Relevant bibliographies by topics / Models of adaptation

Academic literature on the topic 'Models of adaptation'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Models of adaptation"

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Novikov, D. A. "Team adaptation models." Automation and Remote Control 71, no. 5 (May 2010): 882–93. http://dx.doi.org/10.1134/s0005117910050164.

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Young, Laurence R. "Models for neurovestibular adaptation." Journal of Vestibular Research 13, no. 4-6 (December 28, 2003): 297–307. http://dx.doi.org/10.3233/ves-2003-134-614.

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Dynamic models have played a more prominent role in the vestibular and oculomotor field than in any other branch of physiology. The ease of identification of input and output variables and the challenge of multi-loop, multi-axis adaptive control has attracted numerous modelers from engineering and shaped behavioral and neurophysiological experimental programs. In particular, the adaptive characteristics of the neurovestibular system have generated continuing speculation as to mechanisms. This treatment of adaptation and multi-sensor integration covers the development and application of such models, principally in the author's laboratory. It emphasizes the continuing relevance of both "model reference" and "error pattern recognition" notions of adaptive control.
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Cowin, Stephen C. "Bone Stress Adaptation Models." Journal of Biomechanical Engineering 115, no. 4B (November 1, 1993): 528–33. http://dx.doi.org/10.1115/1.2895535.

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The basic concepts employed in formulating models of the process of stress adaptation in living bone tissue are reviewed. A purpose of this review is to define and separate issues in the formulation of bone remodeling theories. After discussing the rationale and objective of these models, the concepts and techniques involved in the modeling process are reviewed one by one. It is concluded that some techniques will be more successful than others in achieving the goals of computational bone remodeling. In particular, rationale is given for the preference of surface bone remodeling approaches over internal bone remodeling approaches, and for interactive multi-scale level, rather than mono-scale level, computational strategies.
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SCHULZKE, JORG-DIETER, HEINS SCHMITZ, MICHAEL FROMM, CARL J. BENTZEL, and ERNST OTTO RIECKEN. "Clinical Models of Intestinal Adaptation." Annals of the New York Academy of Sciences 859, no. 1 INTESTINAL PL (November 1998): 127–38. http://dx.doi.org/10.1111/j.1749-6632.1998.tb11117.x.

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Beckmann, Aike, C.-Elisa Schaum, and Inga Hense. "Phytoplankton adaptation in ecosystem models." Journal of Theoretical Biology 468 (May 2019): 60–71. http://dx.doi.org/10.1016/j.jtbi.2019.01.041.

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TERRIER, A., R. L. RAKOTOMANANA, A. N. RAMANIRAKA, and P. F. LEYVRAZ. "Adaptation Models of Anisotropic Bone." Computer Methods in Biomechanics and Biomedical Engineering 1, no. 1 (January 1997): 47–59. http://dx.doi.org/10.1080/01495739708936694.

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Mill, Robert, Martin Coath, Thomas Wennekers, and Susan L. Denham. "Abstract Stimulus-Specific Adaptation Models." Neural Computation 23, no. 2 (February 2011): 435–76. http://dx.doi.org/10.1162/neco_a_00077.

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Many neurons that initially respond to a stimulus stop responding if the stimulus is presented repeatedly but recover their response if a different stimulus is presented. This phenomenon is referred to as stimulus-specific adaptation (SSA). SSA has been investigated extensively using oddball experiments, which measure the responses of a neuron to sequences of stimuli. Neurons that exhibit SSA respond less vigorously to common stimuli, and the metric typically used to quantify this difference is the SSA index (SI). This article presents the first detailed analysis of the SI metric by examining the question: How should a system (e.g., a neuron) respond to stochastic input if it is to maximize the SI of its output? Questions like this one are particularly relevant to those wishing to construct computational models of SSA. If an artificial neural network receives stimulus information at a particular rate and must respond within a fixed time, what is the highest SI one can reasonably expect? We demonstrate that the optimum, average SI is constrained by the information in the input source, the length and encoding of the memory, and the assumptions concerning how the task is decomposed.
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Su, Xun, and Minpeng Chen. "Econometric Approaches That Consider Farmers’ Adaptation in Estimating the Impacts of Climate Change on Agriculture: A Review." Sustainability 14, no. 21 (October 22, 2022): 13700. http://dx.doi.org/10.3390/su142113700.

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The question of whether and to what extent farmers can adapt to climate change has recently gained academic interest. This paper reviews contemporary econometric approaches that assess the impacts of climate change on agriculture and consider farmer adaptation, complementing previous methodological reviews with this distinctive adaptation perspective. The value of adaptation can be measured by comparing the differences between the long-term climate change effect and the short-term weather shock effect. However, this theoretical model has not yet been well supported by empirical evidence, as it is difficult to identify true adaptation, incorporating adaptation cost, and estimated adaptation rate. Quasi-natural experiments, cost-benefit analysis, and Bayesian models are effective tools to address these methodological drawbacks. Two methods dominate in the estimation of climate effects, but each has its own advantages. A good estimate provides a trade-off between the incorporation of farmers’ adaptive behavior and the reduction in omitted variables bias. Cross-sectional data models based on climate variability can capture farmers’ long-term adaptations but are prone to bias due to omitted variables. Panel data models are more effective at mitigating omitted variable bias by applying fixed effects, but do not consider farmers’ adaptative behavior to long-term climate change. To address this dilemma, several cutting-edge approaches have been developed, including integration with the weather and climate model, the long differences approach, and the long- and short-term hybrid approach. We found three key challenges, namely: (1) exploring adaptation mechanisms, (2) the CO2 fertilization effect, and (3) estimating the distributional effects of climate impacts. We also recommend future empirical studies to incorporate satellite remote sensing data, examine the relationship between different adaptation measures, model farmers’ future climate expectations, and include adaptation costs.
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Jia, Huicong, Fang Chen, and Enyu Du. "Adaptation to Disaster Risk—An Overview." International Journal of Environmental Research and Public Health 18, no. 21 (October 25, 2021): 11187. http://dx.doi.org/10.3390/ijerph182111187.

