Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…Common challenges in the area of robotics include issues such as sensor modeling, dynamic operating environments, and limited on-broad computational resources. To improve decision making, robots need a dependable framework to facilitate communication between different modules and the optimal action for real-world applications. …”
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Efficiency assessment of micro hydropower for agriculture using modern modeling by Urishev Omadjon, Salomov Uktam, Ergashev Sirojiddin, Kuchkarov Akmaljon, Madaliev Murodil, Abdukarimov Bekzod, Juraev Nurmakhamad

“…Using modern numerical analysis methods, including computational turbulence modeling algorithms, the study evaluates the energy production and optimization of micro-hydropower plant operation under various conditions. …”
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Delta-V-Based Cooperative Strategies for Orbital Two-Pursuer One-Evader Pursuit–Evasion Games by Sihan Xu, Liran Zhao, Weichen Zhang, Zhaohui Dang

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Towards ML Models’ Recommendations by Lara Kallab, Elio Mansour, Richard Chbeir

“…A prominent way to achieve this is machine learning (ML), which optimizes system performance by employing learning algorithms to create models based on data and its inherent patterns. …”
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Compact bandpass pixelated microwave filters with short-circuited stubs via inverse design by Miguel A. Gomez, Wei Jia, Steve Blair, Berardi Sensale-Rodriguez

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Adaptive Event-Triggered Predictive Control for Agile Motion of Underwater Vehicles by Bo Wang, Junchao Peng, Jing Zhou, Liming Zhao

“…Computational Fluid Dynamics (CFD) software is employed for hydrodynamic analysis and shape optimization. …”
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An Analysis of Consumer Purchase Behavior Following Cart Addition in E-Commerce Utilizing Explainable Artificial Intelligence by Ramazan Esmeli, Aytac Gokce

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Machine Learning Models for Predicting Abnormal Brain CT Scan Findings in Mild Traumatic Brain Injury Patients by Amirmohammad Toloui, Amir Ghaffari Jolfayi, Hamed Zarei, Arash Ansarian, Amir Azimi, Seyed Mohammad Forouzannia, Rosita Khatamian Oskooi, Gholamreza Faridaalaee, Shayan Roshdi Dizaji, Seyed Ali Forouzannia, Seyedeh Niloufar Rafiei Alavi, Mohammadreza Alizadeh, Hadis Najafimehr, Saeed Safari, Alireza Baratloo, Mostafa Hosseini, Mahmoud Yousefifard

“…This study aimed to develop and optimize machine learning (ML) algorithms to predict abnormal brain computed tomography (CT) scans in patients with mild TBI. …”
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Environmental and Economic Dispatching of Fire-Wind Combined System Based on Improved MOPSO by Li Rongshuai, Du Ruiqi, Lu Yi, Jiang Shan

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Brain-Shapelet: A Framework for Capturing Instantaneous Abnormalities in Brain Activity for Autism Spectrum Disorder Diagnosis by Yijie Ren, Zhengwang Xia, Yudong Zhang, Zhuqing Jiao

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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

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Agile DQN: adaptive deep recurrent attention reinforcement learning for autonomous UAV obstacle avoidance by Fadi AlMahamid, Katarina Grolinger

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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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SlidingConv: Domain-Specific Description of Sliding Discrete Cosine Transform Convolution for Halide by Yamato Kanetaka, Hiroyasu Takagi, Yoshihiro Maeda, Norishige Fukushima

“…Therefore, various algorithmic and hardware accelerations have been proposed for filtering. …”
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Total Positivity of the Cubic Trigonometric Bézier Basis by Xuli Han, Yuanpeng Zhu

“…Moreover, we show that for λ=-2 or μ=-2 the basis is not suited for curve design from the blossom point of view. In order to compute the corresponding cubic trigonometric Bézier curves stably and efficiently, we also develop a new corner cutting algorithm.…”
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Harnessing Vehicle-to-Vehicle Communications for 3G Downloads on the Move by Yanmin Zhu, Qinghua Chen, Chao Chen

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Solving Minimum Cost Three-Dimensional Localization Problem in Ocean Sensor Networks by Chao Zhang, Yingjian Liu, Zhongwen Guo, Yu Wang

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Trainable embedding quantum physics informed neural networks for solving nonlinear PDEs by Stefan Berger, Norbert Hosters, Matthias Möller

“…By leveraging the advantages of classical and quantum computers, we can create algorithms that have a potential to be run on noisy intermediate-scale quantum devices (NISQ). …”
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Multi-Level Thresholding Based on Composite Local Contour Shannon Entropy Under Multiscale Multiplication Transform by Xianzhao Li, Yaobin Zou

“…Existing approaches predominantly rely on metaheuristic optimization algorithms, which frequently encounter local optima stagnation and require extensive parameter tuning, thereby degrading segmentation accuracy and computational efficiency. …”
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The Design and Data Analysis of an Underwater Seismic Wave System by Dawei Xiao, Qin Zhu, Jingzhuo Zhang, Taotao Xie, Qing Ji

“…The system adopts a three-stage architecture consisting of watertight instrument housing, a communication circuit, and a buoy to realize high-capacity real-time data transmissions. The host computer performs the collaborative optimization of multi-modal hardware architecture and adaptive signal processing algorithms, enabling the detection of ship targets in oceanic environments. …”
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