scholarly journals The Rotating Snake Illusion is a straightforward consequence of non-linearity in arrays of standard motion detectors

2020 ◽  
Author(s):  
Michael Bach ◽  
Lea Atala-Gérard

AbstractThe Rotating Snakes illusion is a motion illusion based on repeating, asymmetric luminance patterns. Recently, we found certain grey-value conditions where a weak, illusory motion occurs in the opposite direction. Of the four models for explaining the illusion, one (Backus and Oruç, 2005) also explains the unexpected perceived opposite direction. We here present a simple new model, without free parameters, based on an array of standard correlation-type motion detectors with a subsequent non-linearity (e.g., saturation) before summing the detector outputs. The model predicts (1) the pattern-appearance motion illusion for steady fixation, (2) an illusion under the real-world situation of saccades across or near the pattern (pattern shift), (3) a relative maximum of illusory motion for the same grey values where it is found psychophysically, and (4) the inverse illusion for certain luminance values. We submit that the model’s sparseness of assumptions justifies adding a fifth model to explain this illusion.

i-Perception ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 204166952095802
Author(s):  
Michael Bach ◽  
Lea Atala-Gérard

The Rotating Snakes illusion is a motion illusion based on repeating, asymmetric luminance patterns. Recently, we found certain gray-value conditions where a weak illusory motion occurs in the opposite direction. Of the four models for explaining the illusion, one also explains the unexpected perceived opposite direction.We here present a simple new model, without free parameters, based on an array of standard correlation-type motion detectors with a subsequent nonlinearity (e.g., saturation) before summing the detector outputs. The model predicts (a) the pattern-appearance motion illusion for steady fixation, (b) an illusion under the real-world situation of saccades across or near the pattern (pattern shift), (c) a relative maximum of illusory motion for the same gray values where it is found psychophysically, and (d) the opposite illusion for certain luminance values. We submit that the new model’s sparseness of assumptions justifies adding a fifth model to explain this illusion.


Author(s):  
Xiaoyu Tang ◽  
Yulin Gao ◽  
Weiping Yang ◽  
Ming Zhang ◽  
Jinglong Wu

Bimodal audiovisual (AV) stimuli are detected or discriminated faster and more accurately than either visual or auditory unimodal stimuli. This effect is called audiovisual integration. Recently, researchers have been increasingly focused on the audiovisual integration of natural, auditory, and visual stimuli in real-world situations. There are some differences between audiovisual integration of naturalistic stimuli and non-naturalistic stimuli, such as the time of occurrence of audiovisual integration, and the neural mechanism. Factors affecting audiovisual integration in real-world situations are summarized here, with particular focus on temporal asynchrony and semantic matching. Stimuli of audiovisual integration in the real-world situation should be controlled strictly, especially emotional factors, familiarity factors, semantic matching, and the match of the naturalistic stimuli and non-naturalistic stimuli. In the future, researchers should study the influence of attention on audiovisual integration and the mechanism of audiovisual integration with naturalistic stimuli in the real-world situation.


Author(s):  
Janina Krawitz ◽  
Yu-Ping Chang ◽  
Kai-Lin Yang ◽  
Stanislaw Schukajlow

AbstractTo solve mathematical modelling problems, students must translate real-world situations, which are typically presented in text form, into mathematical models. To complete the translation process, the problem-solver must first understand the real-world situation. Therefore, reading comprehension can be considered an essential part of solving modelling problems, and fostering reading comprehension might lead to better modelling competence. Further, ease of comprehension and involvement have been found to increase interest in the learning material, and thus, improving reading comprehension might also increase interest in modelling. The aims of this study were to (a) determine whether providing students with reading comprehension prompts would improve the modelling sub-competencies needed to construct a model of the real-world situation and their interest in modelling and (b) analyze the hypothesized effects in two different educational environments (Germany and Taiwan). We conducted an experimental study of 495 ninth graders (201 German and 294 Taiwanese students). The results unexpectedly revealed that providing reading comprehension prompts did not affect the construction of a real-world model. Further, providing reading comprehension prompts improved students’ situational interest. The effects of providing reading comprehension prompts on the construction of a real-world model were similar in Germany and Taiwan. Students’ interest in modelling improved more in Germany. An in-depth quantitative analysis of students’ responses to reading prompts, their solutions, and their interest in the experimental group confirmed the positive relation between reading comprehension and modelling and indicated that the reading comprehension prompts were not sufficient for improving reading comprehension. Implications for future research are discussed.