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The role of natural disaster adaptation is increasingly being considered in academic research. The Paris Agreement and Sustainable Development Goal 13 require measuring the progress made on this adaptation. This review summarizes the development stages of adaptation, the multiple attributes and analysis of adaptation definitions, the models and methods for adaptation analysis, and the research progress of natural disaster adaptation. Adaptation research methods are generally classified into two types: case analysis and mathematical models. The current adaptive research in the field of natural disasters focuses primarily on the response of the social economy, especially the adaptive decision making and risk perception at farm-level scales (farmer households). The evaluation cases of adaptation in the field of disasters exist mostly as a part of vulnerability evaluation. Adaptation and adaptive capacity should focus on four core issues: adaptation to what; who or what adapts; how does adaptation occur; what is adaptation; and how good is the adaptation. The main purpose of the “spatial scale–exposure–vulnerability” three-dimensional scales of adaptation assessment is to explore the differences in index system under different scenarios, the spatial pattern of adaptations, and the geographical explanation of its formation mechanism. The results of this study can help and guide future research on integrating climate change and disaster adaptations especially in regional sustainable development and risk reduction strategies.
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Gorban, A. N., T. A. Tyukina, L. I. Pokidysheva, and E. V. Smirnova. "Dynamic and thermodynamic models of adaptation." Physics of Life Reviews 37 (July 2021): 17–64. http://dx.doi.org/10.1016/j.plrev.2021.03.001.

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Dissertations / Theses on the topic "Models of adaptation"

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Pennings, Pleuni. "Models of adaptation and speciation." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-66567.

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Wallin, Johan. "Dose Adaptation Based on Pharmacometric Models." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-100569.

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Many drugs exhibit major variability in both pharmacokinetic (PK) and pharmacodynamic (PD) parameters that prevents the use of the same dose for all patients. Variability can occur both between patients (IIV) as well as within patients over the course of time (IOV). In a drug with narrow therapeutic range and substantial IIV, dose selection may require individual adaptation. Adaptation can either be made before (a priori) or after (a posteriori) first drug administration. The former implies basing the dose on prior information known to be influential, such as kidney function indicators, weight or concomitant medication, whereas a posteriori dose adaptations are based on post-treatment observations. Often individualization cannot be based on the clinical outcome itself. In such cases, drug concentrations or biomarkers may be valuable for dose individualisation. In this thesis two therapeutic areas where dosing is critical have been investigated regarding the possibilities of a priori and a posteriori dose adaptation; anticancer treatment where myelosuppression is dose limiting, and tacrolimus used for immunosuppression in paediatric transplantation. In tacrolimus previously published models were found to be of little value for dose adaptation in the early critical days post-transplantation. New PK models were developed and used to suggest new dosing regimens tailored for the paediatric population, recognizing the changing pharmacokinetics in the early time post-transplantation. For several anticancer drugs covariates were identified that partly explained IIV in myelosuppression. IOV were found to be lower than IIV which implies that individual dose adaptations a posteriori can be valuable. Dose adaptation, using Bayesian principles in order to simultaneously minimise the risk of severe toxicity or subtherapeutic levels, was evaluated using simulations. Type and amount of data needed, as well as variability parameters influential on the outcome, were evaluated. Results show drug concentrations being of little value, if neutrophil counts are available. The models discussed in this thesis have been implemented in MS Excel macros for Bayesian forecasting, to allow widespread distribution to clinical settings without necessitating access to specific statistical software.
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Xu, Jiaolong. "Domain adaptation of deformable part-based models." Doctoral thesis, Universitat Autònoma de Barcelona, 2015. http://hdl.handle.net/10803/290266.

