Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. The conjugate problem was constructed, and the functional gradient was computed, while the existence of the Frechet derivative was proved. …”
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Physics-Informed Decoupled Calibration for Fourier Ptychographic Microscopy by Mingdi Liu, Junzhao Liang, Yanxiong Wu, Zicong Luo, Rui Xie, Jiaxiong Luo, Lisong Yan

“…To address this, we propose a physically decoupled correction framework integrating convolutional neural network (CNN), simulated annealing (SA) algorithms, and GPU parallel acceleration. The CNN extracts frequency-domain circular features related to LED positioning errors as physical priors, while the GPU-accelerated SA algorithm accurately solves LED array spatial parameters during FPM forward propagation. …”
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Studying Pupil-Size Changes as a Function of Task Demands and Emotional Content in a Clinical Interview Situation by Daniel Gugerell, Benedikt Gollan, Moritz Stolte, Ulrich Ansorge

“…This was possible with an algorithmic online measure of cognitive load as well as with a conventional pupil-size measure, providing proof of the external validity of the algorithm/online measure.…”
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Numerical Simulation Study on the Response of Ship Engine Room Structure Under Fire Based on Thermo-Mechanical Coupling Model by Yuechao Zhao, Zeya Miao, Shouye Wang, Dihao Ai

“…To precisely assess the post-fire structural integrity of ships, in this study, a thermal–mechanical coupling data interface was created, employing a significant eddy simulation algorithm for fire dynamics and a technique to analyze the structural thermal–mechanical coupling reaction. …”
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Fast and Efficient Drone Path Planning Using Riemannian Manifold in Indoor Environment by Rohit Dujari, Brijesh Patel, Bhumeshwar K. Patle

“…This paper introduces an innovative dual-path planning algorithm rooted in a topological three-dimensional Riemannian manifold (T3DRM) to optimize drone navigation in complex environments. …”
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Standardized Extraction of Air Traffic Control Hazard Features Based on Expert Knowledge by Xianghua Tan, Zhipeng Cai, Zhibin Quan, Weili Zeng

“…Air traffic control (ATC) hazard feature extraction is a key information retrieval task for air traffic hazard records. While text-based feature extraction ranks term importance based solely on statistical results, we aim to use external knowledge to extract features that meet the definition of hazards. …”
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Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London by Kang Xinwei

“…The goal of this work is to satisfy urban consumers’ demand for online shopping while lowering CO2 emissions. However, few studies have focused on the parcel locker itself. …”
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Global Single-Shot Indoor Localization of Autonomous Flight Robots With Minimal Sensor Configuration by Timm von Bergen, Sascha Rock

“…Afterwards, one of two methods is employed: a randomized coarse-to-fine search, in which the search space is iteratively reduced, or a parallel differential evolution algorithm, which enhances pose estimates with evolutionary algorithms while avoiding premature convergence. …”
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An Explainable Machine Learning Model for Predicting Macroseismic Intensity for Emergency Management by Federico Mori, Giuseppe Naso

“…As damage severity increases, feature importance shifts from PGA to PGV, while site-specific variables (slope, Vs30) act as refiners rather than amplifiers of shaking. …”
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Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly by Claudio Urrea

“…Problem: Existing Human–Robot Collaboration (HRC) allocators cannot react at a sub-second scale while accounting for worker fatigue. Objective: We designed a fatigue-aware combinatorial auction executed every 100 ms. …”
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Enhanced Edge Feature Fusion and Visual State Space for Precise Detection of Switch Tip Close Fitting by Chang Zhengtang, Lan Xiangui, Lai Yihui

“…An Edge Feature Enhancement Module uses dilated convolutions to enhance local feature extraction, while a Visual State Space Module in the skip connections captures contextual spatial information. …”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…Moreover, for small-sample datasets, GAN technique can effectively augment tabular training datasets while preserving the original data distribution. …”
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Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials by Ahmed Farid Ibrahim, Mohamed Abdrabou Hussein

“…This approach provides a scalable solution for enhancing AC production sustainability, while addressing critical waste management challenges.…”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). This proposed work provides an accurate prediction of demand for energy conservation and it reduces the burden on electric grids while minimizing the cost of charging. …”
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An optimized implementation of adaptive noise canceller based on proposed shift and add multiplier by Aneela Pathan, Khalil M. Zohaib, Rizwan Aziz, Adil Hussain Chandio, Syed Haseeb Shah

“…Wiener, Steepest, and LMS are the most often utilized. While in hardware translation on ASICS and FPGAs, adaptive filters require more resources than straightforward FIR or IIR designs. …”
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Experimental and numerical investigation on thermal performance of enhanced geothermal system: A case study of Guanzhong basin by Guoyao Jin, Yuxiang Zhao, Ye Min, Xiao Zhang, Chao Jiang, Zijing Tan

“…A multi-objective genetic algorithm correlates operational variables with extraction efficiency, providing a quantitative framework for optimization. …”
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The Sakhalin Ainu: origin and population contacts according to cranial-metric data by Moiseyev V.G., Zubova A.V.

“…Albeit it is generally accepted that the Sakhalin Ainu are decedents of Ainu migrants from Hokkaido, significant cranial differences has been revealed between these two related populations. Thus, while M. Levin argued in favor of the Nivkh component in the Sakhalin Ainu population, A. …”
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SRM-YOLO for Small Object Detection in Remote Sensing Images by Bin Yao, Chengkun Zhang, Qingxiang Meng, Xiandong Sun, Xuyang Hu, Lu Wang, Xilai Li

“…In this paper, we introduce SRM-YOLO, a novel small object detection algorithm based on the YOLOv8 framework. The model incorporates the following key innovations: Reuse Fusion Structure (RFS), which enhances feature fusion; SPD-Conv, which enables effective downsampling while preserving critical information; and a specialized detection head designed for small objects. …”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…The proposed model architecture is simpler and more efficient compared to existing solutions from the literature using approximately only half the amount of NN parameters, while representing a complete three-dimensional material model. …”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. Furthermore, to tackle the non-convexity caused by highly coupled optimization variables, we employ a deep reinforcement learning algorithm based on double deep Q-network and twin delayed deep deterministic policy gradient (DDQN-TD3). …”
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