SapotaNet: Paving the Way for Efficient Deep Learning with Lightweight Network Architecture by Anita Bhatt, Maulin Joshi

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Transforming learning or creating dependency? Teachers’ perspectives and barriers to AI integration in education by Hardiyanti Pratiwi, Agus Riwanda, Hasruddin Hasruddin, Sujarwo Sujarwo, Amir Syamsudin

“…The emergence of artificial intelligence [AI] in education offers significant potential to enhance personalized learning, feedback, and instructional strategies. However, its effectiveness depends on educators' practices and students' capabilities, especially in rural contexts where the digital divide presents challenges. …”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. …”
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The effect of reward and voluntary choice on the motor learning of serial reaction time task by Yanghui Quan, Jiayue Wang, Yandong Wang, Guanlan Kang, Guanlan Kang

“…The purpose of the present study is to investigate the effects of reward and voluntary choice on motor skill learning in a serial reaction time task (SRTT).MethodsParticipants completed six parts of SRTT, including pre-test, training phase, immediate post-test, a random session, delayed post-test, and retention test on the following day. …”
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Evaluating performance and generalizability of Learning from Demonstration for the harvesting of apples & pears by Robert van de Ven, Ard T. Nieuwenhuizen, Eldert J. van Henten, Gert Kootstra

“…Automating agricultural tasks is challenging because of the large amount of variation in the environment and variation in tasks. Learning from Demonstration (LfD) is a promising method that allows robots to adjust to new environments and tasks easily through an easy training procedure performed by the end-user. …”
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Fine-Pruning: A biologically inspired algorithm for personalization of machine learning models by Joseph Bingham, Saman Zonouz, Dvir Aran

“…This work demonstrates that by returning to biomimicry, specifically mimicking how the brain learns through pruning, we can solve various classical machine learning problems while utilizing orders of magnitude fewer computational resources and no labels. …”
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Predicting Sugar Yield From Sugarcane Using Machine Learning for Jaggery Production by Kathirvel Narayanasamy, Ilayaraja Venkatachalam

“…This study presents a machine learning approach for rapid and accurate prediction of sugar yield per metric ton of sugarcane, using multiple physicochemical and environmental parameters. …”
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Data-driven network intrusion detection using optimized machine learning algorithms by Dauda Adeite Adenusi, Oladosu Oyebisi Oladimeji, Theopilus Adekunle Oyekola, Korede Solomon Olagunju

“…Network intrusion detection systems (NIDS) play a crucial role in maintaining cybersecurity by identifying malicious network activities. This study presents a comprehensive evaluation of machine learning approaches for network intrusion detection, comparing the performance of Decision Trees (DT), Random Forest (RF), K-Nearest Neighbors (K-NN), Gradient Boosting (GB), and Logistic Regression (LR) algorithms. …”
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Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles. by Arne F Meyer, Jan-Philipp Diepenbrock, Max F K Happel, Frank W Ohl, Jörn Anemüller

“…Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. …”
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Leveraging Machine Learning for Enhanced Bug Triaging in Open-Source Software Projects by Nitanta Adhikari, Rabindra Bista, Joao Carlos Ferreira

“…This study explores the application of machine learning to automate and improve bug triaging efficiency and accuracy. …”
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Clinical concept annotation with contextual word embedding in active transfer learning environment by Asim Abbas, Mark Lee, Niloofer Shanavas, Venelin Kovatchev

“…Objective The study aims to present an active learning approach that automatically extracts clinical concepts from unstructured data and classifies them into explicit categories such as Problem, Treatment, and Test while preserving high precision and recall and demonstrating the approach through experiments using i2b2 public datasets. …”
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Exploring Regional Determinants of Tourism Success in the Eurozone: An Unsupervised Machine Learning Approach by Charalampos Agiropoulos, James Ming Chen, George Galanos, Thomas Poufinas

“…This paper presents an initial analysis of the factors influencing tourism success at the NUTS 2 regional level across the Eurozone from 2010 to 2019. …”
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Improving Railway Track Detection With a Mixed-Modality Deep Learning Approach by Wichian Ooppakaew, Jakkrit Onshaunjit, Saifun Khrueakhrai, Jakkree Srinonchat

“…Artificial intelligence’s capacity to swiftly and precisely analyze data enables systems to react to possible dangers promptly. The present study introduces a sophisticated railway track identification system that utilizes semantic segmentation methods and deep learning models to effectively distinguish between items and persons in close proximity to railway zones. …”
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Explainable Recommender Systems Through Reinforcement Learning and Knowledge Distillation on Knowledge Graphs by Alexandra Vultureanu-Albişi, Ionuţ Murareţu, Costin Bădică

“…This study presents a novel framework, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>X</mi><msup><mi>R</mi><mn>2</mn></msup><msup><mi>K</mi><mn>2</mn></msup><mi>G</mi></mrow></semantics></math></inline-formula> (X for explainability, first R for recommender systems, the second R for reinforcement learning, first K for knowledge graph, the second K stands for knowledge distillation, and G for graph-based techniques), with the goal of developing a next-generation recommender system with a focus on careers empowerment. …”
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Understanding and Expressing The Factors Causing Difficulties of Children In Learning, Especially In The Field Of Reading by Wita Seftiani, Zakariyah, Indo Dini Aulia

“…The discussion that we present aims to discuss the factors that cause learning difficulties, especially in the field of reading in SD 122/X Sungai Beras students, Mendahara Ulu District, East Tanjung Jabung Regency. …”
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Motor imagery EEG signal classification using novel deep learning algorithm by Sathish Mathiyazhagan, M. S. Geetha Devasena

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Laor Initialization: A New Weight Initialization Method for the Backpropagation of Deep Learning by Laor Boongasame, Jirapond Muangprathub, Karanrat Thammarak

“…This paper presents Laor Initialization, an innovative weight initialization technique for deep neural networks that utilizes forward-pass error feedback in conjunction with k-means clustering to optimize the initial weights. …”
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Lung Nodule Detection For CT-Guided Biopsy Images Using Deep Learning by B. Prashanthi, S.P. Angelin Claret

“…The methodology encompasses a modern deep-learning approach applied to a private dataset obtained from the Barnard Institute of Radiology at Madras Medical College, Chennai, which has been granted ethical approval.  …”
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Curricula and learning objectives in nurse practitioner programmes: a scoping review protocol by Birgitta Ljungbeck, Katarina Sjogren Forss, Hafrún Finnbogadóttir

“…The findings will be presented through a numerical summary of the included articles, followed by a thematic analysis.Ethics and dissemination Research ethics approval is not required for a scoping review. …”
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Learning by heart: cultural patterns in the faunal processing sequence during the middle pleistocene. by Ruth Blasco, Jordi Rosell, Manuel Domínguez-Rodrigo, Sergi Lozano, Ignasi Pastó, David Riba, Manuel Vaquero, Josep Fernández Peris, Juan Luis Arsuaga, José María Bermúdez de Castro, Eudald Carbonell

“…Social learning, as an information acquisition process, enables intergenerational transmission and the stabilisation of cultural forms, generating and sustaining behavioural traditions within human groups. …”
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