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Journal articles on the topic 'Dynamic adaptation'

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Published: 4 June 2021

Last updated: 25 May 2024

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1

Wang, Jinsung, and Robert L. Sainburg. "Interlimb Transfer of Novel Inertial Dynamics Is Asymmetrical." Journal of Neurophysiology 92, no. 1 (July 2004): 349–60. http://dx.doi.org/10.1152/jn.00960.2003.

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Mechanisms underlying interlimb transfer of adaptation to visuomotor rotations have recently been explored in depth. However, little data are available regarding interlimb transfer of adaptation to novel inertial dynamics. The present study thus investigated interlimb transfer of dynamics by examining the effect of initial training with one arm on subsequent performance with the other in adaptation to a 1.5-kg mass attached eccentrically to the forearm. Using inverse dynamic analysis, we examined the changes in torque strategies associated with adaptation to the extra mass, and with interlimb transfer of that adaptation. Following initial training with the dominant arm, nondominant arm performance improved substantially in terms of linearity and initial direction control as compared with naïve performance. However, initial training with the nondominant arm had no effect on subsequent performance with the dominant arm. Inverse dynamic analysis revealed that improvements in kinematics were implemented by increasing flexor muscle torques at the elbow to counter load-induced increases in extensor interaction torques as well as increasing flexor muscle torques at the shoulder to counter the extensor actions of elbow muscle torque. Following opposite arm adaptation, the nondominant arm adopted this dynamic strategy early in adaptation. These findings suggest that dominant arm adaptation to novel inertial dynamics leads to information that can be accessed and utilized by the opposite arm controller, but not vice versa. When compared with our previous findings on interlimb transfer of visuomotor rotations, our current findings suggest that adaptations to visuomotor and dynamic transformations are mediated by distinct neural mechanisms.

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2

Hirschfeld, Robert, and Katsuya Kawamura. "Dynamic service adaptation." Software: Practice and Experience 36, no. 11-12 (2006): 1115–31. http://dx.doi.org/10.1002/spe.766.

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3

Cottrell, Garrison W., Mai Nguyen, and Fu-Sheng Tsung. "Dynamic rate adaptation." Artificial Intelligence Review 7, no. 5 (October 1993): 271–83. http://dx.doi.org/10.1007/bf00849055.

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4

Brogi, Antonio, Javier Cámara, Carlos Canal, Javier Cubo, and Ernesto Pimentel. "Dynamic Contextual Adaptation." Electronic Notes in Theoretical Computer Science 175, no. 2 (June 2007): 81–95. http://dx.doi.org/10.1016/j.entcs.2007.03.005.

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5

Sonnleitner, B. "Dynamic adaptation of microbes." Journal of Biotechnology 65, no. 1 (September 1998): 47–60. http://dx.doi.org/10.1016/s0168-1656(98)00121-7.

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6

Chandrasekhara, M. S., M. C. Wilder, and L. W. Carr. "Compressible Dynamic Stall Control Using Dynamic Shape Adaptation." AIAA Journal 39, no. 10 (October 2001): 2021–24. http://dx.doi.org/10.2514/2.1196.

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7

Chandrasekhara, M. S., M. C. Wilder, and L. W. Carr. "Compressible dynamic stall control using dynamic shape adaptation." AIAA Journal 39 (January 2001): 2021–24. http://dx.doi.org/10.2514/3.14964.

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8

Field, Douglas P., Thomas F. Shipley, and Douglas W. Cunningham. "Prism adaptation to dynamic events." Perception & Psychophysics 61, no. 1 (January 1999): 161–76. http://dx.doi.org/10.3758/bf03211957.

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9

Mazhukin, A. V., and V. I. Mazhukin. "Dynamic adaptation for parabolic equations." Computational Mathematics and Mathematical Physics 47, no. 11 (November 2007): 1833–55. http://dx.doi.org/10.1134/s0965542507110097.

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10

Ortin, Francisco, and Juan Manuel Cueva. "Dynamic adaptation of application aspects." Journal of Systems and Software 71, no. 3 (May 2004): 229–43. http://dx.doi.org/10.1016/s0164-1212(02)00157-7.