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La detecció de vianants és crucial per als sistemes d’assistència a la conducció (ADAS). Disposar d’un classificador precís és fonamental per a un detector de vianants basat en visió. Al entrenar un classificador, s’assumeix que les característiques de les dades d’entrenament segueixen la mateixa distribució de probabilitat que la de les dades de prova. Tot i això, a la pràctica, aquesta assumpció pot no complir-se per diferents causes. En aquests casos, en la comunitat de visió per computador és cada cop més comú utilitzar tècniques que permeten adaptar els classificadors existents del seu entorn d’entrenament (domini d’origen) al nou entorn de prova (domini de destí). En aquesta tesi ens centrem en l’adaptació de domini dels detectors de vianants basats en models deformables basats en parts (DPMs). Com a prova de concepte, utilitzem dades sintètiques com a domini d’origen (món virtual) i adaptem el detector DPM entrenat en el món virtual per a funcionar en diferents escenaris reals. Començem explotant al màxim les capacitats de detecció del DPM entrenant en dades del món virtual, però, tot i això, al aplicar-lo a diferents conjunts del món real, el detector encara perd poder de discriminació degut a les diferències entre el món virtual i el real. És per això, que ens centrem en l’adaptació de domini del DPM. Per començar, considerem un únic domini d’origen per a adaptar-lo a un únic domini de destí mitjançant dos mètodes d’aprenentatge per lots, l’A-SSVM i el SASSVM. Després, l’ampliem a treballar amb múltiples (sub-)dominis mitjançant una adaptació progressiva, utilitzant una jerarquia adaptativa basada en SSVM (HASSVM) en el procés d’optimització. Finalment, extenem HA-SSVM per a aconseguir un detector que s’adapti de forma progressiva i sense intervenció humana al domini de destí. Cal destacar que cap dels mètodes proposats en aquesta tesi requereix visitar les dades del domini d’origen. L’evaluació dels resultats, realitzada amb el sistema d’evaluació de Caltech, mostra que el SA-SSVM millora lleugerament respecte el ASSVM i millora en 15 punts respecte el detector no adaptat. El model jeràrquic entrenat mitjançant el HA-SSVM encara millora més els resultats de la adaptació de domini. Finalment, el mètode sequencial d’adaptació de domini ha demostrat que pot obtenir resultats comparables a la adaptació per lots, però sense necessitat d’etiquetar manualment cap exemple del domini de destí. L’adaptació de domini aplicada a la detecció de vianants és de gran importància i és una àrea que es troba relativament sense explorar. Desitgem que aquesta tesi pugui assentar les bases del treball futur d’aquesta àrea.
La detección de peatones es crucial para los sistemas de asistencia a la conducción (ADAS). Disponer de un clasificador preciso es fundamental para un detector de peatones basado en visión. Al entrenar un clasificador, se asume que las características de los datos de entrenamiento siguen la misma distribución de probabilidad que las de los datos de prueba. Sin embargo, en la práctica, esta asunción puede no cumplirse debido a diferentes causas. En estos casos, en la comunidad de visión por computador cada vez es más común utilizar técnicas que permiten adaptar los clasificadores existentes de su entorno de entrenamiento (dominio de origen) al nuevo entorno de prueba (dominio de destino). En esta tesis nos centramos en la adaptación de dominio de los detectores de peatones basados en modelos deformables basados en partes (DPMs). Como prueba de concepto, usamos como dominio de origen datos sintéticos (mundo virtual) y adaptamos el detector DPM entrenado en el mundo virtual para funcionar en diferentes escenarios reales. Comenzamos explotando al máximo las capacidades de detección del DPM entrenado en datos del mundo virtual pero, aun así, al aplicarlo a diferentes conjuntos del mundo real, el detector todavía pierde poder de discriminaci ón debido a las diferencias entre el mundo virtual y el real. Es por ello que nos centramos en la adaptación de dominio del DPM. Para comenzar, consideramos un único dominio de origen para adaptarlo a un único dominio de destino mediante dos métodos de aprendizaje por lotes, el A-SSVM y SA-SSVM. Después, lo ampliamos a trabajar con múltiples (sub-)dominios mediante una adaptación progresiva usando una jerarquía adaptativa basada en SSVM (HA-SSVM) en el proceso de optimización. Finalmente, extendimos HA-SSVM para conseguir un detector que se adapte de forma progresiva y sin intervención humana al dominio de destino. Cabe destacar que ninguno de los métodos propuestos en esta tesis requieren visitar los datos del dominio de origen. La evaluación de los resultados, realizadas con el sistema de evaluación de Caltech, muestran que el SA-SSVM mejora ligeramente respecto al A-SSVM y mejora en 15 puntos respecto al detector no adaptado. El modelo jerárquico entrenado mediante el HA-SSVM todavía mejora más los resultados de la adaptación de dominio. Finalmente, el método secuencial de adaptación de domino ha demostrado que puede obtener resultados comparables a la adaptación por lotes pero sin necesidad de etiquetar manualmente ningún ejemplo del dominio de destino. La adaptación de domino aplicada a la detección de peatones es de gran importancia y es un área que se encuentra relativamente sin explorar. Deseamos que esta tesis pueda sentar las bases del trabajo futuro en esta área.
On-board pedestrian detection is crucial for Advanced Driver Assistance Systems (ADAS). An accurate classi cation is fundamental for vision-based pedestrian detection. The underlying assumption for learning classi ers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classi ers. However, in practice, there are di erent reasons that can break this constancy assumption. Accordingly, reusing existing classi ers by adapting them from the previous training environment (source domain) to the new testing one (target domain) is an approach with increasing acceptance in the computer vision community. In this thesis we focus on the domain adaptation of deformable part-based models (DPMs) for pedestrian detection. As a prof of concept, we use a computer graphic based synthetic dataset, i.e. a virtual world, as the source domain, and adapt the virtual-world trained DPM detector to various real-world dataset. We start by exploiting the maximum detection accuracy of the virtual-world trained DPM. Even though, when operating in various real-world datasets, the virtualworld trained detector still su er from accuracy degradation due to the domain gap of virtual and real worlds. We then focus on domain adaptation of DPM. At the rst step, we consider single source and single target domain adaptation and propose two batch learning methods, namely A-SSVM and SA-SSVM. Later, we further consider leveraging multiple target (sub-)domains for progressive domain adaptation and propose a hierarchical adaptive structured SVM (HA-SSVM) for optimization. Finally, we extend HA-SSVM for the challenging online domain adaptation problem, aiming at making the detector to automatically adapt to the target domain online, without any human intervention. All of the proposed methods in this thesis do not require revisiting source domain data. The evaluations are done on the Caltech pedestrian detection benchmark. Results show that SA-SSVM slightly outperforms A-SSVM and avoids accuracy drops as high as 15 points when comparing with a non-adapted detector. The hierarchical model learned by HA-SSVM further boosts the domain adaptation performance. Finally, the online domain adaptation method has demonstrated that it can achieve comparable accuracy to the batch learned models while not requiring manually label target domain examples. Domain adaptation for pedestrian detection is of paramount importance and a relatively unexplored area. We humbly hope the work in this thesis could provide foundations for future work in this area.
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Pirrotta, Elizabeth. "Testing chromatic adaptation models using object colors /." Online version of thesis, 1994. http://hdl.handle.net/1850/11674.

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Nikolaidis, Stefanos. "Mathematical Models of Adaptation in Human-Robot Collaboration." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1121.

