Noise-Aware UAV Path Planning in Urban Environment with Reinforcement Learning by Shahin Sarhan, Marco Rinaldi, Stefano Primatesta, Giorgio Guglieri

“…The Deep Deterministic Policy Gradient (DDPG) algorithm optimizes flight paths, minimizing the noise impact, and balancing both the path length and the population density located under the UAV path. …”
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GARMT: Grouping-Based Association Rule Mining to Predict Future Tables in Database Queries by Peixiong He, Libo Sun, Xian Gao, Yi Zhou, Xiao Qin

“…However, data sparsity—where most fields in large table sets remain unused by most queries—leads to inefficiencies in access optimization. We propose a grouping-based approach (GARMT) that partitions SQL queries into fixed-size groups and applies a modified FP-Growth algorithm (GFP-Growth) to identify frequent table access patterns. …”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Characterizing Satellite Soil Moisture Drydown: A Bivariate Filtering Approach by Jhilam Sinha, Ashish Sharma, Lucy Marshall, Seokhyeon Kim

“…Abstract Drying of soil impacts land energy and water balance, influences the sustainability of vegetation growth, and modulates hydrological extremes including floods. While satellite soil moisture data are widely used for a range of environmental applications, systematic differences from regional in‐situ data prevent their optimal use as key physical signatures (such as soil moisture recession, also termed drydown) are represented differently. …”
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A framework to organize public transport-based crowdshipping by Meijing Zhang, Lynette Cheah

“…This approach allows transit passengers to serve as crowdshippers, ensuring that parcel delivery demand aligns with crowdshipper availability, while considering locker capacity constraints. The framework involves formulating and solving parcel assignment and vehicle routing problems, incorporating matching for parcels and lockers, and using an iterative heuristic algorithm for optimal locker selection. …”
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Slax: a composable JAX library for rapid and flexible prototyping of spiking neural networks by Thomas M Summe, Siddharth Joshi

“…To address this, we introduce Slax, a JAX-based library designed to accelerate SNN algorithm design and evaluation. Slax is compatible with the broader JAX and Flax ecosystem and provides optimized implementations of diverse training algorithms, enabling direct performance comparisons. …”
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The Footropter: A Passive Prosthetic Prescription Tool With Adjustable Forefoot and Hindfoot Stiffness by Harrison L. Bartlett, Brittany M. Moores, Brian E. Lawson, Max K. Shepherd

“…The Footropter, when paired with a preference optimization algorithm, can enable CPs to integrate patients’ experiential input into the clinical prescription process.…”
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UAV Spiral Maneuvering Trajectory Intelligent Generation Method Based on Virtual Trajectory by Tao Chen, Shaopeng Li, Yong Xian, Leliang Ren, Zhenyu Liu

“…A deep reinforcement learning (DRL) approach, employing the proximal policy optimization (PPO) algorithm, is implemented to train a policy network capable of end-to-end virtual trajectory generation. …”
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ISAC Receiver Design: Joint DoA and Data Estimation in the Presence of Incomplete Signal Observations by Iman Valiulahi, Christos Masouros, Mahmoud Alaaeldin, Emad Alsusa

“…We propose a convex optimization based on the dual of atomic norm minimization (ANM). …”
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Machine learning analysis of thermo-bioconvection in a micropolar hybrid nanofluid-filled square cavity with oxytactic microorganisms by Ahlawat Anil, Chaudhary Shilpa, Karuppusamy Loganathan, Mohammed Salman Arafath, Kandasamy Thirumalaisamy, Thameem Basha Hayath

“…In addition, a machine learning approach was employed to accurately predict fluid transport properties using a multilayer artificial neural network structured with a feed-forward backpropagation model and optimized using the Levenberg–Marquardt algorithm. …”
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Coordinated Jamming and Poisoning Attack Detection and Mitigation in Wireless Federated Learning Networks by Sofia Barkatsa, Maria Diamanti, Panagiotis Charatsaris, Stefanos Voikos, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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Efficient RANSAC in 4D Plane Space for Point Cloud Registration by Chang Liu, Chao Liu, Yuming Zhang, Zhongqi Wu, Jianwei Guo

“…3D registration methods based on point-level information struggle in situations with noise, density variation, large-scale points, and small overlaps, while existing primitive-based methods are usually sensitive to tiny errors in the primitive extraction process. …”
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A Machine Learning Approach for Predicting Particle Spatial, Velocity, and Temperature Distributions in Cold Spray Additive Manufacturing by Lurui Wang, Mehdi Jadidi, Ali Dolatabadi

“…To bypass the high cost of purely CFD-driven optimization, we construct a two-stage machine learning (ML) framework trained on 48 high-fidelity CFD simulations. …”
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Lightcone bounds for quantum circuit mapping via uncomplexity by Matthew Steinberg, Medina Bandić, Sacha Szkudlarek, Carmen G. Almudever, Aritra Sarkar, Sebastian Feld

“…We also develop an initial placement algorithm based on graph similarity search, aiding us in optimally placing circuit qubits onto a device. 600 realistic benchmarks using the IBM Qiskit compiler and a brute-force method are then tested against the lightcone bound, with results unambiguously verifying the veracity of the bound, while permitting trustworthy estimations of minimal overhead in near-term realizations of quantum algorithms. …”
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Enhancing the effectiveness of wireless sensor networks through consensus estimation and universal coverage by Hua Tian

“…The method divides the network environment into distinct regions, activating only one node per region based on its residual energy and centrality, while other nodes enter a low-energy sleep mode to conserve power. …”
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Trainable embedding quantum physics informed neural networks for solving nonlinear PDEs by Stefan Berger, Norbert Hosters, Matthias Möller

“…In direct comparison with classical PINNs, this approach showed an ability to achieve superior results while using the same number of parameters, highlighting their potential for more efficient optimization in high-dimensional parameter spaces, which could be transformative for future applications.…”
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A Colored Traveling Salesman Problem with Varying City Colors by Xianghu Meng, Jun Li, MengChu Zhou

“…A colored traveling salesman problem (CTSP) is a path optimization problem in which colors are used to characterize diverse matching relationship between cities and salesmen. …”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…To overcome the challenges posed by homomorphic encryption, we redesign the traditional histogram construction algorithm, optimizing it for secure computation by addressing constraints related to nested loops and conditional statements. …”
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Predictive analysis of solubility data with pressure and temperature in assessing nanomedicine preparation via supercritical carbon dioxide by Hashem O. Alsaab, Yusuf S. Althobaiti

“…The ADABOOST ensemble technique was applied to strengthen the predictive capabilities of the models, while hyperparameter tuning was conducted using the Jellyfish Optimization (JO) algorithm. …”
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Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…Modern military operations require commanders to make complex tactical decisions involving the effective allocation of multiple friendly forces to counter enemy threats while managing diverse streams of battlefield information. …”
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