Relevant bibliographies by topics / Adaptive snapshots

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Adaptive snapshots'

Author: Grafiati
Published: 29 August 2023

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Journal articles on the topic "Adaptive snapshots"

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YU, Jing, and Yaan LI. "Adaptive Beamforming with Inadequate Snapshots." Journal of Physics: Conference Series 787 (January 2017): 012025. http://dx.doi.org/10.1088/1742-6596/787/1/012025.

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Liao, Zhipeng, Keqing Duan, Jinjun He, Zizhou Qiu, and Binbin Li. "Robust Adaptive Beamforming Based on a Convolutional Neural Network." Electronics 12, no. 12 (June 20, 2023): 2751. http://dx.doi.org/10.3390/electronics12122751.

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To address the advancements in jamming technology, it is imperative to consider robust adaptive beamforming (RBF) methods with finite snapshots and gain/phase (G/P) errors. This paper introduces an end-to-end RBF approach that utilizes a two-stage convolutional neural network. The first stage includes convolutional blocks and residual blocks without downsampling; the blocks assess the covariance matrix precisely using finite snapshots. The second stage maps the first stage’s output to an adaptive weight vector employing a similar structure to the first stage. The two stages are pre-trained with different datasets and fine-tuned as end-to-end networks, simplifying the network training process. The two-stage structure enables the network to possess practical physical meaning, allowing for satisfying performance even with a few snapshots in the presence of array G/P errors. We demonstrate the resulting beamformer’s performance with numerical examples and compare it to various other adaptive beamformers.
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Wu, Xun, Jie Luo, Guowei Li, Shurui Zhang, and Weixing Sheng. "Fast Wideband Beamforming Using Convolutional Neural Network." Remote Sensing 15, no. 3 (January 25, 2023): 712. http://dx.doi.org/10.3390/rs15030712.

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With the wideband beamforming approaches, the synthetic aperture radar (SAR) could achieve high azimuth resolution and wide swath. However, the performance of conventional adaptive wideband time-domain beamforming is severely affected as the received signal snapshots are insufficient for adaptive approaches. In this paper, a wideband beamformer using convolutional neural network (CNN) method, namely, frequency constraint wideband beamforming prediction network (WBPNet), is proposed to obtain a satisfactory performance in the circumstances of scanty snapshots. The proposed WBPNet successfully estimates the direction of arrival of interference with scanty snapshots and obtains the optimal weights with effectively null for the interference by utilizing the uniqueness of CNN to extract potential nonlinear features of input information. Meanwhile, the novel beamformer has an undistorted response to the wideband signal of interest. Compared with the conventional time-domain wideband beamforming algorithm, the proposed method can fast obtain adaptive weights because of using few snapshots. Moreover, the proposed WBPNet has a satisfactory performance on wideband beamforming with low computational complexity because it avoids the inverse operation of covariance matrix. Simulation results show the meliority and feasibility of the proposed approach.
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Gong, C., L. Huang, D. Xu, and Z. Ye. "Knowledge‐aided robust adaptive beamforming with small snapshots." Electronics Letters 49, no. 20 (September 2013): 1258–59. http://dx.doi.org/10.1049/el.2013.2198.

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Brooker, D. J., Kay L. Gemba, and Laurie T. Fialkowski. "Overcoming snapshot-deficient measurements with knowledge-aided approaches." JASA Express Letters 2, no. 5 (May 2022): 054804. http://dx.doi.org/10.1121/10.0010455.

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The use of knowledge-aided covariance is considered for processing underwater acoustic array data in snapshot-deficient scenarios. The knowledge-aided formalism is a technique that combines array data with a known covariance to produce an invertible estimate. For underwater acoustics, simulations of ambient noise provide the a priori covariance allowing degraded signals to be processed adaptively in situations where the sample covariance matrix is rank-deficient. The method is demonstrated for matched field processing using the 21 element array event S5 from the SWellEx-96 experiment. With five snapshots, the knowledge-aided approach significantly reduces localization ambiguity compared to the adaptive white noise gain constraint processor.
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Sun, Xu, and Ranwei Li. "Robust adaptive beamforming method for active sonar in single snapshot." MATEC Web of Conferences 283 (2019): 03006. http://dx.doi.org/10.1051/matecconf/201928303006.

