Synaptic learning rules and sparse coding in a model sensory system. by Luca A Finelli, Seth Haney, Maxim Bazhenov, Mark Stopfer, Terrence J Sejnowski

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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…The study demonstrated the superiority of ensemble learning techniques in enhancing detection accuracy and robustness. …”
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Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction. by Akash Bahai, Chee Keong Kwoh, Yuguang Mu, Yinghui Li

“…The 3D structure of RNA critically influences its functionality, and understanding this structure is vital for deciphering RNA biology. …”
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Exhaustive search for novel multicomponent alloys with brute force and machine learning by Viktoriia Zinkovich, Vadim Sotskov, Alexander Shapeev, Evgeny Podryabinkin

“…The candidate structures are evaluated using the low-rank potential (LRP), trained to reproduce energies of structures equilibrated with density functional theory (DFT). Thanks to extreme computational effectiveness of the LRP, it is feasible to evaluate hundreds of thousands of structures per second, per CPU core. …”
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A hybrid framework of generative deep learning for antiviral peptide discovery by Huynh Anh Duy, Tarapong Srisongkram

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EFL teacher perceptions of student beliefs attitudes and motivation in online learning by Mohamed Mekheimer

“…Drawing upon theories of perception, functionality, and self-efficacy, the study explored the influence of teachers' internal factors on successful e-learning implementation. …”
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Explicit intent enhanced contrastive learning with denoising networks for sequential recommendation by Jinfang Sheng, Xuhao Zhang, Bin Wang

“…However, most contrastive learning models address the critical issue of data sparsity using data augmentation, which amplifies the noise present in the original sequences, resulting in learning biased user intent distribution functions, and deteriorating the modeling effectiveness of true intent. …”
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Kaartdijin Bidi (Learning Journey): Place-based Cultural Regeneration at University by Sandra Wooltorton, Lauren Stephenson, Kathie Ardzejewska, Len Collard

“…Imagine being in a university that functions in a place-based culturally regenerative way. …”
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High-Performance stacking ensemble learning for thermoelectric figure-of-merit prediction by Yuelin Wang, Chengquan Zhong, Jingzi Zhang, Honghao Yao, Junjie Chen, Xi Lin

“…Here we present a machine learning (ML) approach, the stacking model, that significantly improves zT prediction accuracy for doped thermoelectric. …”
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Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility by Mehmet Bilge Han Taş, Kemal Özkan, İnci Sarıçiçek, Ahmet Yazici

“…To solve this problem, reinforcement learning was used and tested on the simulation environment SUMO. …”
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Machine Learning‐Enhanced Nanoparticle Design for Precision Cancer Drug Delivery by Qingquan Wang, Yujian Liu, Chenchen Li, Bin Xu, Shidang Xu, Bin Liu

“…Therefore, innovative approaches are needed to optimize nanoparticle (NP) design and functionality, enhancing their delivery efficiency and therapeutic outcomes. …”
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Verifiable secure aggregation scheme for privacy protection in federated learning networks by Wujun Yao, Tanping Zhou, Yiliang Han, Xiaolin Wang

“…To verify the integrity of server aggregation computations while protecting the privacy of clients, this paper introduces a privacy-preserving verifiable secure aggregation scheme for federated learning networks. Initially, we construct a functional reuse private key ring generation algorithm, enabling clients to encrypt and protect their private gradients using the private key ring. …”
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Multimodal learning for enhanced SPECT/CT imaging in sports injury diagnosis by Zhengzheng Jiang, YaWen Shen

“…IntroductionSingle-photon emission computed tomography/computed tomography (SPECT/CT) imaging plays a critical role in sports injury diagnosis by offering both anatomical and functional insights. However, traditional SPECT/CT techniques often suffer from poor image quality, low spatial resolution, and limited capacity for integrating multiple data sources, which can hinder accurate diagnosis and intervention.MethodsTo address these limitations, this study proposes a novel multimodal learning framework that enhances SPECT/CT imaging through biomechanical data integration and deep learning. …”
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The Role of Machine Translation in English Language Learning: A Systematic Review by Judelyn Alones

“… This systematic literature review (SLR) examines the functions, limitations, and effectiveness of machine translation (MT) tools in English language learning. …”
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Deep learning tools predict variants in disordered regions with lower sensitivity by Federica Luppino, Swantje Lenz, Chi Fung Willis Chow, Agnes Toth-Petroczy

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Electroencephalographic power spectrum patterns related to the intelligence of children with learning disorders by Benito Javier Martínez-Briones, Thalía Fernández, Juan Silva-Pereyra

“…Children with learning disorders (LD) perform below average in tests of academic abilities and intelligence. …”
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Learning through AI-clones: Enhancing self-perception and presentation performance by Qingxiao Zheng, Zhuoer Chen, Yun Huang

“…The results, viewed through the lens of social comparison theory, showed that AI clones functioned as positive “role models” for encouraging positive social comparisons. …”
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An investigation of far and near transfer in a gamified visual learning paradigm. by Stefanie Duyck, Hans Op de Beeck

“…After training, visual perceptual learning improvements are mostly constrained to the trained stimulus feature and retinal location. …”
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Application of Machine Learning for Adaptive Trajectory Control of UAVs Under Uncertainty by Alexander S. Ermilov, Olga A. Saltykova

“…The article explores the potential of applying machine learning (ML) for adaptive trajectory control of unmanned aerial vehicles (UAVs) under uncertainty. …”
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The Effectiveness of Hybrid Learning in English Pronunciation Pedagogy in the Nigerian ESL Context by Jacinta Benjamin-Ohwodede, Adekunle Mamudu, Simeon Nyemike Awunor

“…This paper is a study on the effectiveness of hybrid learning; a blend of traditional and technology-based training, vis-à-vis the second language (L2) learner of English pronunciation. …”
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