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While much work in human-robot interaction has focused on leaderfollower teamwork models, the recent advancement of robotic systems that have access to vast amounts of information suggests the need for robots that take into account the quality of the human decision making and actively guide people towards better ways of doing their task. This thesis proposes an equal-partners model, where human and robot engage in a dance of inference and action, and focuses on one particular instance of this dance: the robot adapts its own actions via estimating the probability of the human adapting to the robot. We start with a bounded-memory model of human adaptation parameterized by the human adaptability - the probability of the human switching towards a strategy newly demonstrated by the robot. We then examine more subtle forms of adaptation, where the human teammate adapts to the robot, without replicating the robot’s policy. We model the interaction as a repeated game, and present an optimal policy computation algorithm that has complexity linear to the number of robot actions. Integrating these models into robot action selection allows for human-robot mutual-adaptation. Human subject experiments in a variety of collaboration and shared-autonomy settings show that mutual adaptation significantly improves human-robot team performance, compared to one-way robot adaptation to the human.
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Acosta, Padilla Francisco Javier. "Self-adaptation for Internet of things applications." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S094/document.

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L'Internet des Objets (IdO) couvre peu à peu tous les aspects de notre vie. À mesure que ces systèmes deviennent plus répandus, le besoin de gérer cette infrastructure complexe comporte plusieurs défis. En effet, beaucoup de petits appareils interconnectés fournissent maintenant plus d'un service dans plusieurs aspects de notre vie quotidienne, qui doivent être adaptés à de nouveaux contextes sans l'interruption de tels services. Cependant, ce nouveau système informatique diffère des systèmes classiques principalement sur le type, la taille physique et l'accès des nœuds. Ainsi, des méthodes typiques pour gérer la couche logicielle sur de grands systèmes distribués comme on fait traditionnellement ne peuvent pas être employées dans ce contexte. En effet, cela est dû aux capacités très différentes dans la puissance de calcul et la connectivité réseau, qui sont très contraintes pour les appareils de l'IdO. De plus, la complexité qui était auparavant gérée par des experts de plusieurs domaines, tels que les systèmes embarqués et les réseaux de capteurs sans fil (WSN), est maintenant accrue par la plus grande quantité et hétérogénéité des logiciels et du matériel des nœuds. Par conséquent, nous avons besoin de méthodes efficaces pour gérer la couche logicielle de ces systèmes, en tenant compte les ressources très limitées. Cette infrastructure matérielle sous-jacente pose de nouveaux défis dans la manière dont nous administrons la couche logicielle de ces systèmes. Ces défis peuvent entre divisés en : Intra-nœud, sur lequel nous faisons face à la mémoire limitée et à la puissance de calcul des nœuds IdO, afin de gérer les mises à jour sur ces appareils ; Inter-noeud, sur lequel une nouvelle façon de distribuer les mises à jour est nécessaire, en raison de la topologie réseau différente et le coût en énergie pour les appareils alimentés par batterie ; En effet, la puissance de calcul limitée et la durée de vie de chaque nœud combiné à la nature très distribuée de ces systèmes, ajoute de la complexité à la gestion de la couche logicielle distribuée. La reconfiguration logicielle des nœuds dans l'Internet des objets est une préoccupation majeure dans plusieurs domaines d'application. En particulier, la distribution du code pour fournir des nouvelles fonctionnalités ou mettre à jour le logiciel déjà installé afin de l'adapter aux nouvelles exigences, a un impact énorme sur la consommation d'énergie. La plupart des algorithmes actuels de diffusion du code sur l'air (OTA) sont destinés à diffuser un microprogramme complet à travers de petits fragments, et sont souvent mis en œuvre dans la couche réseau, ignorant ainsi toutes les informations de guidage de la couche applicative. Première contribution : Un moteur de modèles en temps d'exécution représentant une application de l'IdO en cours d'exécution sur les nœuds à ressources limitées. La transformation du méta-modèle Kevoree en code C pour répondre aux contraintes de mémoire spécifiques d'un dispositif IdO a été réalisée, ainsi que la proposition des outils de modélisation pour manipuler un modèle en temps d'exécution. Deuxième contribution : découplage en composants d'un système IdO ainsi qu'un algorithme de distribution de composants efficace. Le découplage en composants d'une application dans le contexte de l'IdO facilite sa représentation sur le modèle en temps d'exécution, alors qu'il fournit un moyen de changer facilement son comportement en ajoutant/supprimant des composants et de modifier leurs paramètres. En outre, un mécanisme pour distribuer ces composants en utilisant un nouvel algorithme appelé Calpulli est proposé
The Internet of Things (IoT) is covering little by little every aspect on our lives. As these systems become more pervasive, the need of managing this complex infrastructure comes with several challenges. Indeed, plenty of small interconnected devices are now providing more than a service in several aspects of our everyday life, which need to be adapted to new contexts without the interruption of such services. However, this new computing system differs from classical Internet systems mainly on the type, physical size and access of the nodes. Thus, typical methods to manage the distributed software layer on large distributed systems as usual cannot be employed on this context. Indeed, this is due to the very different capacities on computing power and network connectivity, which are very constrained for IoT devices. Moreover, the complexity which was before managed by experts on several fields, such as embedded systems and Wireless Sensor Networks (WSN), is now increased by the larger quantity and heterogeneity of the node’s software and hardware. Therefore, we need efficient methods to manage the software layer of these systems, taking into account the very limited resources. This underlying hardware infrastructure raises new challenges in the way we administrate the software layer of these systems. These challenges can be divided into: intra-node, on which we face the limited memory and CPU of IoT nodes, in order to manage the software layer and ; inter-node, on which a new way to distribute the updates is needed, due to the different network topology and cost in energy for battery powered devices. Indeed, the limited computing power and battery life of each node combined with the very distributed nature of these systems, greatly adds complexity to the distributed software layer management. Software reconfiguration of nodes in the Internet of Things is a major concern for various application fields. In particular, distributing the code of updated or new software features to their final node destination in order to adapt it to new requirements, has a huge impact on energy consumption. Most current algorithms for disseminating code over the air (OTA) are meant to disseminate a complete firmware through small chunks and are often implemented at the network layer, thus ignoring all guiding information from the application layer. First contribution: A models@runtime engine able to represent an IoT running application on resource constrained nodes. The transformation of the Kevoree meta-model into C code to meet the specific memory constraints of an IoT device was performed, as well as the proposition of modelling tools to manipulate a model@runtime. Second contribution: Component decoupling of an IoT system as well as an efficient component distribution algorithm. Components decoupling of an application in the context of the IoT facilitates its representation on the model@runtime, while it provides a way to easily change its behaviour by adding/removing components and changing their parameters. In addition, a mechanism to distribute such components using a new algorithm, called Calpulli is proposed
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Gurdamar, Emre. "Adaptation Of Turbulence Models To A Navier-stokes Solver." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606568/index.pdf.