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11

Benda, Jan, Leonard Maler, and André Longtin. "Linear Versus Nonlinear Signal Transmission in Neuron Models With Adaptation Currents or Dynamic Thresholds." Journal of Neurophysiology 104, no. 5 (November 2010): 2806–20. http://dx.doi.org/10.1152/jn.00240.2010.

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Spike-frequency adaptation is a prominent aspect of neuronal dynamics that shapes a neuron's signal processing properties on timescales ranging from about 10 ms to >1 s. For integrate-and-fire model neurons spike-frequency adaptation is incorporated either as an adaptation current or as a dynamic firing threshold. Whether a physiologically observed adaptation mechanism should be modeled as an adaptation current or a dynamic threshold, however, is not known. Here we show that a dynamic threshold has a divisive effect on the onset f–I curve (the initial maximal firing rate following a step increase in an input current) measured at increasing mean threshold levels, i.e., adaptation states. In contrast, an adaptation current subtractively shifts this f–I curve to higher inputs without affecting its slope. As a consequence, an adaptation current acts essentially linearly, resulting in a high-pass filter component of the neuron's transfer function for current stimuli. With a dynamic threshold, however, the transfer function strongly depends on the input range because of the multiplicative effect on the f–I curves. Simulations of conductance-based spiking models with adaptation currents, such as afterhyperpolarization (AHP)-type, M-type, and sodium-activated potassium currents, do not show the divisive effects of a dynamic threshold, but agree with the properties of integrate-and-fire neurons with adaptation current. Notably, the effects of slow inactivation of sodium currents cannot be reproduced by either model. Our results suggest that, when lateral shifts of the onset f–I curve are seen in response to adapting inputs, adaptation should be modeled with adaptation currents and not with a dynamic threshold. In contrast, when the slope of onset f–I curves depends on the adaptation state, then adaptation should be modeled with a dynamic threshold. Further, the observation of divisively altered onset f–I curves in adapted neurons with notable variability of their spike threshold could hint to yet known biophysical mechanisms directly affecting the threshold.

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12

Lidz, Carol S., and Elizabeth D. Peña. "Dynamic Assessment." Language, Speech, and Hearing Services in Schools 27, no. 4 (October 1996): 367–72. http://dx.doi.org/10.1044/0161-1461.2704.367.

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This article describes the dynamic assessment model, an alternative approach to the diagnostic assessment of young children. This model is adaptable for use by all members of the multidisciplinary team. Specific adaptation as a diagnostic measure for speech-language pathologists working with preschool Latino children has been successful in differentiating language differences from language deficiencies. The article describes the research and offers two case illustrations to demonstrate application of this adaptation.

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13

Nax, Heinrich H. "Uncoupled Aspiration Adaptation Dynamics Into the Core." German Economic Review 20, no. 2 (May 1, 2019): 243–56. http://dx.doi.org/10.1111/geer.12160.

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Abstract Dynamics for play of transferable-utility cooperative games are proposed that require information regarding own payoff experiences and other players’ past actions, but not regarding other players’ payoffs. The proposed dynamics provide an evolutionary interpretation of the proto-dynamic ‘blocking argument’ (Edgeworth, 1881) based on the behavioral principles of ‘aspiration adaptation’ (Sauermann and Selten, 1962) instead of best response. If the game has a non-empty core, the dynamics are absorbed into the core in finite time with probability one. If the core is empty, the dynamics cycle infinitely through all coalitions.

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14

Gearhart, Stephannie S. "‘These are modern times’: Nostalgia and the adaptation of history in Billy Morrissette’s Scotland, PA." Journal of Adaptation in Film & Performance 13, no. 1 (March 1, 2020): 23–35. http://dx.doi.org/10.1386/jafp_00010_1.