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Forming narrow beams is a useful way for active sonar to anti-reverberation when it works in the shallow water. High-resolution adaptive beamforming with the performance of narrow beamwidths and low sidelobe levels is a better and more efficient method, particularly in the scenario where the installation space for sonar array is limited, such as hull-mounted sonar. Due to the short duration of target echo signal in the complex and varying acoustic channel, conventional adaptive beamforming methods are invalid. Therefore, this paper proposes a robust adaptive beamforming method for active sonar in single snapshot, also called the steered dominant mode rejection (STDMR). Firstly, STDMR steered the sample covariance matrix (STCM) based on wide-band focusing, which the needed number of snapshots is greatly reduced. Secondly, by partial eigendecomposition, the large eigenvalues of the STCM which are greater than the noise energy and their eigenvectors are used for dominant mode rejection (DMR). DMR is a typical eigenspace-based algorithm which has small computational load and fast convergence speed. Finally, modified with the methods of diagonal loading of 3-5dB over the noise energy and signal mismatch protection, improved the robustness of this method. Simulation and experimental data analysis shows that the STDMR method achieves narrow beams and low-level sidelobes in single snapshot. Hence, the STDMR beamformer is an appropriate implementation to use for active sonar detection systems.
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Wang, He, Ting Zhang, Lei Cheng, and Hangfang Zhao. "Snapshot-deficient active target localization in beam-time domain using multi-frequency expectation-maximization algorithm." Journal of the Acoustical Society of America 153, no. 2 (February 2023): 990–1003. http://dx.doi.org/10.1121/10.0017164.

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The two-dimensional (2D) active target localization is generally hindered by the high temporal and spatial sidelobe levels in snapshot-deficient scenarios, where the adaptive approaches undergo performance degeneration since they require many snapshots to build the sample covariance matrix. Aiming at working robustly in snapshot-deficient active scenarios, a 2D expectation-maximization-based vertical-time-record (EMVTR) approach is proposed to compensate for the snapshot deficiency and achieve the high-resolution active localization by reconstructing the covariance matrix using estimated hyperparameters, i.e., signal powers and noise variance. With the short-time Fourier transform, the proposed approach could reduce echoes' temporal correlation and attain robust beam-time localization in mild reverberation. The multi-frequency EMVTR is derived from the single-frequency case to improve the weak echo localization. The performance is evaluated by considering single and multiple target echoes in simulation and a single moving target with tank experimental data. The results manifest the proposed EMVTR's robustness and effectiveness for the 2D active localization in snapshot-deficient scenarios.
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Ullmann, Sebastian, Marko Rotkvic, and Jens Lang. "POD-Galerkin reduced-order modeling with adaptive finite element snapshots." Journal of Computational Physics 325 (November 2016): 244–58. http://dx.doi.org/10.1016/j.jcp.2016.08.018.

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Li, Hongtao, Ke Wang, Chaoyu Wang, Yapeng He, and Xiaohua Zhu. "Robust Adaptive Beamforming Based on Worst-Case and Norm Constraint." International Journal of Antennas and Propagation 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/765385.

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A novel robust adaptive beamforming based on worst-case and norm constraint (RAB-WC-NC) is presented. The proposed beamforming possesses superior robustness against array steering vector (ASV) error with finite snapshots by using the norm constraint and worst-case performance optimization (WCPO) techniques. Simulation results demonstrate the validity and superiority of the proposed algorithm.
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Cui, Weichen, Tong Wang, Degen Wang, and Kun Liu. "An Efficient Sparse Bayesian Learning STAP Algorithm with Adaptive Laplace Prior." Remote Sensing 14, no. 15 (July 22, 2022): 3520. http://dx.doi.org/10.3390/rs14153520.

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Space-time adaptive processing (STAP) encounters severe performance degradation with insufficient training samples in inhomogeneous environments. Sparse Bayesian learning (SBL) algorithms have attracted extensive attention because of their robust and self-regularizing nature. In this study, a computationally efficient SBL STAP algorithm with adaptive Laplace prior is developed. Firstly, a hierarchical Bayesian model with adaptive Laplace prior for complex-value space-time snapshots (CALM-SBL) is formulated. Laplace prior enforces the sparsity more heavily than Gaussian, which achieves a better reconstruction of the clutter plus noise covariance matrix (CNCM). However, similar to other SBL-based algorithms, a large degree of freedom will bring a heavy burden to the real-time processing system. To overcome this drawback, an efficient localized reduced-dimension sparse recovery-based space-time adaptive processing (LRDSR-STAP) framework is proposed in this paper. By using a set of deeply weighted Doppler filters and exploiting prior knowledge of the clutter ridge, a novel localized reduced-dimension dictionary is constructed, and the computational load can be considerably reduced. Numerical experiments validate that the proposed method achieves better performance with significantly reduced computational complexity in limited snapshots scenarios. It can be found that the proposed LRDSR-CALM-STAP algorithm has the potential to be implemented in practical real-time processing systems.
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Dissertations / Theses on the topic "Adaptive snapshots"

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Chetry, Manisha. "Advanced reduced-order modeling and parametric sampling for non-Newtonian fluid flows." Electronic Thesis or Diss., Ecole centrale de Nantes, 2023. http://www.theses.fr/2023ECDN0011.

