Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…Our findings suggest that while classification is robust across different transformations, the variation in feature selection necessitates caution when using machine learning for biomarker identification. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…The findings demonstrate that the proposed method can effectively adapt to large-scale air combat environments while achieving high win rates and rapid decision-making performance.…”
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Flexible hardware for teaching and research in renewable energy and off-grid microgrids by Cristian Escudero-Quintero, Juan Pablo Guzman-Rodriguez, Juan Pablo Villegas-Ceballos, Elkin Edilberto Henao-Bravo, Daniel Gonzalez-Montoya

“…The platform enables real-time energy management using FPPT algorithms while providing an intuitive graphical interface for data visualization and system monitoring. …”
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Nonlinear dynamics of the media addiction model using the fractal-fractional derivative technique by Saima Rashid, Rehana Ashraf, Ebenezer Bonyah

“…The Atangana-Baleanu FF differential operators are recently defined in FF differential operators that are applied to characterize the SMA model’s mathematical algorithm. We investigated the numerical behaviour of the SMA in three ways: (i) changing the fractional-order α as well as the fractal-dimension ℘; (ii) changing α while keeping ℘ constant; and (iii) changing ℘ while keeping α constant. …”
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Design of Nonlinear PID and FOPID Controllers for Electronic Throttle Valve Plate’s Position by Mohamed Jasim Mohamed, Luay Thamir Rasheed

“…A metaheuristic optimization technique, namely, the grey wolf optimization (GWO) algorithm, is introduced for optimizing the controllers’ parameters while minimizing the integral of the cube time square error (IT^3SE) cost function. …”
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Distributed Target Detection with Coherent Fusion in Tracking Based on Phase Prediction by Aoya Wang, Jing Lu, Shenghua Zhou, Linhai Wang

“…In order to obtain the superiority of coherent processing while overcoming the real implementation difficulties of a coherent framework, this paper studies a distributed coherent detection algorithm for fusion detection. …”
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AlphaRouter: Bridging the Gap Between Reinforcement Learning and Optimization for Vehicle Routing with Monte Carlo Tree Searches by Won-Jun Kim, Junho Jeong, Taeyeong Kim, Kichun Lee

“…However, an inherent gap exists between computationally driven DRL and optimization-based heuristics. While a DRL algorithm for a certain problem is able to solve several similar problem instances, traditional optimization algorithms focus on optimizing solutions to one specific problem instance. …”
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Evaluating Sparse Inertial Measurement Unit Configurations for Inferring Treadmill Running Motion by Mackenzie N. Pitts, Megan R. Ebers, Cristine E. Agresta, Katherine M. Steele

“…Inertial measurement units (IMUs) are used to analyze running performance. While leveraging one sensor to estimate kinematic and kinetic variables is common, sparsity limits the number of digital biomarkers that can be evaluated. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…One of the main challenges in this process lies in the nonlinear relationship between screw positions and the filter’s frequency response, making conventional tuning methods difficult and inefficient. Additionally, while intelligent algorithms can assist in tuning, they often require large volumes of simulated data, leading to high computational costs. …”
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A Dynamic Framework for Community-Facility Siting with Inter-Community Competition by Sisi Zhu, Haoying Han, Anran Dai

“…This study proposes a bi-objective multi-scenario dynamic model (BOMSDM) for community-facility siting, which aims to maximize service efficiency and social equity while considering variable facility numbers and inter-community competition. …”
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Trading in the Quantum Era: optimizing Bitcoin gains and energy costs by Simona-Vasilica Oprea, Adela Bâra, Cristian Bucur, Bogdan-George Tudorică, Niculae Oprea

“…This paper presents an in-depth analysis of a Quantum-inspired Multi-objective Optimization Algorithm (QMOA) applied to a unique problem: maximizing trading profits while minimizing energy costs. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…Two experimental studies validate the approach: the first systematically evaluates multiple predefined shading patterns to identify optimal characteristics, while the second demonstrates that algorithmic optimization of highly irregular shading configurations can simultaneously improve multiple visual comfort metrics, significantly outperforming regular shading patterns in terms of glare reduction, view preservation, and spatial frequency performance.…”
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Bayesian Optimized GridDehazeNet for Adaptive Haze Removal in Real-World Applications by Sungkwan Youm

“…Haze removal is essential for improving image visibility in applications like autonomous vehicles and surveillance. While models like GridDehazeNet enhance dehazing performance, our research emphasizes that selecting appropriate image data and application methods is even more crucial. …”
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A Gain-Computation Enhancements Resource Allocation for Heterogeneous Service Flows in IEEE 802.16 m Mobile Networks by Wafa Ben Hassen, Meriem Afif

“…In a single service access, we propose a dynamic resource allocation algorithm at the physical layer aiming to maximize the cell data rate while ensuring fairness among users. …”
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Hybrid energy system optimization integrated with battery storage in radial distribution networks considering reliability and a robust framework by Mohammad Javad Aliabadi, Masoud Radmehr

“…Abstract This research presents a robust optimization of a hybrid photovoltaic-wind-battery (PV/WT/Batt) system in distribution networks to reduce active losses and voltage deviation while also enhancing network customer reliability considering production and network load uncertainties. …”
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Reprogramming Heritage: An Approach for the Automatization in the Adaptative Reuse of Buildings by Marta Domènech-Rodríguez, David López López, Sergi Nadal, Anna Queralt, Còssima Cornadó

“…The proposed methodology for a computational algorithm aims to systematise spatial characteristics, assess programmatic needs, and optimise building usage, while addressing challenges such as data integration and quality assurance. …”
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Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements by Tat Khoa Doan, Trung Thanh Nguyen, An-Le Van

“…The entropy method and vibration and communication particle swarm optimization (VCPSO) algorithm were employed to compute the weights and determine optimal factors. …”
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Investigation of soil resistivity impacts on the electrodes of grounding system subjected to lightning strikes by Osama E. Gouda, Adel Z. El Dein, Sara Yassin, Matti Lehtonen, Mohamed M. F. Darwish

“…The study is done on the behaviour of the ground electrodes while the resistivity of the soil is altered from small to high value in the case of homogeneous soil, while the study is obtained on two‐layer soils in the case of diverse values of the reflection factor. …”
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Privacy-preserving and verifiable spectral graph analysis in the cloud by Yuzhao Song

“…Current schemes are proposed for privacy alone under the semi-honest model, while disregarding the realistic threat posed by the misbehaving cloud that might skip computationally intensive operations for economic gain. …”
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Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

“…This paper presents a systematic approach to molecular networks by integrating GNN models with the DoReFa-Net quantization algorithm. The proposed method aims to enhance computational efficiency while maintaining predictive performance, enabling lightweight yet effective models suitable for molecular task. …”
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