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Journal articles on the topic 'Reinforcement Theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Schoenfeld, William N. "“Reinforcement” in Behavior Theory." Behavior Analyst 18, no. 1 (1995): 173–85. http://dx.doi.org/10.1007/bf03392705.

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2

Maeda, Shin-ichi. "Theory of Reinforcement Learning." Journal of the Robotics Society of Japan 39, no. 7 (2021): 621–24. http://dx.doi.org/10.7210/jrsj.39.621.

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3

Dolatyar, Khalil, and Benjamin R. Walker. "Reinforcement sensitivity theory and mindfulness." Personality and Individual Differences 163 (September 2020): 110089. http://dx.doi.org/10.1016/j.paid.2020.110089.

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4

Corr, Philip J. "Reinforcement sensitivity theory and personality." Neuroscience & Biobehavioral Reviews 28, no. 3 (2004): 317–32. http://dx.doi.org/10.1016/j.neubiorev.2004.01.005.

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5

Adams, Mark A. "Reinforcement theory and behavior analysis." Behavioral Development Bulletin 9, no. 1 (2000): 3–6. http://dx.doi.org/10.1037/h0100529.

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6

Kruglikov, Ilja L., and Philipp E. Scherer. "General theory of skin reinforcement." PLOS ONE 12, no. 8 (2017): e0182865. http://dx.doi.org/10.1371/journal.pone.0182865.

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7

Villere, Maurice F., and Sandra S. Hartman. "Reinforcement Theory: A Practical Tool." Leadership & Organization Development Journal 12, no. 2 (1991): 27–31. http://dx.doi.org/10.1108/01437739110138039.

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8

Cho, Young Tae, Duck Young Yoon, and Kwang Hee Im. "Damage Theory for Discontinuously-Reinforced Composites Including Cracked Inhomogeneity." International Journal of Modern Physics B 17, no. 08n09 (2003): 1801–7. http://dx.doi.org/10.1142/s0217979203019691.

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In particle or short-fiber reinforced composites, cracking of the reinforcements is a significant damage mode because the cracked reinforcements lose load carrying capacity. This paper deals with an incremental damage theory of particle or short-fiber reinforced composites. The composite undergoing damage process contains intact and broken reinforcements in a matrix. To describe the load carrying capacity of the cracked reinforcement, the average stress of a cracked ellipsoidal inhomogeneity in infinite body, which was proposed in the previous paper is introduced. An incremental constitutive r

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9

Johnson, Judith L., Lucy M. Kim, Thorayya S. Giovannelli, and Tiffany Cagle. "Reinforcement sensitivity theory, vengeance, and forgiveness." Personality and Individual Differences 48, no. 5 (2010): 612–16. http://dx.doi.org/10.1016/j.paid.2009.12.018.

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10

Balzano, M., and G. Paderni. "Stochastic reinforcement problems and ergodic theory." Proceedings of the Royal Society of Edinburgh: Section A Mathematics 121, no. 1-2 (1992): 33–53. http://dx.doi.org/10.1017/s030821050001413x.

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SynopsisWe study the asymptotic behaviour of Dirichlet problems in domains of R2 bounded by thin layers whose thickness is given by means of an assigned ergodic random function. Using a capacitary method together with ergodic theorems for additive and superadditive processes, we are able to characterise the limit problem precisely.

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11

Brauer, Jonathan R., and Charles R. Tittle. "Social Learning Theory and Human Reinforcement." Sociological Spectrum 32, no. 2 (2012): 157–77. http://dx.doi.org/10.1080/02732173.2012.646160.

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12

Smillie, Luke D., and Chris J. Jackson. "Functional Impulsivity and Reinforcement Sensitivity Theory." Journal of Personality 74, no. 1 (2006): 47–84. http://dx.doi.org/10.1111/j.1467-6494.2005.00369.x.

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13

Shahan, Timothy A., and Paul Cunningham. "Conditioned reinforcement and information theory reconsidered." Journal of the Experimental Analysis of Behavior 103, no. 2 (2015): 405–18. http://dx.doi.org/10.1002/jeab.142.

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14

Krupić, Dino, and Philip J. Corr. "How reinforcement sensitivity theory relates to self-determination theory." Personality and Individual Differences 155 (March 2020): 109705. http://dx.doi.org/10.1016/j.paid.2019.109705.