Author(s):  
Andrew Brooks

Education is moving out of the classroom and into the real world, driven by both emerging Information and Communication Technologies (ICT) and new economic models. The boom of the web and social networking has revolutionised global communication and collaboration. A DIY culture and industries are emerging because of this. Mobile devices connecting to the digital superhighways are merging the real and digital worlds. This, coupled with the falling cost of the hardware as well as the free software movement may soon place a new model of education into the grasp of almost everyone. A model where education is no longer the process of being fed information, but rather a process of enquiry, exploration, discovery, expression and re-interpretation of the world around us on our own terms. The potential for learning from and with each other at this moment in time is unprecedented.


2013 ◽  
Vol 705 ◽  
pp. 499-503 ◽  
Author(s):  
Fei Yang ◽  
Liang Di Zhang ◽  
Jing Fang Shen

Malthusian population growth model is not applicable to the real world situation in most cases, since the simplifying assumptions are too ideal. In this article, we will generalize the classic population growth models by Stochastic differential equations, and get the extended models appealed to the real world better as well. When modeling the environmental perturbation by white noise process, we get an advanced model .


2001 ◽  
Vol 24 (3) ◽  
pp. 409-410 ◽  
Author(s):  
Francisco J. Gil-White

I argue that (1) the accusation that psychological methods are too diverse conflates “reliability” with “validity”; (2) one must not choose methods by the results they produce – what matters is whether a method acceptably models the real-world situation one is trying to understand; (3) one must also distinguish methodological failings from differences that arise from the pursuit of different theoretical questions.


1975 ◽  
Vol 7 (1) ◽  
pp. 239-245
Author(s):  
James Nelson ◽  
Gerald Doeksen

Teaching rural development must reflect the breadth and complexity of the real world situation. Time limitations may restrict the teacher primarily to presentation and discussion of the field's many facets, leaving little time to consider how these diverse elements interact. Even if careful course planning and strict adherence to a course outlined provide classroom time for such consideration, only advanced graduate students are likely to have sufficient expertise to readily understand the relationships, real or hypothesized, resulting from these interactions.Alternatives in the classroom include giving these relationships only cursory, descriptive treatment, or digging into them with analytical fervor, thereby causing many students a great deal of chagrin. A third alternative is demonstrating interactive aspects of rural development with a game. Such a game is discussed in this paper.


2021 ◽  
Vol 17 (1) ◽  
pp. 109-121
Author(s):  
Hyosup Song

Abstract In this study, I explore a new model of narrative that contains interactions between three levels of story – narrative story, cognitive story, and social story. With this new model, narrative is no longer a static form but rather a whole signifying process among levels. I term this new model narrative-semiosis. The narrative-semiosis model in this study is closely related to the six elements of Jakobson’s communication model. In my new model, cognitive story exists in the minds of both the addresser and addressee, and social story exists in the context where human beings think and perform in the real world. Cognitive story is inferred from the message that is in a narrative story. In this paper, I describe the semiotic interactions among the three levels of stories, not unidirectional but bidirectional, in my narrative-semiosis model. I also validate my model by applying it to a traditional Korean shaman epic Danggumagi and a painting text, Sun and Moon, describing their semiotic narrative signification.


2021 ◽  
pp. 19-24
Author(s):  
Stuart Russell

AbstractA long tradition in philosophy and economics equates intelligence with the ability to act rationally—that is, to choose actions that can be expected to achieve one’s objectives. This framework is so pervasive within AI that it would be reasonable to call it the standard model. A great deal of progress on reasoning, planning, and decision-making, as well as perception and learning, has occurred within the standard model. Unfortunately, the standard model is unworkable as a foundation for further progress because it is seldom possible to specify objectives completely and correctly in the real world. The chapter proposes a new model for AI development in which the machine’s uncertainty about the true objective leads to qualitatively new modes of behavior that are more robust, controllable, and deferential to humans.


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