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Set in America in the 1970s, Billy Morrissette’s 2001 adaptation of Shakespeare’s Macbeth, Scotland, PA, waivers between nostalgia and critique. In order to understand the film’s conflicting attitudes towards the era in which it is set and to appreciate how adaptations, generally, often feel ambivalent about their past(s), this essay begins by discussing Scotland, PA’s construction of the 1970s. In an effort to answer Lynne Bradley’s call for ‘a new model’ of modern adaptation, seeing it as ‘a complex double gesture’, the essay discusses how although Scotland, PA appears to illustrate many of the qualities of what Fredric Jameson has called the nostalgia film, this categorization of the adaptation neither accounts for its use of irony nor for the inherently complex nature of nostalgia. Ultimately, Scotland, PA’s ambivalence about history, the essay proposes, encourages us to conceive of the relationship between source/past and adaptation/present as a site of complex, dynamic negotiations rather than a static dichotomy that obliges us to choose between an adaptation’s acceptance or rejection of its forebears.

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15

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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16

MAZHUKIN, A. V. "Dynamic Adaptation In Convection — Diffusion Equations." Computational Methods in Applied Mathematics 8, no. 2 (2008): 171–86. http://dx.doi.org/10.2478/cmam-2008-0012.

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Abstract With the example of solving some known modeling problems the fea-tures of constructing grids adapted to the solution of parabolic equations are consid-ered. Convection-diffusion problems are described by nonlinear Burgers and Buckley — Leverette equations. A detailed analysis of the differential approximations and numerical results shows that the idea of using an arbitrary time-dependent system of coordinates for adapted grid generation in combination with the principle of quasi-stationarity makes the dy-namic adaptation method universal, effective, and algorithmically simple. Universality is achieved due to the use of an arbitrary time-dependent system of co-ordinates that moves at a velocity determined by the unknown solution. This universal approach makes it possible to generate adapted grids for time-dependent problems of mathematical physics with various mathematical features. Among these features are large gradients, and propagation of weak and strong discontinuities in known nonlinear transfer problems. The efficiency is determined by automatically fitting the velocity of the moving nodes to the dynamics of the solution. The close relationship between the adaptation mechanism and the structure of parabolic equations allows one to automatically control nodes motion of nodes so that their trajectories do not intersect. The simplicity of the algorithm is achieved due to the general approach to the adaptive grid generation that is independent of the form and type of the differential equations.

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17

Hassan, Sara, Rami Bahsoon, Leandro Minku, and Nour Ali. "Dynamic Evaluation of Microservice Granularity Adaptation." ACM Transactions on Autonomous and Adaptive Systems 16, no. 2 (June 30, 2021): 1–35. http://dx.doi.org/10.1145/3502724.

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Microservices have gained acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. Among the critical microservice architecture design decisions is when to adapt the granularity of a microservice architecture by merging/decomposing microservices. No existing work investigates the following question: How can we reason about the trade-off between predicted benefits and cost of pursuing microservice granularity adaptation under uncertainty? To address this question, we provide a novel formulation of the decision problem to pursue granularity adaptation as a real options problem. We propose a novel evaluation process for dynamically evaluating granularity adaptation design decisions under uncertainty. Our process is based on a novel combination of real options and the concept of Bayesian surprises. We show the benefits of our evaluation process by comparing it to four representative industrial microservice runtime monitoring tools, which can be used for retrospective evaluation for granularity adaptation decisions. Our comparison shows that our process can supersede and/or complement these tools. We implement a microservice application—Filmflix—using Amazon Web Service Lambda and use this implementation as a case study to show the unique benefit of our process compared to traditional application of real options analysis.

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18

Siu-Nam Chuang and A. T. S. Chan. "Dynamic QoS Adaptation for Mobile Middleware." IEEE Transactions on Software Engineering 34, no. 6 (November 2008): 738–52. http://dx.doi.org/10.1109/tse.2008.44.

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19

Wang, Jindong, Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, and Qiang Yang. "Transfer Learning with Dynamic Distribution Adaptation." ACM Transactions on Intelligent Systems and Technology 11, no. 1 (February 11, 2020): 1–25. http://dx.doi.org/10.1145/3360309.

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20

Morin, Brice, Olivier Barais, Jean-Marc Jezequel, Franck Fleurey, and Arnor Solberg. "Models@ Run.time to Support Dynamic Adaptation." Computer 42, no. 10 (October 2009): 44–51. http://dx.doi.org/10.1109/mc.2009.327.