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15

Xing, Xiangyang, Jianzhong Pei, Chenchen Shen, et al. "Performance and Reinforcement Mechanism of Modified Asphalt Binders with Nano-Particles, Whiskers, and Fibers." Applied Sciences 9, no. 15 (2019): 2995. http://dx.doi.org/10.3390/app9152995.

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The asphalt binders could be modified to improve road perfo rmances by using various methods, and the reinforcement mechanisms are obviously different and quietly affect the road performances. According to the composite reinforcement theory, nano-CaCO3 particles, CaCO3 whiskers, and aramid fibers were used as reinforcements to prepare modified asphalt binders, and the conventional technical performances and dynamic shear rheometer (DSR) rheological properties were measured and investigated. In addition, scanning electron microscopy (SEM) was applied to observe the interfaces between reinforcem

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16

Smederevac, Snežana, Dušanka Mitrović, Petar Čolović, and Željka Nikolašević. "Validation of the Measure of Revised Reinforcement Sensitivity Theory Constructs." Journal of Individual Differences 35, no. 1 (2014): 12–21. http://dx.doi.org/10.1027/1614-0001/a000121.

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The paper presents validation of the Reinforcement Sensitivity Questionnaire (RSQ), measuring the constructs of the Revised Reinforcement Sensitivity theory (RST). The research was conducted on a sample of 565 participants, using three measures of the constructs of the Revised Reinforcement Sensitivity Theory – the Behavioral Inhibition System/Behavioral Approach System (BIS/BAS) scale, Reinforcement Sensitivity Theory Personality Questionnaire (RST-PQ), and Reinforcement Sensitivity Questionnaire. The results of confirmatory factor analysis suggest good internal validity of the RSQ, while the

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17

TUYLS, KARL, and ANN NOWÉ. "Evolutionary game theory and multi-agent reinforcement learning." Knowledge Engineering Review 20, no. 1 (2005): 63–90. http://dx.doi.org/10.1017/s026988890500041x.

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In this paper we survey the basics of reinforcement learning and (evolutionary) game theory, applied to the field of multi-agent systems. This paper contains three parts. We start with an overview on the fundamentals of reinforcement learning. Next we summarize the most important aspects of evolutionary game theory. Finally, we discuss the state-of-the-art of multi-agent reinforcement learning and the mathematical connection with evolutionary game theory.

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18

Zizzo, Daniel John. "From reinforcement of acts to reinforcement of social preferences." Behavioral and Brain Sciences 25, no. 2 (2002): 282–83. http://dx.doi.org/10.1017/s0140525x02570059.

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Rachlin rightly highlights behavioural reinforcement, conditional cooperation, and framing. However, genes may explain part of the variance in altruistic behaviour. Framing cannot be used to support his theory of altruism. Reinforcement of acts is not identical to reinforcement of patterns of acts. Further, many patterns of acts could be reinforced, and Rachlin's altruism is not the most likely candidate.

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19

Dayan, P., and N. D. Daw. "Decision theory, reinforcement learning, and the brain." Cognitive, Affective, & Behavioral Neuroscience 8, no. 4 (2008): 429–53. http://dx.doi.org/10.3758/cabn.8.4.429.

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20

Jackson, Chris J. "Gray's Reinforcement Sensitivity Theory: a psychometric critique." Personality and Individual Differences 34, no. 3 (2003): 533–44. http://dx.doi.org/10.1016/s0191-8869(02)00305-7.

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21

Thompson, A. G., and C. R. Windsor. "Cement grouts in theory and reinforcement practice." International Journal of Rock Mechanics and Mining Sciences 35, no. 4-5 (1998): 407–8. http://dx.doi.org/10.1016/s0148-9062(98)00093-x.

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22

Staddon, J. E. R. "Feeding by Numbers: Foraging and Reinforcement Theory." Contemporary Psychology: A Journal of Reviews 34, no. 7 (1989): 682–83. http://dx.doi.org/10.1037/030925.

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23

Doya, Kenji. "Reinforcement learning: Computational theory and biological mechanisms." HFSP Journal 1, no. 1 (2007): 30–40. http://dx.doi.org/10.2976/1.2732246/10.2976/1.

