Machine learning and partial differential equations: benchmark, simplify, and discover by Petros Koumoutsakos

“…Many of these simulations are based on models expressed as Partial Differential Equations (PDEs). PDEs are invaluable inductive inference engines, as their solutions generalize beyond the particular problems they describe. …”
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The Effect of Extended Smartphone Screen Time on Continuous Partial Attention by M. Fırat

“…Students with the highest total weekly screen time on short video platform had higher continuous partial attention scores. Students attributed this finding to hypnotic algorithms, distracting redundancy, marketing and advertising, passive receiver mode, short video flow, and surprising content. …”
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Practical Quantum Advantage on Partially Fault-Tolerant Quantum Computer by Riki Toshio, Yutaro Akahoshi, Jun Fujisaki, Hirotaka Oshima, Shintaro Sato, Keisuke Fujii

“…Our framework is based on partially fault-tolerant logical operations to minimize spatial overhead and avoids the costly distillation techniques typically required for executing non-Clifford gates. …”
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Exploratory Study of a Green Function Based Solver for Nonlinear Partial Differential Equations by Pablo Solano-López, Jorge Saavedra, Raúl Molina

“…This work explores the numerical translation of the weak or integral solution of nonlinear partial differential equations into a numerically efficient, time-evolving scheme. …”
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The Algorithmic Auteur by Dan Valeriu Voinea

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Algorithmic governance by Christian Katzenbach, Lena Ulbricht

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Ideologies in Algorithms. How Do Ideologies Give Shape to Algorithms? by Natalia Gondek, Grzegorz Tutak, Jan Gondek

“…The article addresses the growing influence of algorithms on social and cultural life. …”
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Camera Calibration Optimization Algorithm Based on Nutcracker Optimization Algorithm by Lei Li, Zelong Xiao, Taiyang Hu

“…Traditional calibration methods usually achieve approximate solutions due to the complexity of solving nonlinear equations, resulting in reprojection errors. This article proposes a camera calibration optimization algorithm based on the Starling-Inspired Strategy optimization algorithm, which improves calibration accuracy and stability by combining chaotic mapping and sine cosine optimization strategies. …”
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Implementation of Grover’s Algorithm & Bernstein-Vazirani Algorithm with IBM Qiskit by Yang-Che Liu, Mei-Feng Liu

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Universal Synchronization Algorithm for Wireless Sensor Networks—``FUSA algorithm'' by Michal Chovanec, Jana Púchyová, Martin Hudik, Michal Kochláň

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Demand Prediction of Emergency Supplies under Fuzzy and Missing Partial Data by Ming Zhang, Hanlin Wu, Zhifeng Qiu, Yifan Zhang, Boquan Li

“…This study aims at improving supplies demand prediction accuracy under partial data fuzziness and missing. The main contributions of this study are summarized as follows. (1) In view that it is difficult for the turning point of the whitenization weight function to determine fuzzy data, two computational formulas solving “core” of fuzzy interval grey numbers were proposed, and the obtained “core” replaced primary fuzzy information so as to reach the goal of transforming uncertain information into certain information. (2) For partial data missing, the improved grey k-nearest neighbor (GKNN) algorithm was put forward based on grey relation degree and K-nearest neighbor (KNN) algorithm. …”
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Partial discharge pattern recognition based on EEMD singular value entropy by Luo Riping, Luo Yingting, Lai Shiyu, Zhao Xianyang, Wang Liqi

“…Secondly, the singular value decomposition is performed on the reconstructed signal, and the singular value entropy is calculated in combination with the information entropy algorithm. Finally, according to the singular value entropy, the type of GIS partial discharge is distinguished. …”
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Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Ruiqin Tian, Ying Lu

“…This study introduces a partial functional linear spatial autoregressive model which can explore the relationship between a scalar spatially dependent response variable and predictive variables containing both multiple scalar covariates and a functional covariate. …”
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Equilibrium Strategies for Overtaking-Free Queueing Networks under Partial Information by David Barbato, Alberto Cesaro, Bernardo D’Auria

“…We investigate the equilibrium strategies for customers arriving at overtaking-free queueing networks and receiving partial information about the system’s state. In an overtaking-free network, customers cannot be overtaken by others arriving after them. …”
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GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

“…To accurately diagnose partial discharge faults in Gas Insulated Switchgear (GIS), a fault diagnosis method based on Symplectic Geometric Mode Decomposition (SGMD) and improved Long Short Term Memory (LSTM) is proposed. …”
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On the Partial Offloading to Multiple Helpers-Based Task Offloading for IoT Networks by Usman Mahmood Malik, Muhammad Awais Javed, Abdulaziz AlMohimeed, Mohammed Alkhathami, Abeer Almujalli

“…We propose a modified many-to-many matching-based task offloading algorithm to reduce the task latency in a POMH scenario. …”
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Using UMAP for Partially Synthetic Healthcare Tabular Data Generation and Validation by Carla Lázaro, Cecilio Angulo

“…In addition, the common case of lack of information due to technical issues, transcript errors, or differences between descriptors considered in different health centers leads to the need for data imputation and partial data generation techniques. This study introduces a novel methodology for partially synthetic tabular data generation, designed to reduce the reliance on sensor measurements and ensure secure data exchange. …”
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MHD Free Convection in an Enclosure Loaded with Nanofluid and Partially Cross-heated by A. Marfouk, A. Mansour, A. Hasnaoui, A. Amahmid, M. Hasnaoui

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Research on Model Reconstruction Methods for Partial Point Cloud Information Loss by Zhengping CHANG, Guoshuai YUAN, Jiuhua LI, Yang ZHAO, Zhongqi WANG

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Filter Learning-Based Partial Least Squares Regression and Its Application in Infrared Spectral Analysis by Yi Mou, Long Zhou, Weizhen Chen, Jianguo Liu, Teng Li

“…Partial Least Squares (PLS) regression has been widely used to model the relationship between predictors and responses. …”
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