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Le sujet de cette thèse porte sur laréduction d'ordre de modèle (MOR) deproblèmes d'écoulement non-Newtonianparamétrés qui ont des applicationsindustrielles importantes. Les méthodestraditionnelles de réduction de l'ordre desmodèles limitent les performances decalcul de ces problèmes hautement nonlinéaires, nous suggérons donc une techniqued'hyper-réduction avancée basée sur uneapproximation sparse de l'évaluation destermes non linéaire à complexité reduite.Nous proposons également une stratégie destabilisation hors ligne pour stabiliser le modèleconstitutif dans le modèle d'ordre réduit quiest moins cher à calculer tout en maintenant laprécision du modèle d'ordre complet. Lacombinaison des deux réduit drastiquement lecoût du processeur, augmentantinévitablement les performances du MOR. Cetravail est validé sur deux problèmes debenchmark. En outre, une stratégied'échantillonnage adaptatif est égalementprésentée dans ce manuscrit, qui est réaliséeen tirant parti de l'approximation des modèlesmulti-fidélité. Vers la fin de la thèse, nousabordons un autre problème qui estgénéralement observé dans les cas où desmaillages d'éléments finis adaptatifs sontdéployés. Dans de tels cas, les méthodes MORne parviennent pas à produire unereprésentation de faible dimension car lessnapshots ne sont pas des vecteurs de mêmelongueur. Par conséquent, nous suggérons uneméthodologie qui peut générer des fonctionsde base réduites pour des snapshotsadaptative
The subject of this thesis concernsmodel-order reduction (MOR) of parameterizednon-Newtonian flow problems that havesignificant industrial applications. TraditionalMOR methods constrain the computationalperformance of such highly nonlinear problems,so we suggest a state-of-the-art hyper-reductiontechnique based on a sparse approximation totackle the evaluation of nonlinear terms at muchreduced complexity. We also provide offlinestabilization strategy for stabilizing theconstitutive model in the reduced order modelframework that is less expensive to computewhile maintaining the full order model's (FOM)accuracy. Combining the two significantlylowers the CPU cost as compared to the FOMevaluation which inevitably boosts MORperformance. This work is validated on twobenchmark flow problems. Additionally, anadaptive sampling strategy is also presented inthis manuscript which is achieved byleveraging multi-fidelity model approximation.Towards the end of the thesis, we addressanother issue that is typically observed forcases when adaptive finite element meshesare deployed. In such cases, MOR methods failto produce a low-dimensional representationsince the snapshots are not vectors of samelength. We therefore, suggest an alternatemethod that can generate reduced basisfunctions for database of space-adaptedsnapshots
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Kraay, Andrea L. (Andrea Lorraine) 1976. "Physically constrained maximum likelihood method for snapshot deficient adaptive array processing." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87331.

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Thesis (Elec.E. and S.M. in Electrical Engineering)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2003.
"February 2003."
Includes bibliographical references (leaves 139-141).
by Andrea L. Kraay.
Elec.E.and S.M.in Electrical Engineering
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Minet, Jean. "Imagerie multispectrale, vers une conception adaptée à la détection de cibles." Phd thesis, Université Paris Sud - Paris XI, 2011. http://pastel.archives-ouvertes.fr/pastel-00714207.