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24

Jara-Ettinger, Julian. "Theory of mind as inverse reinforcement learning." Current Opinion in Behavioral Sciences 29 (October 2019): 105–10. http://dx.doi.org/10.1016/j.cobeha.2019.04.010.

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25

Leue, Anja, and André Beauducel. "A Meta-Analysis of Reinforcement Sensitivity Theory: On Performance Parameters in Reinforcement Tasks." Personality and Social Psychology Review 12, no. 4 (2008): 353–69. http://dx.doi.org/10.1177/1088868308316891.

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26

Zhu, Guo Liang. "The Analysis of Relationship between Stirrup and Longitudinal Reinforcement with Regression Analysis." Applied Mechanics and Materials 438-439 (October 2013): 342–45. http://dx.doi.org/10.4028/www.scientific.net/amm.438-439.342.

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Regional confined concrete is a method which can strengthen constraint in the most needed position, it can make concrete, longitudinal reinforcement and transverse stirrup to form a more effective binding, and provide a stronger restraint in required regional giving full play the role of constraints. In the result analysis of the regional confined column specimen load test, we found that longitudinal reinforcement and stirrup strains have certain relationship. This article analyses the relationship between the two from the stirrup and longitudinal reinforcements strains in the contingency load

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27

Schulte-Hubbert, F., D. Drummer, and L. Hoffmann. "Model Approach for Displaying Dynamic Filament Displacement during Impregnation of Continuous Fibres Based on the Theory of Similarity – Theory and Modelling." International Polymer Processing 36, no. 4 (2021): 423–34. http://dx.doi.org/10.1515/ipp-2020-4020.

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Abstract The underlying process for the production of textile reinforced thermoplastics is the impregnation of dry textile reinforcements with a thermoplastic matrix. The process parameters such as temperature, time and pressure of the impregnation are mainly determined by the permeability of the reinforcement. This results from a complex interaction of hydrodynamic compaction and relaxation behavior caused by textile and process parameters. The foundation for the description and optimization of impregnation progresses is therefore the determination of the pressure-dependent permeability of fi

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28

Grishin, Nikolay Vladimirovich. "Reinforcement Theory and Study of the Impact of Internet Technologies on Political Participation of Modern Youth." RUDN Journal of Political Science 23, no. 1 (2021): 47–59. http://dx.doi.org/10.22363/2313-1438-2021-23-1-47-59.

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The article examines the methodological possibilities of reinforcement theory in the field of studying the influence of Internet technologies on political behavior. The prospects of the theory of reinforcement are considered in the context of the changing role of Internet technologies in the political process since the beginning of the 2010s and the growing popularity of competing methodological directions, first of all, the theory of mobilization. It is revealed that the rivalry between the theory of reinforcement and the theory of mobilization at the present stage turns into a state of metho

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29

Long, A. C., and C. D. Rudd. "A Simulation of Reinforcement Deformation during the Production of Preforms for Liquid Moulding Processes." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 208, no. 4 (1994): 269–78. http://dx.doi.org/10.1243/pime_proc_1994_208_088_02.

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Composite materials offer an attractive alternative to metals in the automotive and aerospace industries. Of the many possible production methods, liquid moulding processes such as resin transfer moulding (RTM) and structural reaction injection moulding (SRIM) demonstrate potential for high-volume manufacture. It is common to use preformed reinforcements, although this can cause certain problems. Fibre movement during forming can cause adverse effects such as wrinkling and thinning. The high levels of waste generated by subsequent trimming operations are proving unacceptable for medium to high

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30

Pickering, Alan D. "The Conceptual Nervous System and Personality." European Psychologist 2, no. 2 (1997): 139–63. http://dx.doi.org/10.1027/1016-9040.2.2.139.

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In this paper the conceptual nervous system approach to the study of personality is traced back to the ideas of Pavlov. The links between his ideas and two strands of modern European personality theory ( Eysenck's, 1967 , arousal theory of extraversion; Gray's, 1970 , reinforcement sensitivity theory) are emphasized. Recent data concerning reinforcement sensitivity theory have revealed a diversity of relationships between personality trait measures and the behavioral responses to the signals of reinforcement present. In view of these data, a reappraisal of the basics of reinforcement sensitivi

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31

Killeen, Peter R. "Mathematical principles of reinforcement." Behavioral and Brain Sciences 17, no. 1 (1994): 105–35. http://dx.doi.org/10.1017/s0140525x00033628.

