miRNA in Machine-Learning-Based Diagnostics of Oral Cancer by Xinghang Li, Valentina L. Kouznetsova, Igor F. Tsigelny

“…Traditional cancer diagnostic methods, such as biopsies and histopathological analyses, while effective, are invasive, costly, and require specialized skills. …”
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Image-Based Malware Detection Using Deep CNN Models by hawraa omran musa, Muhanad Tahrir Younis

“…The selection of a 64 × 64 size frame reduces network complexity while speeding up training without sacrificing important information. …”
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The contribution of X to youth environmental movements addressing climate change: Effective impact or distorting noise? by Ángela Alonso-Jurnet, Ainara Larrondo Ureta, Jordi Morales-i-Gras

“…The findings suggest that while these actions attract considerable attention, they may also contribute to a distorting effect associated with the increasingly prevalent paradigm of “climate obstructionism”, by shifting the focus away from substantive climate action towards divisive public discourse. …”
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SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…This study addresses and overcomes this limitation by proposing an innovative approach: instead of sharing weight vectors, we advocate sharing support vectors while safeguarding client data privacy through vector perturbation. …”
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Econometric modeling for proactive risk management of financial failure in Moroccan SMEs: a stepwise logistic regression approach in python by Dina Ait Lahcen, Nour-Eddin Amghar

“…While the limited sample size is a constraint, the results underscore the continued relevance of traditional financial indicators in early warning systems. …”
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Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble by Yanmin Fan

“…Convolutional neural network (CNN) is the first neural network utilized for extracting the spatial characteristics of the data, while Long Short-Term Memory (LSTM) networks—more specifically, an LSTM Stack—are used to comprehend the time-dependent flow of the data based on medical information from patients. …”
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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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Digitalization of human resource management: current trends and challenges for Russian enterprises by Mikhail K. Chernyakov, Irina A. Chernyakova

“…These include employee resistance to change, cybersecurity risks, the need to revise labor standards, and ethical concerns related to the use of AI algorithms. Special attention is given to regional specifics: while large companies actively adopt innovations, small and medium-sized businesses lag due to high technology costs and a shortage of qualified personnel. …”
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Collocations with the Nomination ‘‘Russia’’ in the Corpus of Finno-Ugric Internet Travelogues by Natalya A. Osmak

“…The data obtained through sentiment analysis of contexts and their expert evaluation may be used in the further development of algorithms for automatic text sentiment analysis.…”
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Profiling Astroturfers on Facebook: A Complete Framework for Labeling, Feature Extraction, and Classification by Jonathan Schler, Elisheva Bonchek-Dokow

“…We then applied and compared several algorithms in the classification stage, and achieved improved results, with an F₁ score of 77% and accuracy of 92%.…”
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Liftable Point-Line Configurations: Defining Equations and Irreducibility of Associated Matroid and Circuit Varieties by Oliver Clarke, Giacomo Masiero, Fatemeh Mohammadi

“…As corollaries, we provide a geometric representation for the defining equations of two specific examples: the quadrilateral set and the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> grid. While the polynomials for the latter were previously computed using specialized algorithms tailored for this configuration, the geometric interpretation of these generators was missing. …”
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Trajectory Aware Deep Reinforcement Learning Navigation Using Multichannel Cost Maps by Tareq A. Fahmy, Omar M. Shehata, Shady A. Maged

“…Deep reinforcement learning (DRL)-based navigation in an environment with dynamic obstacles is a challenging task due to the partially observable nature of the problem. While DRL algorithms are built around the Markov property (assumption that all the necessary information for making a decision is contained in a single observation of the current state) for structuring the learning process; the partially observable Markov property in the DRL navigation problem is significantly amplified when dealing with dynamic obstacles. …”
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Credit Rating Model Based on Improved TabNet by Shijie Wang, Xueyong Zhang

“…Under the rapid evolution of financial technology, traditional credit risk management paradigms relying on expert experience and singular algorithmic architectures have proven inadequate in addressing complex decision-making demands arising from dynamically correlated multidimensional risk factors and heterogeneous data fusion. …”
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Equivariant learning leveraging geometric invariances in 3D molecular conformers for accurate prediction of quantum chemical properties by Jianhua Sun, Ye Cao, Huijing Hu, Baoqiao Qi

“…The foundation of the 3DMSE approach lies in an equivariant learning module that adeptly captures the subtle geometric intricacies of molecular conformers while ensuring invariance to rotations and permutations. …”
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Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Algorithmic recommendation mechanisms of social media platforms, viral diffusion of user-generated content (UGC), and real-time public opinion pressures are fundamentally deconstructing the traditional corporate crisis response paradigm that used to rely on one-way statements and delayed reactions. …”
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Usage of short video applications (SVAs): Exploring Italian users’ social representations of short video creators and trust in informational and educational SVA content providers by Willow-G. Curry, Elisa Colì

“…Informational and sports & entertainment are the primary types of content viewed across all age groups. While younger users place greater emphasis on professional skills and authoritative content, older users tend to prioritize engagement and presentation skills. …”
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Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation by A. Srinivaas, N. R. Sakthivel, Binoy B. Nair

“…The former uses physical models of engine components to diagnose defects, while the latter employs statistical analysis of sensor data to identify patterns indicating faults. …”
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Research on the robustness of the open-world test-time training model by Shu Pi, Xin Wang, Jiatian Pi

“…However, deploying TTT/TTA in open-world environments is challenging due to the difficulty in distinguishing between strong out-of-distribution (OOD) samples and regular weak OOD samples. While emerging Open-World TTT (OWTTT) approaches address this challenge, they introduce a new vulnerability: test-time poisoning attacks. …”
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Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation by Marco Negozio, Lorenzo Donati, Adrian H. A. Lutey

“…PCG formation was predicted with 5.8% false negatives and 3.9% false positives compared to 10.1% and 18.1%, respectively, with existing analytical models, while grain size was predicted with a mean squared error (MSE) of 9.77 μm2 compared to 48.3 μm2. …”
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Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices by Alexis Courbet, Patrick Amar, François Fages, Eric Renard, Franck Molina

“…We show that proof‐of‐concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. …”
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