SOCIAL COMPLEXITY AND LEARNING FORAGING TASKS IN BEES by AMAYA-MÁRQUEZ MARISOL, WELLS HARRINGTON

“…Experiments utilized blue vs. white flower patches to standardize rewards in each experimental situation. Although honey bees learned faster than blue orchard bees when given a molarity difference reward problem, there was no significant difference in learning rate when presented a volume difference reward problem. …”
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Learning Quantum Processes with Quantum Statistical Queries by Chirag Wadhwa, Mina Doosti

“…For the latter, we present average-case query complexity lower bounds for learning classes of unitaries. …”
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Modeling Active Learning in a Robot Collective by Mehmet Dinçer Erbaş

“…Afterwards, we design an active learning procedure in which the learner robot can manifest what it understand from the presented information. …”
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Initiating language engagement with multimodal learning tasks by Aránzazu García-Pinar

“…In fact, engagement has become one of the most fashionable research topics in educational psychology. The present study explores the engagement among five engineering undergraduates for one semester while working on L2 tasks, which entailed the multimodal analysis of 8 technology-related TED Talks and was purposefully designed to initiate them into multimodal literacy and foster their language learning. …”
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Additional-Language Learning, Interdisciplinary Instruction, and Technology by Clayton Smith

“… In this issue, we focus on additional-language learning, interdisciplinary instruction, and  technology. …”
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Adaptive learning on mobile network traffic data by Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, Deyu Tang

“…Specifically, a method based on the fuzzy competence model is devised to detect concept drift, and a dynamic learning method is presented to update the classification model, so as to adapt to an ever-changing environment at an appropriate time. …”
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INFORMATIONAL SUPPORT OF THE USE OF STANDARDS IN E-LEARNING by Oleg I. Selivantsev, Maxim V. Sutyagin

“…The article presents tools for information support of the application of standards in the field of e-learning and automate the process of assessing the quality of electronic educational resources. …”
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Selecting learning partners: memory for participation and competence by Oktay Ülker, Daniel Bodemer

“…An experimental study (N = 85) examined how type (participation vs. competence) and level (high vs. medium vs. low) of presented group awareness information influence learning partner selection in two phases (when information is present and when it is remembered). …”
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Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…The present work explores the application of Automated Machine Learning techniques, particularly on the optimization of Artificial Neural Networks through hyperparameter tuning. …”
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Deep learning for quantitative dynamic fragmentation analysis by Erwin Cazares, Brian E. Schuster

“…Here we trained binary-, three-, and five-class models using supervised learning on experimentally measured dynamic fracture experiments on various opaque structural ceramic materials that were adhered on transparent polymer (polycarbonate or acrylic) backing materials. …”
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EXPLORING SOME ASPECTS OF LANGUAGE LEARNING WEBSITES by Tatiana M. Gulaya, Svetlana A. Romanova

“…This paper presents results of the surveyperformed in MESI, in academic groupsmajoring in “World Economy”. …”
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Robotic waste sorting using deep learning by Goorun Yurisha, Marais Stephen, Nicolls Fred

“…The ongoing waste crisis has highlighted the need to address the problem of waste collection and sorting. This paper presents an automated waste sorting system with Deep Learning using a stereoscopic camera and a robotic manipulator. …”
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ALGORITHM FOR PHONOGRAM COMPARISON IN E-LEARNING SYSTEMS by V. V. Kiselev, A. G. Davydau, A. A. Tkachenia

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Tapping into the vocal learning and rhythmic synchronization hypothesis by Constantina Theofanopoulou

“…Abstract In this article, I present three main points that could benefit the “vocal learning and rhythmic synchronization hypothesis”, encompassing neurogenetic mechanisms of gene expression transmission and single motor neuron function, classification of different behavioral motor phenotypes (e.g., spontaneous vs. voluntary), and other evolutionary considerations (i.e., the involvement of reward mechanisms).…”
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Learning by precedents based on the analysis of the features properties by V. V. Krasnoproshin, V. G. Rodchanka

“…The issue of learning by precedents is studied. A method of learning based on the analysis of the properties of feature combinations and building feature subspaces where classes do not intersect is proposed. …”
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Exploring teachers’ beliefs about learning principles by Erik Meij, Erik Meij, Anneke Smits, Martijn Meeter

“…In an explicit classroom statement task, participants were presented with a statement about actions in the classroom that either were or were not in line with principles of learning and asked how firmly they believed it was true (or false) and on what basis. …”
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Advanced deep learning for masked individual surveillance by Mohamed Elhoseny, Ahmed Hassan, Marwa H. Shehata, Mohammed Kayed

“…To address this critical issue, we present a novel enhanced surveillance system that leverages deep learning techniques to tackle two crucial tasks simultaneously: anomaly detection of masked individuals' activities and masked face completion for accurate recognition. …”
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Soundwalking with AI: collaborative creativity as embodied learning by Martim S. Galvão, Marcel Zaes Sagesser

“…This paper presents an innovative approach to designing soundwalks in educational group settings by harnessing AI, particularly ChatGPT, to inspire collaborative auditory imagination and soundscape creation. …”
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STUDY REGARDING MANAGEMENT OF LEARNING AND TEACHING PROCESS by Silvia PUIU

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Detection of microfibres in wastewater sludge with deep learning by Félix Martí-Pérez, Ana Domínguez-Rodríquez, Carlos Monserrat, Cèsar Ferri, María-José Luján-Facundo, Eva Ferrer-Polonio, Amparo Bes-Piá, José-Antonio Mendoza-Roca

“…Traditional detection methods are labour-intensive and lack the scalability necessary for effective monitoring. This study presents a novel approach utilising advanced deep learning techniques to enhance the detection of MFi in sewage sludge samples using two different filtration support (fibreglass and cellulose acetate). …”
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