A hierarchical reinforcement learning approach for energy‐aware service function chain dynamic deployment in IoT by Shuyi Wang, Haotong Cao, Longxiang Yang

“…This method can more effectively lower energy consumption and carbon emissions when compared to other hierarchical algorithms based on conventional deep neural networks and non‐hierarchical algorithms. …”
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Technological Transformations in the Audiovisual Media Industry: A Case Study of Netflix by Nadir LAMARI & Ahmed Mahdi ZOUAOUI

“…The article also considers the social and cultural ramifications of these technological shifts, exploring how Netflix influences viewer preferences and public culture while navigating ethical considerations inherent in algorithmic recommendations. …”
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Quantum-Resistant Blockchain Protocols for Secure Transactions by Vishal Puneyani, K. Vivekananda Bhat

“…While Kyber is a robust key exchange mechanism, it is not suitable for signing transactions. …”
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Afropolitan Influence: Gender, Comedy, and Social Media in Global Africa by Robin K. Crigler

“…In addition, I argue for greater critical attention to what I call “algorithmic mystery”—the influence of opaque social media algorithms in promoting, maintaining, and severing digital connections.…”
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Design of Telerobotic Drilling Control System with Haptic Feedback by Faraz Shah, Ilia G. Polushin

“…The paper deals with the design of control algorithms for virtual reality based telerobotic system with haptic feedback that allows for the remote control of the vertical drilling operation. …”
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CSTFNet: A CNN and Dual Swin-Transformer Fusion Network for Remote Sensing Hyperspectral Data Fusion and Classification of Coastal Areas by Dekai Li, Harold Neira-Molina, Mengxing Huang, Syam M.S., Yu Zhang, Zhang Junfeng, Uzair Aslam Bhatti, Muhammad Asif, Nadia Sarhan, Emad Mahrous Awwad

“…CSTFNet integrates spectral and spatial processing capabilities, significantly reducing computational complexity while maintaining high classification accuracy. The improved CNN module employs one-dimensional convolutions to handle high-dimensional data, while the DLST module uses window-based multihead attention to capture both local and global dependencies. …”
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Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique by Hao Huang, Zhaoli Wang, Yaoxing Liao, Weizhi Gao, Chengguang Lai, Xushu Wu, Zhaoyang Zeng

“…However, deep learning algorithms are difficult to explain, like a “black box” that lacks insight. …”
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Causal emissions factor benchmarks during contingent nuclear outages by Pierre Christian, Joel Cofield, Sam Koebrich, Gavin McCormick

“…A key step in implementing this ‘load-shifting’ strategy involves measuring changes of emissions as a consequence of changes in electricity load. While multiple modeling algorithms have previously estimated this quantity, previous methods have been forced to either calibrate against dispatch modeling assumptions, or against statistical models that might not be free of causal confounders. …”
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Efficient Context-Preserving Encoding and Decoding of Compositional Structures Using Sparse Binary Representations by Roman Malits, Avi Mendelson

“…In addition, the proposed algorithms allow to optimize the amount of compute and memory needed to achieve the desired encoding/decoding performance.…”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Catalytic pyrolysis faces the challenge of rapid catalyst deactivation (resulting in a 30% activity loss after 5 cycles), while microwave systems incur high capital costs. …”
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Numerical Simulation of Dynamic Response of Slab-Column Structures under Fire-Explosion Coupled Effects by LIU Jingbo, YANG Qiong, WU Lei, WANG Chengquan, YU Xiongfei, FANG Mingyu, DONG Tengfang

“…ObjectiveSlab-column structures exhibit inherent vulnerabilities to extreme events due to low structural redundancy. While their response to individual fire or explosion hazards has been studied, the sequential scenario of a fire followed by an explosion presents a complex challenge that is not well understood. …”
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Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis by Ana Maria Cristina Jura, Daniela Eugenia Popescu, Cosmin Cîtu, Marius Biriș, Corina Pienar, Corina Paul, Oana Maria Petrescu, Andreea Teodora Constantin, Alexandru Dinulescu, Ioana Roșca

“…<i>Background and Objectives</i>: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. …”
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Relocation Optimization for Shared Electric Vehicles: A Literature Review by Ye Zou, Qian Yu, Dongming Jiang, Youjun Deng

“…Static relocation is analyzed in terms of operator-based relocation and user-based relocation, while dynamic relocation is analyzed in terms of four methodologies: optimization models, simulations, multi-stage methods, and deep reinforcement learning. …”
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Efficient Implementation of Radar Imaging Techniques Including Time Gating Clutter Removal for Through the Walls Applications by Orlandino Testa, Stefano Pisa, Renato Cicchetti

“…Moreover, to reduce the computation time, the numerical procedures are structured in such a way to employ fast Fourier transform or inverse fast Fourier transform algorithms whenever it results possible, while to reduce the artifact effects due to antenna and wall reflections, the time domain gating technique is implemented. …”
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Control of Overfitting with Physics by Sergei V. Kozyrev, Ilya A. Lopatin, Alexander N. Pechen

“…While there are many works on the applications of machine learning, not so many of them are trying to understand the theoretical justifications to explain their efficiency. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…In low Signal-to-Noise Ratio (SNR) conditions, various approaches and algorithms are applied to improve speech quality and intelligibility. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…In structure-based design, AI-enhanced scoring functions and binding affinity models outperform classical approaches, while DL transforms molecular dynamics by approximating force fields and capturing conformational dynamics. …”
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RGB and RGNIR image dataset for machine learning in plastic waste detectionZENODO by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim, Nada Adam, Hadia Abdelgader Osman

“…The increasing volume of plastic waste is an environmental issue that demands effective sorting methods for different types of plastic. While spectral imaging offers a promising solution, it has several drawbacks, such as complexity, high cost, and limited spatial resolution. …”
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The other geopolitics of AI by Carme Colomina Saló, Marta Galceran-Vercher

“…It analyses the spaces, actors and concerns currently overlooked in the dominant discourses on the geopolitics of AI, perspectives that are essential to understand how algorithmic systems are going to develop in the coming years.…”
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Using an Improved Regularization Method and Rigid Transformation for Super-Resolution Applied to MRI Data by Matina Christina Zerva, Giannis Chantas, Lisimachos Paul Kondi

“…The proposed method excels in preserving high-frequency details while effectively suppressing noise, addressing common limitations of conventional SR approaches. …”
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