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21

Solarz, P. F., V. I. Rotger, and A. A. Salas. "Dynamic adaptation software for virtual interconsultation." Journal of Physics: Conference Series 477 (December 31, 2013): 012013. http://dx.doi.org/10.1088/1742-6596/477/1/012013.

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22

Johnson, O. Kenneth. "Simple adaptation for dynamic Bogota bag." Tropical Doctor 46, no. 1 (March 29, 2015): 64–66. http://dx.doi.org/10.1177/0049475515578060.

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23

Charvillat, Vincent, and Romulus Grigoraş. "Reinforcement learning for dynamic multimedia adaptation." Journal of Network and Computer Applications 30, no. 3 (August 2007): 1034–58. http://dx.doi.org/10.1016/j.jnca.2005.12.010.

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24

VÁRHELYI, András. "DYNAMIC SPEED ADAPTATION IN ADVERSE CONDITIONS." IATSS Research 26, no. 2 (2002): 52–59. http://dx.doi.org/10.1016/s0386-1112(14)60043-1.

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25

Moreira, Rui S., José Torres, Pedro Sobral, Ricardo Morla, Mark Rouncefield, and Gordon S. Blair. "Dynamic adaptation of personal ubicomp environments." Personal and Ubiquitous Computing 20, no. 2 (March 10, 2016): 165–66. http://dx.doi.org/10.1007/s00779-016-0909-9.

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26

Solomon, Ralf, and J. Leo van Hemmen. "Accelerating backpropagation through dynamic self-adaptation." Neural Networks 9, no. 4 (June 1996): 589–601. http://dx.doi.org/10.1016/0893-6080(95)00144-1.

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27

Dubach, Christophe, Timothy M. Jones, and Edwin V. Bonilla. "Dynamic microarchitectural adaptation using machine learning." ACM Transactions on Architecture and Code Optimization 10, no. 4 (December 2013): 1–28. http://dx.doi.org/10.1145/2541228.2541238.

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28

Khan, M. A. "Data Cache Prefetching With Dynamic Adaptation." Computer Journal 54, no. 5 (March 19, 2010): 815–23. http://dx.doi.org/10.1093/comjnl/bxq028.

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29

Bihari, Thomas E., and Karsten Schwan. "Dynamic adaptation of real-time software." ACM Transactions on Computer Systems 9, no. 2 (May 1991): 143–74. http://dx.doi.org/10.1145/103720.103723.

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30

Stieglitz, Nils, Thorbjørn Knudsen, and Markus C. Becker. "Adaptation and inertia in dynamic environments." Strategic Management Journal 37, no. 9 (September 13, 2015): 1854–64. http://dx.doi.org/10.1002/smj.2433.

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31

DRAKE, R., and V. S. MANORANJAN. "A METHOD OF DYNAMIC MESH ADAPTATION." International Journal for Numerical Methods in Engineering 39, no. 6 (March 30, 1996): 939–49. http://dx.doi.org/10.1002/(sici)1097-0207(19960330)39:6<939::aid-nme888>3.0.co;2-a.

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32

Simionescu, Cristian, and George Stoica. "Efficient Dynamic Batch Adaptation (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (June 26, 2023): 16328–29. http://dx.doi.org/10.1609/aaai.v37i13.27024.

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In this paper we introduce Efficient Dynamic Batch Adaptation (EDBA), which improves on a previous method that works by adjusting the composition and the size of the current batch. Our improvements allow for Dynamic Batch Adaptation to feasibly scale up for bigger models and datasets, drastically improving model convergence and generalization. We show how the method is still able to perform especially well in data-scarce scenarios, managing to obtain a test accuracy on 100 samples of CIFAR-10 of 90.68%, while the baseline only reaches 23.79%. On the full CIFAR-10 dataset, EDBA reaches convergence in ∼120 epochs while the baseline requires ∼300 epochs.

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33

Spieringhs, Rik M., Michael J. Murdoch, and Ingrid M. L. C. Vogels. "Time course of chromatic adaptation under dynamic lighting." Color and Imaging Conference 2019, no. 1 (October 21, 2019): 13–18. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.4.