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This thesis presents the implementation of several two-equation turbulence models into a finite difference, two- and three-dimensional Navier-Stokes Solver. Theories of turbulence modeling and the historical development of these theories are briefly investigated. Turbulence models that are defined by two partial differential equations, based on k-&
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models, having different correlations, constants and boundary conditions are selected to be adapted into the base solver. The basic equations regarding the base Navier-Stokes solver to which the turbulence models are implemented presented by briefly explaining the outputs obtained from the solver. Numerical work regarding the implementation of turbulence models into the base solver is given in steps of non-dimensionalization, transformation of equations into generalized coordinate system, numerical scheme, discretization, boundary and initial conditions and limitations. These sections of implementation are investigated and presented in detail with providing every steps of work accomplished. Certain trial problems are solved and outputs are compared with experimental data. Solutions for fluid flow over flat plate, in free shear, over cylinder and airfoil are demonstrated. Airfoil validation test cases are analyzed in detail. For three dimensional applications, computation of flow over a wing is accomplished and pressure distributions from certain sections are compared with experimental data.
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Clarkson, P. R. "Adaptation of statistical language models for automatic speech recognition." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597745.

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Statistical language models encode linguistic information in such a way as to be useful to systems which process human language. Such systems include those for optical character recognition and machine translation. Currently, however, the most common application of language modelling is in automatic speech recognition, and it is this that forms the focus of this thesis. Most current speech recognition systems are dedicated to one specific task (for example, the recognition of broadcast news), and thus use a language model which has been trained on text which is appropriate to that task. If, however, one wants to perform recognition on more general language, then creating an appropriate language model is far from straightforward. A task-specific language model will often perform very badly on language from a different domain, whereas a model trained on text from many diverse styles of language might perform better in general, but will not be especially well suited to any particular domain. Thus the idea of an adaptive language model whose parameters automatically adjust to the current style of language is an appealing one. In this thesis, two adaptive language models are investigated. The first is a mixture-based model. The training text is partitioned according to the style of text, and a separate language model is constructed for each component. Each component is assigned a weighting according to its performance at modelling the observed text, and a final language model is constructed as the weighted sum of each of the mixture components. The second approach is based on a cache of recent words. Previous work has shown that words that have occurred recently have a higher probability of occurring in the immediate future than would be predicted by a standard triagram language model. This thesis investigates the hypothesis that more recent words should be considered more significant within the cache by implementing a cache in which a word's recurrence probability decays exponentially over time. The problem of how to predict the effect of a particular language model on speech recognition accuracy is also addressed in this thesis. The results presented here, as well as those of other recent research, suggest that perplexity, the most commonly used method of evaluating language models, is not as well correlated with word error rate as was once thought. This thesis investigates the connection between a language model's perplexity and its effect on speech recognition performance, and will describe the development of alternative measures of a language models' quality which are better correlated with word error rate. Finally, it is shown how the recognition performance which is achieved using mixture-based language models can be improved by optimising the mixture weights with respect to these new measures.
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Baptista, Adérito Herculano Sarmento. "Dynamic adaptation of interaction models for stateful web services." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/12042.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
Wireless Sensor Networks (WSNs) are accepted as one of the fundamental technologies for current and future science in all domains, where WSNs formed from either static or mobile sensor devices allow a low cost high-resolution sensing of the environment. Such opens the possibility of developing new kinds of crucial applications or providing more accurate data to more traditional ones. For instance, examples may range from large-scale WSNs deployed on oceans contributing to weather prediction simulations; to high number of diverse Sensor devices deployed over a geographical area at different heights from the ground for collecting more accurate data for cyclic wildfire spread simulations; or to networks of mobile phone devices contributing to urban traffic management via Participatory Sensing applications. In order to simplify data access, network parameterisation, and WSNs aggregation, WSNs have been integrated in Web environments, namely through high level standard interfaces like Web services. However, the typical interface access usually supports a restricted number of interaction models and the available mechanisms for their run-time adaptation are still scarce. Nevertheless, applications demand a richer and more flexible control on interface accesses – e.g. such accesses may depend on contextual information and, consequently, may evolve in time. Additionally, Web services have become increasingly popular in the latest years, and their usage led to the need of aggregating and coordinating them and also to represent state in between Web services invocations. Current standard composition languages for Web services (wsbpel,wsci,bpml) deal with the traditional forms of service aggregation and coordination, while WS-Resource framework (wsrf) deals with accessing services pertaining state concerns (relating both executing applications and the runtime environment). Subjacent to the notion of service coordination is the need to capture dependencies among them (through the workflow concept, for instance), reuse common interaction models, e.g. embodied in common behavioural Patterns like Client/Server, Publish/- Subscriber, Stream, and respond to dynamic events in the system (novel user requests, service failures, etc.). Dynamic adaptation, in particular, is a pressing requirement for current service-based systems due to the increasing trend on XaaS ("everything as a service") which promises to reduce costs on application development and infrastructure support, as is already apparent in the Cloud computing domain. Therefore, the self-adaptive (or dynamic/adaptive) systems present themselves as a solution to the above concerns. However, since they comprise a vast area, this thesis only focus on self-adaptive software. Concretely, we propose a novel model for dynamic interactions, in particular with Stateful Web Services, i.e. services interfacing continued activities. The solution consists on a middleware prototype based on pattern abstractions which may be able to provide (novel) richer interaction models and a few structured dynamic adaptation mechanisms, which are captured in the context of a "Session" abstraction. The middleware was implemented and uses a pre-existent framework supporting Web enabled access to WSNs, and some evaluation scenarios were tested in this setting. Namely, this area was chosen as the application domain that contextualizes this work as it contributes to the development of increasingly important applications needing highresolution and low cost sensing of environment. The result is a novel way to specify richer and dynamic modes of accessing and acquiring data generated by WSNs.
Este trabalho foi parcialmente financiado pelo Centro de Informática e Tecnologias da Informação (CITI), e pela Fundação para a Ciência e a Tecnologia (FCT / MCTES) em projectos de investigação
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Ahadi-Sarkani, Seyed Mohammad. "Bayesian and predictive techniques for speaker adaptation." Thesis, University of Cambridge, 1996. https://www.repository.cam.ac.uk/handle/1810/273100.

