Three-stage hybrid scheduling method based on link adjustment and arc replacement for large-scale satellite ground station resource scheduling considering idleness rate by Shunyi Cao, Xiaolu Liu, Lei He

“…Then, a Local-tabu Optimization Operator Based on Arc Replacement (LTOO-AR) enhances the idleness rate by replacing task arcs while introducing a local-tabu strategy to prevent the algorithm from becoming trapped in local optima. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth... by Mo Li, Haiyan Li, Zhaoqiang Zhou, Yingshan Chen, Yijia Wang, Tianxiao Li, Qiang Fu

“…This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. …”
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Optimizing AI Transformer Models for <italic>CO</italic>&#x2082; Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support by Javier Saez-Perez, Pablo Benlloch-Caballero, David Tena-Gago, Jose Garcia-Rodriguez, Jose Maria Alcaraz Calero, Qi Wang

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Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers by Evan Scope Crafts, Umberto Villa

“…The results provide insight into the strengths and limitations of existing diffusion-model based posterior samplers, while the benchmark problems provide a testing ground for future algorithmic developments.…”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…Grid search five-fold cross-validation was employed for comprehensive hyperparameter optimization, in conjunction with balanced sampling techniques. …”
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Skewed Multifractal Cross-Correlations Between Green Bond Index and Energy Futures Markets: A New Perspective Based on Change Point by Yun Tian, Zhihui Li, Jue Wang, Xu Wu, Huan Huang

“…This study is the first to use the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm to detect trend change points in the nexuses between the green bond index (Green Bond) and WTI of crude oil, gasoline, as well as natural gas futures. …”
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An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…The proposed approach effectively maintains satellite maneuver constraints while achieving significant improvements in priority-based target acquisition and computational efficiency. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…To overcome this issue, Grey Wolf Optimization (GWO) algorithm is proposed to identify the most suitable initial gains for each agent, providing faster adaptation and consistent performance during the training process. …”
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Frame Theory and Fractional Programming for Sparse Recovery-Based mmWave Channel Estimation by Razvan-Andrei Stoica, Hiroki Iimori, Giuseppe Thadeu Freitas de Abreu, Koji Ishibashi

“…The two algorithms differ from each other in that in the first (slightly more accurate), the resulting convex problem is solved via interior point methods, while the second (stand-alone) makes use of the alternating direction method of multipliers (ADMM). …”
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Container Liner Shipping System Design Considering Methanol-Powered Vessels by Zhaokun Li, Xinke Yu, Jianning Shang, Kang Chen, Xu Xin, Wei Zhang, Shaoqiang Yu

“…Moreover, we propose an adaptive piecewise linearization approach combined with a genetic algorithm, which can efficiently solve large-scale instances. …”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…The Isolation Forest algorithm excels in anomaly detection in high-dimensional datasets, while autoencoders provide nonlinear detection capabilities and adaptive feature learning. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…Furthermore, to enhance test-time optimization within our streaming framework, our novel initialization scheme &#x2019;warm-starts' the current optimization using optimized parameters from the preceding slice. …”
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Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…However, we challenged this assumption by initiating the inverse problem at different locations in the parameter space using a robust variant of a gradient-based method, which ultimately resulted in a better fit than global methods.We tested four different optimization algorithms available in the PEST and PEST++ suites. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Finally, machine learning algorithms such as random forest and XGBoost are used to predict vehicle speed based on onboard data and weather sensor data. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…From the results, it produces two metrics, TKN and coliform, that are higher than WHO guidelines while maintaining the optimal level of DO throughout the duration of the study. …”
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Evaluating Customer Segmentation Techniques in the Retail Sector by Nur Diyabi, Duygu Çakır, Ömer Melih Gül, Tevfik Aytekin, Seifedine Kadry

“…DBSCAN showed strengths in identifying non-spherical clusters, while GMM and SOM provided more granular segmentation. …”
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Designing an Adaptive Velocity Obstacle Avoidance System for Autonomous Mars Rover Navigation in Dynamic Terrains by Karim Ahmadi Dastgerdi, SeyedehMarziyeh SalehiGhahfarokhi, Sadegh Ahmadi Dastgerdi

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Calibrating multiplex serology for Helicobacter pylori by Emmanuelle A. Dankwa, Martyn Plummer, Daniel Chapman, Rima Jeske, Julia Butt, Michael Hill, Tim Waterboer, Iona Y. Millwood, Ling Yang, Christiana Kartsonaki

“…We discuss these challenges and propose a novel solution to optimize the translation of the continuous measurements from multiplex serology into probabilities of H. pylori infection, using classification algorithms (Bayesian additive regressive trees (BART), multidimensional monotone BART, logistic regression, random forest and elastic net). …”
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