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Chromatic adaptation is an extensively studied concept. However, less is known about the time course of chromatic adaptation under gradually-changing lighting. Two experiments were carried out to quantify the time course of chromatic adaptation under dynamic lighting. In the first experiment, a step change in lighting chromaticity was used. The time course of adaptation was well described by the Rinner and Gegenfurtner slow adaptation exponential model [Vision Research, 40(14), 2000], and the adaptation state after saturation differed between observers. In the second experiment, chromatic adaptation was measured in response to two different speeds of lighting chromaticity transitions. An adjusted exponential model was able to fit the observed time course of adaptation for both lighting transition speeds.

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34

Breslavsky, P. V., and V. I. Mazhukin. "Simulation of Interacting Discontinious Solutions on Dynamically Adaptive Grids." Computational Methods in Applied Mathematics 7, no. 2 (2007): 103–17. http://dx.doi.org/10.2478/cmam-2007-0006.

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Abstract A further development of the dynamic adaptation method for gas dy- namic problems describing multiple interactions of the shock waves, rarefaction waves, and contact boundaries are considered. By the test Woodward — Colella problem the efficiency of the proposed method for solving problems of gas dynamics with explicit definition of shock waves and contact boundaries is shown. For the problem solution mechanism of the adaptation of diffusion type is used. A choice of the adaptation coeffi- cient for obtaining solution in each of subdomains of quasiuniform grid is substantiated. The discontinuities interaction between each other is solved by the Riemann problem. Application of the dynamic adaptation method allowed obtaining solution in 420 cells which practically coincides with the results of WENO5m method in 12800 cells.

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35

Wen, Bo, Grace I. Wang, Isabel Dean, and Bertrand Delgutte. "Time course of dynamic range adaptation in the auditory nerve." Journal of Neurophysiology 108, no. 1 (July 1, 2012): 69–82. http://dx.doi.org/10.1152/jn.00055.2012.

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Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds.

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36

Park, Jae-Han, Ji-Hun Bae, and Moon-Hong Baeg. "Adaptation Algorithm of Geometric Graphs for Robot Motion Planning in Dynamic Environments." Mathematical Problems in Engineering 2016 (2016): 1–19. http://dx.doi.org/10.1155/2016/3973467.

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This study proposes an adaptive graph algorithm for collision-free motion planning of articulated robots in dynamic environments. For this purpose, deformations of the configuration space were analyzed according to the changes of the workspace using various simulations. Subsequently, we adopted the principles of gas motion dynamics in our adaptation algorithm to address the issue of the deformation of the configuration space. The proposed algorithm has an adaptation mechanism based on expansive repulsion and sensory repulsion, and it can be performed to provide the entire adaptation using distributed processing. The simulation results confirmed that the proposed method allows the adaptation of the roadmap graph to changes of the configuration space.

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37

Musaev, Alexander, and Ekaterina Borovinskaya. "Evolutionary Optimization of Case-Based Forecasting Algorithms in Chaotic Environments." Symmetry 13, no. 2 (February 10, 2021): 301. http://dx.doi.org/10.3390/sym13020301.

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The problem of dynamic adaptation of prediction algorithms in chaotic environments based on identification of the situations-analogs in the database of retrospective observations is considered. Under conditions of symmetrical and unsymmetrical chaotic dynamics, traditional computational schemes of precedent prediction turn out to be ineffective. In this regard, a dynamic adaptation of precedent analysis algorithms based on the method of evolutionary modeling is proposed. Implementation of the computational precedent prediction scheme for chaotic processes as well as the evolutionary modeling method are described.

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38

Titzmann, Peter F., and Richard M. Lee. "Adaptation of Young Immigrants." European Psychologist 23, no. 1 (January 2018): 72–82. http://dx.doi.org/10.1027/1016-9040/a000313.