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Books on the topic "Models of adaptation"

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Roy, Callista. The Roy adaptation model. 3rd ed. Upper Saddle River, NJ: Pearson Prentice Hall, 2008.

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A, Andrews Heather, ed. The Roy adaptation model. Stamford, Conn: Appleton & Lange, 1999.

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1920-, Cowan G. A., Pines David 1924-, Meltzer David, and Santa Fe Institute (Santa Fe, N.M.), eds. Complexity: Metaphors, models, and reality. Reading, Mass: Addison-Wesley, 1994.

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Sohail, Siddiqui Khawar, and Thomas Torsten, eds. Protein adaptation in extremophiles. New York: Nova Biomedical Books, 2008.

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Treur, Jan, and Laila Van Ments, eds. Mental Models and Their Dynamics, Adaptation, and Control. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85821-6.

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Callista Roy: An adaptation model. Newbury Park, Calif: Sage Publications, 1991.

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Adaptation in dynamical systems. Cambridge: Cambridge University Press, 2011.

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Callista, Roy, ed. The Roy adaptation model: The definitive statement. Norwalk, Conn: Appleton & Lange, 1991.

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Environmental and Water Resources Institute (U.S.), ed. Climate change modeling, mitigation, and adaptation. Reston, Virginia: American Society of Civil Engineers, 2013.

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Hidden order: How adaptation builds complexity. Reading, Mass: Addison-Wesley, 1995.

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Book chapters on the topic "Models of adaptation"

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Fink, Gernot A. "Model Adaptation." In Markov Models for Pattern Recognition, 201–9. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6308-4_11.

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Ponting, Keith M. "Channel Adaptation." In Computational Models of Speech Pattern Processing, 112–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60087-6_12.

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Mill, Robert. "Stimulus-Specific Adaptation, Models." In Encyclopedia of Computational Neuroscience, 2883–88. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-6675-8_109.

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Mill, Robert. "Stimulus-Specific Adaptation, Models." In Encyclopedia of Computational Neuroscience, 1–7. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7320-6_109-2.

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Somogyi, Zoltán, Dóra Hidy, Györgyi Gelybó, Zoltán Barcza, Galina Churkina, László Haszpra, László Horváth, Attila Machon, and Balázs Grosz. "Models and Their Adaptation." In Atmospheric Greenhouse Gases: The Hungarian Perspective, 201–28. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9950-1_9.

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Hester, Todd, and Peter Stone. "Learning and Using Models." In Adaptation, Learning, and Optimization, 111–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27645-3_4.

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DeMori, Renato, and Marcello Federico. "Language Model Adaptation." In Computational Models of Speech Pattern Processing, 280–303. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60087-6_26.

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Fleurey, Franck, Vegard Dehlen, Nelly Bencomo, Brice Morin, and Jean-Marc Jézéquel. "Modeling and Validating Dynamic Adaptation." In Models in Software Engineering, 97–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01648-6_11.

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Lehmann, Janette, Mounia Lalmas, Elad Yom-Tov, and Georges Dupret. "Models of User Engagement." In User Modeling, Adaptation, and Personalization, 164–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31454-4_14.

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Santana, Roberto, and Siddhartha Shakya. "Probabilistic Graphical Models and Markov Networks." In Adaptation, Learning, and Optimization, 3–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28900-2_1.

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Conference papers on the topic "Models of adaptation"

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Uzunov, Anton V., Mohan Baruwal Chhetri, and John Wondoh. "GOURMET: A Methodology for Realizing Goal-Driven Self-Adaptation." In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2021. http://dx.doi.org/10.1109/models-c53483.2021.00034.

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Vogel, Thomas, and Holger Giese. "Adaptation and abstract runtime models." In the 2010 ICSE Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1808984.1808989.

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Mohammed, Mufasir Muthaher. "Dynamic adaptation for distributed systems in model-driven engineering." In MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550356.3558505.

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"Naïve Bayes Domain Adaptation for Biological Sequences." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004245500620070.

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Moisan, Sabine, Jean-Paul Rigault, and Mathieu Acher. "A feature-based approach to system deployment and adaptation." In 2012 Models in Software Engineering (MiSE). IEEE, 2012. http://dx.doi.org/10.1109/mise.2012.6226019.

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Connell, S. D., and N. K. Jain. "Writer adaptation of online handwriting models." In Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318). IEEE, 1999. http://dx.doi.org/10.1109/icdar.1999.791817.

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Zhuo Han and Kumpati S. Narendra. "Second level adaptation using multiple models." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5991086.

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Kitza, Markus, Pavel Golik, Ralf Schlüter, and Hermann Ney. "Cumulative Adaptation for BLSTM Acoustic Models." In Interspeech 2019. ISCA: ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-2162.

