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Home / Journals / Mathematics and Computer Science / Advanced Deep Learning Methods for Audio and Speech processing
Advanced Deep Learning Methods for Audio and Speech processing
Lead Guest Editor:
Peyman Goli
Department of Electrical and Computer Engineering, Khavaran Institute of Higher Education, Mashhad, Iran
Guest Editors
Stuart Rubin
Department of Applied Science and Technology / Intelligent Sensing Branch, Space and Naval Warfare Systems Center Pacific
San Diego, CA, USA
Nanlin Jin
Department of Computer and Information Science, Northumbria University
Newcastle Upon Tyne, Tyne and Wear, UK
Ping Guo
Department of Computer Science, University of Illinois at Springfield
Springfield, USA
Mohammad-Reza Karami
Department of Electrical and Computer Engineering, Babol Noshivani University of Technology
Babol, Iran
Professor Pollyana Notargiacomo
School of Computing and Informatics, Mackenzie Presbyterian University
São Paulo, Brazil
Sangho Park
Department of Computer, Electronics and Graphics Technology, Central Connecticut State University
New Britain, USA
Introduction
This issue is about geometry concept applied in solving mathematics problems, with regarding geometrical or visual abilities. That is a mental imagery by means of cognitive strategies. The foundation is the constitutive genesis of geometric concepts, a frame to the advances responses in cognition and support the mathematical intuition, and the foundational analysis of the constitutive process as an epistemological issue. The context of representation is for effective learning, tailored to the uses of the cognitive recognized by the students. While the visuals as recipes for new cases, the compartmentalization of mathematics, separable from the formal one. Overall, there are beliefs that developed in the independency between the conceptual structures and the representation. The relation is a connections drawn in interrelated knowledge, a richness of interconnection and promoting numerous viewpoints. In this issue, the visual representation transmisses knowledge encoded from personalized knowledge. The representation derivable from exploration in the mathematics area and outline the theoretical approach to solve the problems using manipulation and construction the visual. As a comparison, single representations, e.g., logic and a schema is the facets of abstract concepts, while the visual ability regarded as a flexibility of thinking and having a diversified repertoire about a conceptual manner. The use of visual representation is in different levels of thinking. For example, to see two equations like arrangable visuals to another one. That leads to take issues related to the visual explanations as a mental model in learning. The other representations considered for visual abilities, where the complexity requires re-represented from multiple perspectives. The mental imagery is the premise of the performance of visual problems viewpoint. The premise is the use of cognitive rather than an imagistic strategy to accomplish the mathematics problems. The problem is: Has the mental imagery primed effect on binocular rivalry in aphantasics when performing the visual problems? I believe that a reference to quasi-perceptual conscious experience is essential in order to distinguish mental imagery from other mental phenomena. I want to know the correlate of quasi-perceptual experiences and the mental imagery though the question about the visual representations of unconscious mental imagery. That is to define the fact that depends on the context and attempting to compact the idea of geometric concept into the purposes of algebra.

Aims and Scope:

  1. Visual abilities
  2. Visual representations
  3. Visual problems
  4. Visual thinking
  5. Mental imagery
  6. Perceptual image
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