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Abstract. We draw upon developmental psychology theory to highlight the developmental process of acculturation in adolescent immigrants. First, we describe different ways in which development and acculturation have been combined in past research on immigrant youth. These studies mainly considered developmental and acculturation-related changes, predictors, and stages, or utilized the developmental context model by Bronfenbrenner (1977) . However, developmental considerations are often only implicitly implemented in existing research and not in a very systematic manner. The dynamic aspects of development are particularly understated in acculturation research. For this reason, we reference and expand upon concepts pertaining to the biological, social, and psychological changes in pubertal development to highlight ways in which acculturation research can be made more dynamic and less static. We specifically present the concepts of acculturative timing, tempo, pace, and synchronicity as a means to systematically study acculturative changes over time in immigrant adolescents. In summary, in this review, we present a more dynamic and less static understanding of acculturation processes that includes normative developmental aspects for a more complex understanding of immigrant youth’s psychosocial adaptation.

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39

Small, D. L., and C. E. Morris. "Delayed activation of single mechanosensitive channels in Lymnaea neurons." American Journal of Physiology-Cell Physiology 267, no. 2 (August 1, 1994): C598—C606. http://dx.doi.org/10.1152/ajpcell.1994.267.2.c598.

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Some stretch-activated (SA) channels challenged with suction jumps exhibit adaptation, a dynamic behavior that can be overlooked because of its mechanical fragility. In previous studies of neuronal SA K channels, we detected no adaptation, but the protocols used were not designed to detect dynamics. Here, we reproduce the adaptation seen by others in Xenopus SA cationic (Cat) channels but show that, with the same protocol, no adaptation occurs with SA K channels. Instead, SA K channels exhibit a different dynamic behavior, delayed activation. Lymnaea SA K channels subjected to pressure jumps responded after a 1- to 4-s delay with a gradual, rather than abrupt, onset of activation. The delay was pressure dependent and was longer for patches from older cultured neurons. Delayed responses were fragile like SA Cat channel adaptation; they disappeared with repeated stimuli. Cytochalasin D decreased the delay and increased the stretch activation of SA K channels. Unlike SA Cat channel adaptation, which occurs only at hyperpolarized potentials, SA K channel delay was not voltage dependent. We note that once SA Cat and SA K channels are "stripped" of their fragile (cytoskeleton-dependent?) dynamics, however, their gating behaviors show little fundamental difference; both are stretch activatable and have a higher open probability at depolarized potentials.

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40

Wanda, Paul A., Gang Li, and Kurt A. Thoroughman. "State dependence of adaptation of force output following movement observation." Journal of Neurophysiology 110, no. 5 (September 1, 2013): 1246–56. http://dx.doi.org/10.1152/jn.00353.2012.

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Humans readily learn to move through direct physical practice and by watching the movements of others. Some researchers have proposed that action observation can inform subsequent changes in control through the acquisition of a neural representation of the novel dynamics, but to date learning following observation has been described by kinematic metrics. Here we designed an experiment to consider the specificity of adaptation to novel dynamic perturbations at the level of force generation. We measured changes in temporal patterns of force output following either the performance or observation of movements perturbed by either position- or velocity-dependent dynamic environments to 1) establish whether previously described observational motor learning effects were attributable to changes in predictive limb control and 2) determine whether such adaptation reflected a learned dependence on limb states appropriate to the haptic environment. We found that subjects who observed perturbed movements produced significant compensatory changes in their lateral force output, despite never directly experiencing force perturbations firsthand while performing the motor task. The time series of observers' adapted force outputs suggested that the state dependence of observed dynamics shapes adaptation. We conclude that the brain can transform observation of kinematics into state-dependent adaptation of reach dynamics.

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41

Orr, Alastair, Jason Donovan, and Dietmar Stoian. "Smallholder value chains as complex adaptive systems: a conceptual framework." Journal of Agribusiness in Developing and Emerging Economies 8, no. 1 (March 12, 2018): 14–33. http://dx.doi.org/10.1108/jadee-03-2017-0031.