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Boulanger, Frederic, Cecile Hardebolle, Christophe Jacquet, and Dominique Marcadet. "Semantic Adaptation for Models of Computation." In 2011 11th International Conference on Application of Concurrency to System Design (ACSD). IEEE, 2011. http://dx.doi.org/10.1109/acsd.2011.17.

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Zahabi, Samira Tofighi, Somayeh Bakhshaei, and Shahram Khadivi. "Using topic models in domain adaptation." In 2014 7th International Symposium on Telecommunications (IST). IEEE, 2014. http://dx.doi.org/10.1109/istel.2014.7000763.

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Reports on the topic "Models of adaptation"

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Lei, Xin, Wen Wang, and Andreas Stolcke. Unsupervised Domain Adaptation with Multiple Acoustic Models. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada630345.

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Kolar, Jachym, Yang Liu, and Elizabeth Shriberg. Speaker Adaptation of Language Models for Automatic Dialog Act Segmentation of Meetings. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada469307.

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Ye, Nong. Models of Quality of Service and Quality of Information Assurance Towards Their Dynamic Adaptation. Fort Belvoir, VA: Defense Technical Information Center, March 2011. http://dx.doi.org/10.21236/ada541993.

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Wyndham, Amber, Emile Elias, Joel Brown, Michael Wilson, and Albert Rango. Drought Vulnerability Assessment to Inform Grazing Practices on Rangelands of Southeastern Colorado’s Major Land Resource Area 69. USDA Southwest Climate Hub, July 2018. http://dx.doi.org/10.32747/2018.6947062.ch.

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Increased climate variability, including more frequent and intense drought, is projected for the southwestern region of the United States. Increased temperatures and reduced precipitation lower soil water availability, resulting in decreased plant productivity and altering species composition, which may affect forage quality and quantity. Reduced forage quality and increased heat stress attributable to warmer temperatures could lead to decreased livestock performance in this system, which is extensively used for livestock grazing. Mitigating the effects of increasing drought is critical to social and ecological stability in the region. Reduced stocking rates, change in livestock breeds and/or grazing practices are general recommendations that could be implemented to cope with increased climatic stress. Ecological Sites and their associated state–and-transition models (STMs) are tools to help land managers implement and evaluate responses to disturbances. The projected change in climate will vary depending upon geographic location. Vulnerability assessments and adaptation strategies are needed at the local level to inform local management decisions and help ameliorate the effects of climate change on rangelands. The United States Department of Agriculture (USDA) Southwest Climate Hub and Natural Resources Conservation Service (NRCS) worked together to produce this drought vulnerability assessment at the Major Land Resource Area (MLRA) level, based on ecological sites and state-and-transition models that will help landowners and government agencies to identify and develop adaptation options for drought on rangelands. The assessment illustrates how site-specific information can be used to help minimize the effects of drought on rangelands and support informed decision-making for the selection of management adaptations within MLRA 69.
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Wyndham, Amber, Emile Elias, Joel R. Brown, Michael A. Wilson, and Albert Rango. Drought Vulnerability Assessment to Inform Grazing Practices on Rangelands in Southeast Arizona and Southwest New Mexico’s Major Land Resource Area 41. United States. Department of Agriculture. Southwest Climate Hub, August 2018. http://dx.doi.org/10.32747/2018.6818230.ch.

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Increased climate variability, including more frequent and intense drought, is projected for the southwestern region of the United States. Increased temperatures and reduced precipitation lower soil water availability, resulting in decreased plant productivity and altered species composition, which may affect forage quality and quantity. Reduced forage quality and increased heat stress attributable to warmer temperatures could lead to decreased livestock performance in this system, which is extensively used for livestock grazing. Mitigating the effects of increasing drought is critical to social and ecological stability in the region. Reduced stocking rates and/or a change in livestock breeds and/or grazing practices are general recommendations that could be implemented to cope with increased climatic stress. Ecological Sites (ESs) and their associated state-and-transition models (STMs) are tools to help land managers implement and evaluate responses to disturbances. The projected change in climate will vary depending upon geographic location. Vulnerability assessments and adaptation strategies are necessary at the local level to inform local management decisions and help to ameliorate the effects of climate change on rangelands. The USDA Southwest Climate Hub and the Natural Resources Conservation Service (NRCS) worked together to produce this drought vulnerability assessment at the Major Land Resource Area (MLRA) level: it is based on ESs/STMs that will help landowners and government agencies to identify and develop adaptation options for drought on rangelands. The assessment illustrates how site-specific information can be used to help minimize the effects of drought on rangelands and to support informed decision-making for selecting management adaptations within MLRA 41.
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Wyndham, Amber, Emile Elias, Joel R. Brown, Michael A. Wilson, and Albert Rango. Drought Vulnerability Assessment to Inform Grazing Practices on Rangelands of Southeastern Colorado’s Major Land Resource Area 69. United States. Department of Agriculture. Southwest Climate Hub, January 2018. http://dx.doi.org/10.32747/2018.6876399.ch.

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Increased climate variability, including more frequent and intense drought, is projected for the southwestern region of the United States. Increased temperatures and reduced precipitation lower soil water availability resulting in decreased plant productivity and altering species composition which may affect forage quality and quantity. Reduced forage quality and increased heat stress attributable to warmer temperatures could lead to decreased livestock performance in this system, which is extensively used for livestock grazing. Mitigating the effects of increasing drought is critical to social and ecological stability in the region. Reduced stocking rates, change in livestock breeds and/or grazing practices are general recommendations that could be implemented to cope with increased climatic stress. Ecological Sites (ESs) and their associated state and transition models (STMs) are tools to help land managers implement and evaluate responses to disturbances. The projected change in climate will vary depending on geographic location. Vulnerability assessments and adaptation strategies are needed at the local level to inform local management decisions and help ameliorate the effects of climate change on rangelands. The USDA Southwest Climate Hub and Natural Resources Conservation Service (NRCS) worked together to produce this drought vulnerability assessment at the Major Land Resource Area (MLRA) level based on ESs/STMs that will help landowners and government agencies identify and develop adaptation options for drought on rangelands. The assessment illustrates how site-specific information can be used to help minimize the effects of drought on rangelands and support informed decision-making for selecting management adaptations within MLRA 69.
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Wyndham, Amber, Emile Elias, Joel Brown, Michael Wilson, and Albert Rango Rango. Drought Vulnerability Assessment to Inform Grazing Practices on Rangelands in Southeast Arizona and Southwest New Mexico’s Major Land Resource Area 41. USDA Southwest Climate Hub, August 2018. http://dx.doi.org/10.32747/2018.6947060.ch.

