1024, 4096). In recent years, we have seen
major advances in broadband all-sky surveys that are set to continue across
optical and IR bands, with the added benefit of the time domain, higher
sensitivity, and improved photometric accuracy. Tunable filters and integral
field spectrographs are poised to make further inroads into intermediate and
narrowband imaging studies of stellar populations. Further advances will come
from AO-assisted imaging and imaging spectroscopy, although photometric
accuracy will be challenging. Integral field spectroscopy will continue to have
a major impact on future stellar population studies, extending into the near
infrared once the OH suppression problem is finally resolved. A sky rendered
dark will allow a host of new ideas to be explored, and old ideas to be
revisited.Comment: Invited review, IAUS 241, "Stellar Populations as Building Blocks of
Galaxies," eds. Vazdekis, Peletier. 12 pages, 1 table. (The sideways table
should print ok; there are 10 columns.
Adaptive management of Ramsar wetlands
Abstract
The Macquarie Marshes are one of Australiaâs iconic wetlands, recognised for their international importance, providing habitat for some of the continentâs more important waterbird breeding sites as well as complex and extensive flood-dependent vegetation communities. Part of the area is recognised as a wetland of international importance, under the Ramsar Convention. River regulation has affected their resilience, which may increase with climate change. Counteracting these impacts, the increased amount of environmental flow provided to the wetland through the buy-back and increased wildlife allocation have redressed some of the impacts of river regulation.
This project assists in the development of an adaptive management framework for this Ramsar-listed wetland. It brings together current management and available science to provide an informed hierarchy of objectives that incorporates climate change adaptation and assists transparent management. The project adopts a generic approach allowing the framework to be transferred to other wetlands, including Ramsar-listed wetlands, supplied by rivers ranging from highly regulated to free flowing.
The integration of management with science allows key indicators to be monitored that will inform management and promote increasingly informed decisions. The project involved a multi-disciplinary team of scientists and managers working on one of the more difficult challenges for Australia, exacerbated by increasing impacts of climate change on flows and inundation patterns
Insights into the development of strategy from a complexity perspective
This paper provides an account of an ongoing project with an independent school in the UK. The project focuses on a strategy development intervention which, from the start, was systemic in orientation. The intention was to integrate simple systems concepts and approaches into the strategy development process to: address power relations in actively engaging a wide range of stakeholders with the schoolâs strategy-making process; generate a range of good ideas; and make the strategy-making process transparent in order to inspire stakeholder confidence in, and commitment to, it and its outcomes. This paper describes how seeking to meet these aims entailed a series of workshops during the course of which an awareness of the relevance, in our interpretation, of Complex Adaptive Systems concepts grew
- âŠ