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Purpose Smallholder value chains are dynamic, changing over time in sudden, unpredictable ways as they adapt to shocks. Understanding these dynamics and adaptation is essential for these chains to remain competitive in turbulent markets. Many guides to value chain development, though they focus welcome attention on snapshots of current structure and performance, pay limited attention to the dynamic forces affecting these chains or to adaptation. The paper aims to discuss these issues. Design/methodology/approach This paper develops an expanded conceptual framework to understand value chain performance based on the theory of complex adaptive systems. The framework combines seven common properties of complex systems: time, uncertainty, sensitivity to initial conditions, endogenous shocks, sudden change, interacting agents and adaptation. Findings The authors outline how the framework can be used to ask new research questions and analyze case studies in order to improve our understanding of the development of smallholder value chains and their capacity for adaptation. Research limitations/implications The framework highlights the need for greater attention to value chain dynamics. Originality/value The framework offers a new perspective on the dynamics of smallholder value chains.

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42

Gavrikov, Mikhail. "Algorithm for Dynamic Scaling Adaptation Pattern Functions." University News. North-Caucasian Region. Technical Sciences Series, no. 1 (March 2016): 3–9. http://dx.doi.org/10.17213/0321-2653-2016-1-3-9.

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43

Awad, Mirna, Nadjia Kara, and Claes Edstrom. "SLO-aware dynamic self-adaptation of resources." Future Generation Computer Systems 133 (August 2022): 266–80. http://dx.doi.org/10.1016/j.future.2022.03.018.

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44

Bertoldi, Nicola. "Dynamic Models in Moses for Online Adaptation." Prague Bulletin of Mathematical Linguistics 101, no. 1 (April 1, 2014): 7–28. http://dx.doi.org/10.2478/pralin-2014-0001.

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Abstract A very hot issue for research and industry is how to effectively integrate machine translation (MT) within computer assisted translation (CAT) software. This paper focuses on this issue, and more generally how to dynamically adapt phrase-based statistical machine translation (SMT) by exploiting external knowledge, like the post-editions from professional translators. We present an enhancement of the Moses SMT toolkit dynamically adaptable to external information, which becomes available during the translation process, and which can depend on the previously translated text. We have equipped Moses with two new elements: a new phrase table implementation and a new LM-like feature. Both the phrase table and the LM-like feature can be dynamically modified by adding and removing entries and re-scoring them according to a time-decaying scoring function. The final goal of these two dynamically adaptable features is twofold: to create additional translation alternatives and to reward those which are composed of entries previously inserted therein. The implemented dynamic system is highly configurable, flexible and applicable to many tasks, like for instance online MT adaptation, interactive MT, and context-aware MT. When exploited in a real-world CAT scenario where online adaptation is applied to repetitive texts, it has proven itself very effective in improving translation quality and reducing post-editing effort.

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Cufflin, Matthew P., and Edward A. H. Mallen. "Dynamic Accommodation Responses Following Adaptation to Defocus." Optometry and Vision Science 85, no. 10 (October 2008): 982–91. http://dx.doi.org/10.1097/opx.0b013e3181886fda.

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Iselin, John P., Joseph M. Prusa, and William J. Gutowski. "Dynamic Grid Adaptation Using the MPDATA Scheme." Monthly Weather Review 130, no. 4 (April 2002): 1026–39. http://dx.doi.org/10.1175/1520-0493(2002)130<1026:dgautm>2.0.co;2.

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van Dijk, Marijn, Paul van Geert, Katharina Korecky-Kröll, Isabelle Maillochon, Sabine Laaha, Wolfgang U. Dressler, and Dominique Bassano. "Dynamic Adaptation in Child-Adult Language Interaction." Language Learning 63, no. 2 (March 5, 2013): 243–70. http://dx.doi.org/10.1111/lang.12002.

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Paz-Filgueira, Clemente, Michael R. Tan, and Dingcai Cao. "Dynamic of ON and OFF chromatic adaptation." Journal of Vision 19, no. 10 (September 6, 2019): 70a. http://dx.doi.org/10.1167/19.10.70a.

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Nogueira, Luis, and Eugenio Oliveira. "Improving brokering adaptation in dynamic heterogeneous environments." International Journal of Product Lifecycle Management 2, no. 2 (2007): 113. http://dx.doi.org/10.1504/ijplm.2007.014275.

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Andova, S., L. P. J. Groenewegen, and E. P. de Vink. "Dynamic adaptation with distributed control in Paradigm." Science of Computer Programming 94 (November 2014): 333–61. http://dx.doi.org/10.1016/j.scico.2013.11.034.

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