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AbstractEffective conditioning requires a correlation between the experimenter's definition of a response and an organism's, but an animal's perception of its behavior differs from ours. These experiments explore various definitions of the response, using the slopes of learning curves to infer which comes closest to the organism's definition. The resulting exponentially weighted moving average provides a model of memory that is used to ground a quantitative theory of reinforcement. The theory assumes that: incentives excite behavior and focus the excitement on responses that are contemporaneou

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32

Morimoto, Jun, and Kenji Doya. "Robust Reinforcement Learning." Neural Computation 17, no. 2 (2005): 335–59. http://dx.doi.org/10.1162/0899766053011528.

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This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both off-line learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H∞ control, we consider a differential game in which a “disturbing” agent tries to make the worst possible disturbance while a “control” agent tries to make the best control inp

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33

Abel, David. "A Theory of State Abstraction for Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9876–77. http://dx.doi.org/10.1609/aaai.v33i01.33019876.

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Reinforcement learning presents a challenging problem: agents must generalize experiences, efficiently explore the world, and learn from feedback that is delayed and often sparse, all while making use of a limited computational budget. Abstraction is essential to all of these endeavors. Through abstraction, agents can form concise models of both their surroundings and behavior, supporting effective decision making in diverse and complex environments. To this end, the goal of my doctoral research is to characterize the role abstraction plays in reinforcement learning, with a focus on state abst

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34

Eftekhari, Zahra, and Shahram Rahimi. "Preana: Game Theory Based Prediction with Reinforcement Learning." Natural Science 06, no. 13 (2014): 1108–21. http://dx.doi.org/10.4236/ns.2014.613099.

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35

Bacon, Alison M., Philip J. Corr, and Liam Paul Satchell. "A reinforcement sensitivity theory explanation of antisocial behaviour." Personality and Individual Differences 123 (March 2018): 87–93. http://dx.doi.org/10.1016/j.paid.2017.11.008.

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36

Shahzadi, Kimiya, and Benjamin R. Walker. "Reinforcement sensitivity theory and relationship satisfaction via mastery." Personality and Individual Differences 139 (March 2019): 46–52. http://dx.doi.org/10.1016/j.paid.2018.11.007.

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37

Farrell, Nicola, Emma Sait, and Benjamin R. Walker. "Reinforcement sensitivity theory and goals in tattooed individuals." Personality and Individual Differences 167 (December 2020): 110234. http://dx.doi.org/10.1016/j.paid.2020.110234.

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38

Walker, Stephen F. "How general is a general theory of reinforcement?" Behavioral and Brain Sciences 17, no. 1 (1994): 154–55. http://dx.doi.org/10.1017/s0140525x00033823.

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39

Kacelnik, Alejandro, and John R. Krebs. "Rate of reinforcement matters in optimal foraging theory." Behavioral and Brain Sciences 8, no. 2 (1985): 340–41. http://dx.doi.org/10.1017/s0140525x00020975.

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40

Subramanian, Jayakumar, and Aditya Mahajan. "Renewal Monte Carlo: Renewal Theory-Based Reinforcement Learning." IEEE Transactions on Automatic Control 65, no. 8 (2020): 3663–70. http://dx.doi.org/10.1109/tac.2019.2953089.

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41

HIRATA, YOSHIAKI. "Theory and practice of filler reinforcement. White carbon." NIPPON GOMU KYOKAISHI 59, no. 8 (1986): 450–62. http://dx.doi.org/10.2324/gomu.59.450.

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42

Roy, Samit, and Anand B. Rajagopalan. "ANALYSIS OF ROCKBOLT REINFORCEMENT USING BEAM-COLUMN THEORY." International Journal for Numerical and Analytical Methods in Geomechanics 21, no. 4 (1997): 241–53. http://dx.doi.org/10.1002/(sici)1096-9853(199704)21:4<241::aid-nag868>3.0.co;2-z.

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43

O'Daly, Matthew, and Edmund Fantino. "Delay reduction theory: Choice, value, and conditioned reinforcement." Behavior Analyst Today 4, no. 2 (2003): 141–50. http://dx.doi.org/10.1037/h0100116.