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L'imagerie hyperspectrale, qui consiste à acquérir l'image d'une scène dans un grand nombre de bandes spectrales, permet de détecter des cibles là où l'imagerie couleur classique ne permettrait pas de conclure. Les imageurs hyperspectraux à acquisition séquentielle sont inadaptés aux applications de détection en temps réel. Dans cette thèse, nous proposons d'utiliser un imageur multispectral snapshot, capable d'acquérir simultanément un nombre réduit de bandes spectrales sur un unique détecteur matriciel. Le capteur offrant un nombre de pixels limité, il est nécessaire de réaliser un compromis en choisissant soigneusement le nombre et les profils spectraux des filtres de l'imageur afin d'optimiser la performance de détection. Dans cet objectif, nous avons développé une méthode de sélection de bandes qui peut être utilisée dans la conception d'imageurs multispectraux basés sur une matrice de filtres fixes ou accordables. Nous montrons, à partir d'images hyperspectrales issues de différentes campagnes de mesure, que la sélection des bandes spectrales à acquérir peut conduire à des imageurs multispectraux capables de détecter des cibles ou des anomalies avec une efficacité de détection proche de celle obtenue avec une résolution hyperspectrale. Nous développons conjointement un démonstrateur constitué d'une matrice de 4 filtres de Fabry-Perot accordables électroniquement en vue de son implantation sur un imageur multispectral snapshot agile. Ces filtres sont développés en technologie MOEMS (microsystèmes opto-électro-mécaniques) en partenariat avec l'Institut d'Electronique Fondamentale. Nous présentons le dimensionnement optique du dispositif ainsi qu'une étude de tolérancement qui a permis de valider sa faisabilité.
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Books on the topic "Adaptive snapshots"

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Holland, John H. 4. Agents, networks, degree, and recirculation. Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199662548.003.0004.

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‘Agents, networks, degree, and recirculation’ explains that when studying complex adaptive systems (CAS) in a grammar-like way, agents serve as the ‘alphabet’. The hierarchical organization of CAS implies different kinds of agents at different levels, with correspondingly different grammars. The interactions of signal-processing agents at a point in time can be specified by a network—a snapshot of the agents’ performance capability. The combination of high fanout (the richness of an agent’s interactions) and hierarchical organization results in complex networks that include large numbers of sequences that form loops. More complex loops allow the CAS to ‘look ahead’, examining the effects of various action sequences without actually executing the actions.
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Clodfelter, Richard. Retail Buying. 7th ed. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501375651.

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Retail Buying, Seventh Edition integrates math concepts throughout the text to guide students through typical buying tasks, from identifying potential customers, to creating a six-month merchandising plan, to developing sales forecasts. Updated with examples and trends from across the world, this book will keep readers informed on how the retailing industry is adapting to changes like an increased focus on sustainability, the growth of digital retailing, and impacts from the coronavirus pandemic. Practice problems and updated information tables further help students to analyze and interpret data across relevant subjects like global buying and sourcing, omnichannel retailing, and social media. New to this Edition: -Updated coverage of the coronavirus pandemic and the expanding usage of social media and mobile technologies -Increased emphasis on product sustainability and changing consumer behavior -New and updated Trendwatch and Snapshot features Instructor Resources -The Instructor’s Guide provides suggestions for planning the course and using the text in the classroom, including sample syllabi, in-class activities, and teaching ideas -The Test Bank includes sample test questions for each chapter -PowerPoint® presentations include images from the book and provide a framework for lecture and discussion STUDIO Features Include: -Study smarter with self-assessment quizzes featuring scored results and personalized study tips -Review concepts with flashcards of essential vocabulary and basic retail math formulas -Practice your skills with downloadable Excel spreadsheets to complete the end-of-chapter Spreadsheet Skills exercises -Enhance your knowledge with printable worksheets featuring step-by-step solutions to common retail buying math problems -Watch videos related to chapter concepts
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Book chapters on the topic "Adaptive snapshots"

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Kastian, Steffen, and Stefanie Reese. "An Adaptive Way of Choosing Significant Snapshots for Proper Orthogonal Decomposition." In IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, 67–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21013-7_5.

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Scherer, Cordula, and Agnese Cretella. "Sustainable Seafood Consumption: A Matter of Individual Choice or Global Market? A Window into Dublin’s Seafood Scene." In Ocean Governance, 233–51. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-20740-2_10.

