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• W2156815972 abstract "This piece of research addressed a systematic approach for evaluation of an interdisciplinary educational challenging phenomenon observed in children's classrooms. Introduced phenomenon is associated with effects of physical educational environment on learning performance in classrooms. Specifically, it describes serious problematic issue of overcrowded effect on classrooms' learning / teaching performance. It has been comparatively presented here versus a challenging phenomenal of human's selectivity auditory scene analysis. This deals with an auditory perception phenomenon, namely known as Cocktail Party Problem (CPP), which originated by process carried out by auditory system of a human (child) while listening. Commonly, this process experienced as following one speaker (teacher' speech) in presence of another overcrowded classroom noisy effect. Herein, adopted approach presented comparative study which motivated by insight into auditory perception, which is derived from original Marr's vision theory. In nature, observed OCR as well as pattern recognition processes, both have been carried out under non ideal environmental learning condition (under effect of noisy data). Furthermore, introduced proposal for active audition modeling is motivated by analogous active vision processes, such as that observed during Optical Character Recognition (OCR). The effects of physical learning environment in classrooms includes three distinct effective factors namely: noisy level in classes, overcrowded classroom space, and housing and neighborhood quality. Specifically, this work explores pupils' ability to listen to, and follow, one speaker in presence of others. More precisely, it considers investigational answer for a challenging question: How students could focus on teachers' interactive speaking in noisy crowd environment? When discussing auditory system it is important to understand difference between physical mechanism of ear and central auditory nervous system in brain responsible for processing auditory information (1). Commonly, this process experienced as following one speaker in presence of another. Such common experience, we may take it for granted as called: the cocktail party problem CPP. It can be trivial experienced process for a normal human (student) listener. From a neurological P.O.V., sounds all enter ear as one cacophonous roar, but brain processes all information and tunes into one sound, such as a person's voice, and filters out rest (2). Interestingly, referring to brain functions and anatomical structure, sound and light are processed by different receptors and neural pathways in brain. However, by considering current knowledge of how auditory and visual stimuli sensations are responding to sound and light respectively. They are represented in nervous system in similar complexity and that undergo with similar initial processing by nervous system (3). Furthermore, by referring to findings announced after some experimental work, results published therein at (3) have implicitly declared that auditory and visual short term memory employ similar mechanisms. Consequently, modeling of Artificial Neural Networks (ANNs) has been adopted for realistic simulation for students' selective attention in overcrowded classrooms. Therefore, an ANN unsupervised model has been suggested herein, to measure performance of selective attention and recognition for visual signal specifically optical character recognition (OCR) subjected to various contaminating noisy levels (Signal to noise ratios) (4). Finally, obtained simulation results declared effect of Neural Network's parameters' relation between extrinsic {various noisy levels (corresponding learning rate values)} and intrinsic {individual students' differences (corresponding to various gain factor values)} factors on recognition and selective attention performances. Additionally, presented obtained findings proved to be in well agreement with recently published results considering dealing with noisy environmental learning (5).The Rest of this paper organized as" @default.
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• W2156815972 date "2014-01-01" @default.
• W2156815972 modified "2023-09-27" @default.
• W2156815972 title "Comparative Analogy of Overcrowded Effects in Classrooms versus Solving 'Cocktail Party Problem' (Neural Networks Approach)" @default.
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