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44

Corr, Philip J. "The reinforcement sensitivity theory of personality and psychopathology." International Journal of Psychophysiology 69, no. 3 (2008): 151–52. http://dx.doi.org/10.1016/j.ijpsycho.2008.05.377.

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45

Warr, Peter B., Israel Sánchez-Cardona, Stanimira K. Taneva, Maria Vera, Uta K. Bindl, and Eva Cifre. "Reinforcement Sensitivity Theory, approach-affect and avoidance-affect." Cognition and Emotion 35, no. 4 (2021): 619–35. http://dx.doi.org/10.1080/02699931.2020.1855119.

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46

Coleman, S. R. "Adaptiveness, law-of-effect theory, and control-system theory." Behavioral and Brain Sciences 23, no. 2 (2000): 253. http://dx.doi.org/10.1017/s0140525x00262432.

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It is suggested that the control-system theory of Domjan et al. restates in engineering vocabulary the primary thesis of law-of-effect theories: namely, that classical-conditioning arrangements may involve CR-contingent reinforcement. The research cited by Domjan et al. is relevant to the idea that classical conditioning is an adaptive process, but is irrelevant to their control-system theory.

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47

Rummel, Amy, and Richard Feinberg. "RE-EVALUATION OR REINFORCEMENT?: A NEW LOOK AT COGNITIVE EVALUATION THEORY." Social Behavior and Personality: an international journal 18, no. 1 (1990): 65–79. http://dx.doi.org/10.2224/sbp.1990.18.1.65.

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Cognitive Evaluation Theory was developed to explain the detrimental effects of extrinsic rewards on intrinsic motivation, a phenomenon contrary to Reinforcement Theory prediction. However, it was suggested that if a person's intrinsic or extrinsic motivational orientation was taken into account, Reinforcement Theory might be able to explain this phenomenon. A 2 (extrinsic x intrinsic motivational orientation) by 2 (competence feedback x controlling feedback) was employed to examine the effect of motivational orientation on intrinsic motivation. Use of the Jonckheere Test of Order suggested th

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48

Shu, Xiaosong, Tengfei Bao, Yangtao Li, Kang Zhang, and Bangbin Wu. "Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory." Sensors 20, no. 9 (2020): 2648. http://dx.doi.org/10.3390/s20092648.

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Considering the multi-sources, heterogeneity and complexity of dam safety assessment, a dam safety assessment model based on interval-valued intuitionistic fuzzy set and evidence theory is proposed to perform dam safety reliability evaluations. In the proposed model, the dynamic reliability based on the supporting degree is applied to modify the data from homologous information. The interval-valued intuitionistic fuzzy set is used to describing the uncertainty and fuzziness between heterogeneous information. Evidence theory is employed to integrate the data from heterogeneous information. Fina

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49

Mussi, R. G. S., Tetsuichi Motegi, Fumi Tanabe, et al. "Influence of an Inclined Cooling Plate on the Production of A356/CNF and A356/SiC MMC by Compocasting." Materials Science Forum 519-521 (July 2006): 609–14. http://dx.doi.org/10.4028/www.scientific.net/msf.519-521.609.

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The influence of an inclined cooling plate utilized as a modification in the compocasting process of aluminum alloy is studied in this paper. Based on the crystal separation theory, molten A356 is poured on the inclined copper plate in order to produce solidification nuclei inside the fluid metal, which is, then, mechanically stirred while reinforcement is added through its surface. Carbon nano fibers (CNF) and particulate SiC were utilized as reinforcement, in quantities varying from 0.5 to 15vol%. Dispersion of the reinforcements was observed by macro and microstructure analysis. For CNF, ad

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50

Černý, Miroslav, and Jaroslav Pokluda. "First Principles Study of Ideal Composites Reinforced by Coherent Nano-Fibres." Key Engineering Materials 465 (January 2011): 73–76. http://dx.doi.org/10.4028/www.scientific.net/kem.465.73.

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Ab initio calculations of elastic moduli and theoretical tensile strength of composite lamina having continuous nano-fibre reinforcements are performed using pseudopotential approach within density functional theory. Results for molybdenum or tungsten nano-fibres in vanadium or niobium matrices, presented as case studies, reveal that the theoretical strength approaches the value corresponding to the strength of the reinforcement already at about 60-80% atomic concentration of reinforcing fibres in the composite.

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