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AbstractSeafood consumption is considered a key element for food security and for nutrition related policies. However, seafood is often not easily accessible or perceived as a popular option even by those living in close proximity to the sea, especially in the western world. Common culprits are usually identified as a lack of specialized shops, culinary knowledge or as the disconnection with local coastal cultural heritage. This is, for instance, the case in Ireland: Irish waters provide a great diversity of seafood and yet, its domestic consumption remains unusually low for an island nation. Most of Ireland’s seafood is exported to other countries, whilst the Irish stick to the popular salmon, cod and tuna; a consumption habit that has obvious sustainability externalities. This contribution aims to unpack the issues connected to seafood consumption in Ireland’s coastal capital Dublin and offers a window into the city’s seafood scene. Data presented were gained within Food Smart Dublin, a multidisciplinary research project designed to encourage a behavioural shift of consumption towards more sustainable local seafood. The project’s purpose was to reconnect Dublin’s society with their tangible and intangible coastal cultural heritage by rediscovering and adapting historical recipes. The paper thus connects past, present, and future perspectives on the topic. First, the past is explored by delineating the potential of marine historical heritage in stimulating sustainable seafood consumption with the reintroduction of traditional Irish recipes. The present offers a data snapshot on consumption patterns towards seafood gathered from structured online questionnaires results from the Food Smart Dublin project. Respondents offered insights into their relationship with the sea, on the frequency with which they consume seafood and the obstacles they see in consuming more of it. Finally, these perspectives delineate possible future scenarios and recommended governance actions to support policymakers in designing a better and more sustainable seafood system.
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"Direct Data Domain Least Squares Approaches to Adaptive Processing Based on Single Snapshots of Data." In Smart Antennas, 75–102. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471722839.ch4.

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Costello, Robert. "Supporting the Needs of the Independent Learner Within Higher Education." In Strategic Collaborative Innovations in Organizational Systems, 140–59. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7390-6.ch007.

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This chapter offers a case study in adaptive personalized learning for higher education learners. The chapter presents a postgraduate recommender system for educational pathway to aid with online support towards selecting suitable transferable skills depending on department and captures a current snapshot of the current trends that the university is facing.
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Zhao, Y. "Ontology Mapping Techniques in Information Integration." In Adaptive Technologies and Business Integration, 308–28. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-048-6.ch015.

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The semantic Web suggests to annotate Web resources with machine-processable metadata; and ontologies, as means to conceptualize and structure knowledge, are seen as the key to realize the vision of the semantic Web. However, ontologies themselves do not provide semantic interoperability, since a single ontology cannot be used to represent all kinds of domains and applications. Ontology mapping, therefore, is introduced to achieve knowledge sharing and semantic integration in an environment with different underlying ontologies. This chapter provides an overview of the approaches to information integration developed by researchers in the community of ontology mapping. After introducing the backgrounds and concepts of ontology mapping, a comprehensive and detailed treatment of different ontology mapping schemes is presented. Closely related aspects of ontology mapping, such as mapping result description, similarity measures, algorithm performance evaluation and so forth, have also been addressed. The emphasis is to present a snapshot of the fast-growing field in a manner suitable for both experts and non-specialists.
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Christopher, Spencer. "Life-Span Changes in Activities, and Consequent Changes in the Cognition and Assessment of the Environment." In Environment, Cognition, and Action. Oxford University Press, 1992. http://dx.doi.org/10.1093/oso/9780195062205.003.0021.

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In this chapter, I sketch an integrated account of environmental assessment, cognition, and action throughout the individual’s life span. Zimring and Gross (this volume) have already described how the schema is structured to include all three aspects; Canter (this volume) has extended this to stress the social context of meanings and actions in which these schema operate; and this chapter accepts and develops their positions. What further can a life-span approach add to the arguments advanced in these earlier integrative chapters? Liben (this volume) has already stated the case most powerfully with respect to her topic, environmental cognition; and it can as easily be applied to evaluation and action. A life-span approach enables development to be put in context: what earlier stages have so far equipped the individual to do, what the demands of the current situation are on the individual, and how variations at the present stage can affect later development. Taking this developmental perspective throws the emphasis on process and on the adaptive nature of the environmental schema for the particular life stage reached by the individual. As such, the perspective provides a test bed for examining the range of theoretical relationships between affect, cognition, and action in the environment advanced in earlier chapters. The life-span approach can also serve to reintroduce into the field a sense of the importance of individual differences, and continuities of individuality through life, which is conspicuously missing from many of the earlier chapters. The developmental tradition within psychology has not, as a whole, stressed individual differences as much as has done the life-span developmental. The life-span perspective has been much concerned with continuities and developments within the individual, as goals and tasks change over the life course. Much mainstream “developmental” research lacks this sense of continuity, being often presented as a series of snapshots of the typical child at different ages or stages. In contrast, the life-span approach, as Liben’s chapter reminds us, emphasizes the processes whereby developments occur, and conceptualizes this development as affected by biological changes, psychological development, changes in the individual’s social role and context, cultural forces, and historical changes during the individual’s life span.
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Zappalaglio, Andrea. "Sui generis, bureaucratic and based on origin: a snapshot of the nature of EU Geographical Indications." In Intellectual Property as a Complex Adaptive System, 132–52. Edward Elgar Publishing, 2021. http://dx.doi.org/10.4337/9781800378384.00018.