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Increased climate variability, including more frequent and intense drought, is projected for the southwestern region of the United States. Increased temperatures and reduced precipitation lower soil water availability, resulting in decreased plant productivity and altered species composition, which may affect forage quality and quantity. Reduced forage quality and increased heat stress attributable to warmer temperatures could lead to decreased livestock performance in this system, which is extensively used for livestock grazing. Mitigating the effects of increasing drought is critical to social and ecological stability in the region. Reduced stocking rates and/or a change in livestock breeds and/or grazing practices are general recommendations that could be implemented to cope with increased climatic stress. Ecological Sites (ESs) and their associated state-and-transition models (STMs) are tools to help land managers implement and evaluate responses to disturbances. The projected change in climate will vary depending upon geographic location. Vulnerability assessments and adaptation strategies are necessary at the local level to inform local management decisions and help to ameliorate the effects of climate change on rangelands. The USDA Southwest Climate Hub and the Natural Resources Conservation Service (NRCS) worked together to produce this drought vulnerability assessment at the Major Land Resource Area (MLRA) level: it is based on ESs/STMs that will help landowners and government agencies to identify and develop adaptation options for drought on rangelands. The assessment illustrates how site-specific information can be used to help minimize the effects of drought on rangelands and to support informed decision-making for selecting management adaptations within MLRA 41.
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8

Wyndham, Amber, Emile Elias, Joel Brown, Michael Wilson, and Albert Rango. Drought Vulnerability Assessment to Inform Grazing Practices on Rangelands of Southeastern Colorado’s Major Land Resource Area 69. USDA Southwest Climate Hub, March 2018. http://dx.doi.org/10.32747/2018.6965584.ch.

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Abstract:
Increased climate variability, including more frequent and intense drought, is projected for the southwestern region of the United States. Increased temperatures and reduced precipitation lower soil water availability resulting in decreased plant productivity and altering species composition which may affect forage quality and quantity. Reduced forage quality and increased heat stress attributable to warmer temperatures could lead to decreased livestock performance in this system, which is extensively used for livestock grazing. Mitigating the effects of increasing drought is critical to social and ecological stability in the region. Reduced stocking rates, change in livestock breeds and/or grazing practices are general recommendations that could be implemented to cope with increased climatic stress. Ecological Sites (ESs) and their associated state and transition models (STMs) are tools to help land managers implement and evaluate responses to disturbances. The projected change in climate will vary depending on geographic location. Vulnerability assessments and adaptation strategies are needed at the local level to inform local management decisions and help ameliorate the effects of climate change on rangelands. The USDA Southwest Climate Hub and Natural Resources Conservation Service (NRCS) worked together to produce this drought vulnerability assessment at the Major Land Resource Area (MLRA) level based on ESs/STMs that will help landowners and government agencies identify and develop adaptation options for drought on rangelands. The assessment illustrates how site-specific information can be used to help minimize the effects of drought on rangelands and support informed decision-making for selecting management adaptations within MLRA 69.
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Erulkar, Annabel, and Erica Chong. Evaluation of a savings and micro-credit program for vulnerable young women in Nairobi. Population Council, 2005. http://dx.doi.org/10.31899/pgy19.1010.

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Tap and Reposition Youth (TRY) was a four-year initiative undertaken by the Population Council and K-Rep Development Agency to reduce adolescents’ vulnerabilities to adverse social and reproductive health outcomes by improving livelihoods options. The project targeted out-of-school adolescent girls and young women aged 16–22 residing in low-income and slum areas of Nairobi. TRY used a modified group-based micro-finance model to extend integrated savings, credit, business support, and mentoring to out-of-school adolescents and young women. A longitudinal study of participants was conducted with a matched comparison group identified through cross-sectional community-based studies, undertaken at baseline and endline to enable an assessment of changes associated with the project. This report states that 326 participants and their controls were interviewed at baseline and 222 pairs were interviewed at endline. The results suggest that rigorous micro-finance models may be appropriate for a subset of girls, especially those who are older and less vulnerable. The impact on noneconomic indicators is less clear. Additional experimentation and adaptation is required to develop livelihoods models that acknowledge and respond to the particular situation of adolescent girls.
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Pradhananga, Saurav, Arthur Lutz, Archana Shrestha, Indira Kadel, Bikash Nepal, and Santosh Nepal. Selection and downscaling of general circulation model datasets and extreme climate indices analysis - Manual. International Centre for Integrated Mountain Development (ICIMOD), 2020. http://dx.doi.org/10.53055/icimod.4.

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A supplement to the Climate Change Scenarios for Nepal report published by the Ministry of Forests and Environment for the National Adaptation Plan (NAP) Process, this manual provides detailed information about the processes through which the assessment highlighted in the report can be carried out. They include – selection of the general circulation/climate models (GCMs), downscaling of the GCM dataset, assessment of changes in precipitation and temperature, and assessment of change in climate extremes. The manual downscales climate datasets for the Koshi River basin, the Kabul River basin, and the Kailash Sacred Landscape to analyse future scenarios in these basins and the landscape.
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