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"Direction of Arrival Estimation and Adaptive Processing Using a Nonuniformly Spaced Array from a Single Snapshot." In Smart Antennas, 147–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471722839.ch6.

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Heltzel, Lisa, and Judith R. Homberg. "Animal models of post-traumatic stress disorder." In Genes, brain, and emotions, 324–42. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198793014.003.0022.

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Fear learning and memory allows organisms to respond adaptively to cues and contexts that are associated with danger upon a future encounter. Sometimes fear responses go awry, leading to an intrusive fear memory failing to extinguish, eliciting an intense, distressing, and persisting response. These are core symptoms of post-traumatic stress disorder (PTSD). There are substantial individual differences in fear learning and memory, such that some are resilient and other are vulnerable to PTSD. In this chapter we set-out the methods to measure fear learning and memory in rodents, discuss their translational value, and present currently available behavioural methods to measure resilience versus vulnerability. Regarding vulnerability factors we focus on biological factors (e.g. altered function of the hypothalamus-pituitary-adrenal axis), genotype (e.g. serotonin transporter, BDNF), age (pre-adolescence, adolescence, adulthood), and gender. This chapter provides a snapshot of the state-of-the-art of animal and behavioural models to investigate individual differences in vulnerability to PTSD.
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Conference papers on the topic "Adaptive snapshots"

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Geretto, Elia, Cristiano Giuffrida, Herbert Bos, and Erik Van Der Kouwe. "Snappy: Efficient Fuzzing with Adaptive and Mutable Snapshots." In ACSAC: Annual Computer Security Applications Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3564625.3564639.

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Zaharov, Viktor V., and Marvi Teixeira. "Adaptive Digital Non-Blind Beamformer for Small Number of Snapshots." In 2006 49th IEEE International Midwest Symposium on Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/mwscas.2006.382058.

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Pan, Yundeng, Paul Liu, and Dong Liu. "Adaptive Multiple Snapshots with Matrix Pencil Method for Color Flow Imaging." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5162279.

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Mueller, C., and J. Lang. "A POD-Galerkin Model for Convection-Diffusion-Reaction Equations with Parametric Data based on Adaptive Snapshots." In XI International Conference on Adaptive Modeling and Simulation. CIMNE, 2023. http://dx.doi.org/10.23967/admos.2023.006.

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Weng, Junjie, Jun Liu, and Siyu Sun. "DOA Estimation with Few Snapshots Based on Iterative Adaptive Approach and Eigenvalue Decomposition." In 2022 IEEE 22nd International Conference on Communication Technology (ICCT). IEEE, 2022. http://dx.doi.org/10.1109/icct56141.2022.10073164.

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Gu, Yujie, and Yimin D. Zhang. "Single-Snapshot Adaptive Beamforming." In 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2018. http://dx.doi.org/10.1109/sam.2018.8448680.

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Afek, Yehuda, Gideon Stupp, and Dan Touitou. "Long-lived and adaptive atomic snapshot and immediate snapshot (extended abstract)." In the nineteenth annual ACM symposium. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/343477.343521.

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Brodie, C. Harrison, and Christopher M. Collier. "Spatial light modulation and optical mixing for snapshot hyperspectral imaging architectures." In Unconventional Imaging and Adaptive Optics 2021, edited by Jean J. Dolne and Mark F. Spencer. SPIE, 2021. http://dx.doi.org/10.1117/12.2594261.

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Bashari, Benyamin, and Philipp Woelfel. "An Efficient Adaptive Partial Snapshot Implementation." In PODC '21: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3465084.3467939.

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Hassanien, Aboulnasr, and Elias Aboutanios. "Single-Snapshot Beamforming using Fast Iterative Adaptive Techniques." In 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2020. http://dx.doi.org/10.1109/sam48682.2020.9104350.

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Reports on the topic "Adaptive snapshots"

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Oxberry, Geoffrey M., Tanya Kostova-Vassilevska, Bill Arrighi, and Kyle Chand. Limited-memory adaptive snapshot selection for proper orthogonal decomposition. Office of Scientific and Technical Information (OSTI), April 2015. http://dx.doi.org/10.2172/1224940.

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