Deep Reinforcement Learning for Efficient Scheduling of Ground-based Astronomical Observations by Hai Cao, Shaoming Hu, Junju Du, Xu Chen, Shuqi Liu, Shuai Feng, Bo Zhang, Yuchen Jiang

“…To support the training of the deep neural network, we propose a scoring mechanism to evaluate the effectiveness of the observations, which is optimized through a refined REINFORCE algorithm with a baseline. …”
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Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets by Catarina Lopes, Andreia Brandão, Manuel R. Teixeira, Mário Dinis-Ribeiro, Carina Pereira

“…Leveraging transcriptomic data from the Gene Expression Omnibus (GEO), we constructed and validated predictive models through machine learning algorithms within the tidymodels framework. Tissue-based models were validated on independent tissue datasets, and subsequently applied to saliva. …”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…This review highlights the significant potential of AI-enhanced qEEG as a non-invasive, cost-effective tool for the diagnosis of AD in its prodromal and dementia stages, while also identifying areas requiring further research to optimize its clinical application. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…It was shown that artificial neural networks were the most common kind of trained model, while several other models were often used as benchmarks for performance. …”
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Ubiquitous memory augmentation via mobile multimodal embedding system by Dongqi Cai, Shangguang Wang, Chen Peng, Zeling Zhang, Zhenyan Lu, Tao Qi, Nicholas D. Lane, Mengwei Xu

“…The core design draws inspiration from the memory functions of the human brain, utilizing coarse-grained embeddings to identify likely candidates, which are then refined through query-driven fine-grained retrieval. A series of algorithm-hardware orchestrated optimizations automatically navigates this process and strengthen the embedding quality. …”
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Double Deep Q-Network-Based Solution to a Dynamic, Energy-Efficient Hybrid Flow Shop Scheduling System with the Transport Process by Qinglei Zhang, Huaqiang Si, Jiyun Qin, Jianguo Duan, Ying Zhou, Huaixia Shi, Liang Nie

“…In addition, 36 test instances of varying sizes, simplified from the excavator boom manufacturing process, are designed for comparative experiments with traditional algorithms. The experimental results demonstrate that DDQCE achieves 40% more Pareto-optimal solutions compared to NSGA-II and MOEA/D while requiring 10% less computational time, confirming that this algorithm efficiently solves the TDEHFSP problem.…”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Classical keypoint matching methods find the extreme pose transitions between cameras present in a CVGL configuration challenging to operate in, while deep neural networks demonstrate superb capacity in this area. …”
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Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side by Ali Sharida, Abdullah Berkay Bayindir, Sertac Bayhan, Haitham Abu-Rub

“…Then, an adaptive estimation strategy employing a recursive least square algorithm is proposed for online dynamic model estimation, which is then used by the IMPC for optimal switching states prediction. …”
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Model‐Free Deep Reinforcement Learning with Multiple Line‐of‐Sight Guidance Laws for Autonomous Underwater Vehicles Full‐Attitude and Velocity Control by Chengren Yuan, Changgeng Shuai, Zhanshuo Zhang, Jianguo Ma, Yuan Fang, YuChen Sun

“…This framework enables seamless switching among guidance modes, such as waypoint following, path following, and trajectory tracking, to achieve optimal attitude control. For comprehensive control of roll, pitch, yaw, and longitudinal velocity, an augmented‐twin delayed deep deterministic policy gradient (A‐TD3) algorithm streamlines the training of the control agent. …”
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Toward edge-computing-enabled collision-free scheduling management for autonomous vehicles at unsignalized intersections by Ziyi Lu, Tianxiong Wu, Jinshan Su, Yunting Xu, Bo Qian, Tianqi Zhang, Haibo Zhou

“…Second, this problem is solved with low complexity by the Edge Intelligence Optimal Entry Time (EI-OET) algorithm based on edge-cloud computing power support. …”
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Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles by Xianjian Jin, Huaizhen Lv, Yinchen Tao, Jianning Lu, Jianbo Lv, Nonsly Valerienne Opinat Ikiela

“…The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with a deep deterministic policy gradient (DDPG)-based deep reinforcement learning (DRL) algorithm for dynamic optimization of controller parameters to improve tracking accuracy and robustness. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…The grayscale banding is eliminated by incorporating a visual optimization strategy based on image gradients. Maximum Histogram Equalization (MHE) is used to achieve high contrast while maintaining fidelity to the original content. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…For instance, understanding gas emissions from crops can help farmers optimize their activities, reducing fertilizer and pesticide use while improving yields. …”
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Deep learning-based phase demodulation for distributed acoustic sensor by Yiming Tang, Kewei Liu, Chen Liu, Haiyong Wu, Rugang Wang, Mengmeng Chen, Fei Xu

“…Experimental results demonstrate that the proposed method significantly enhances processing speed while maintaining accuracy comparable to traditional demodulation algorithms. …”
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A Novel PAPR in OTFS Systems Through ISSA-PTS and ISPR Techniques by Gerges Mansour Salama, Amira A. Mohamed, Aziza I. Hussein, M. Mourad Mabrook

“…The hybrid ISSA-PTS approach optimizes phase rotations to reduce PAPR, while the ISPR technique further enhances PAPR reduction by iteratively rotating sub-block phases without compromising BER. …”
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Nonlinear Model Predictive Control for Trajectory Tracking of Omnidirectional Robot Using Resilient Propagation by Mahmoud El-Sayyah, Mohamad R. Saad, Maarouf Saad

“…This paper proposes an enhanced Nonlinear Model Predictive Control (NMPC) framework that incorporates a robust, convergent variant of the resilient propagation (RPROP) algorithm to efficiently solve the Nonlinear Optimization Problem (NOP) in real time. …”
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Research on Iterative Learning Method for Lower Limb Exoskeleton Rehabilitation Robot Based on RBF Neural Network by Jing Li, Huimin Jiang, Moyao Gao, Shuang Li, Zhanli Wang, Zaixiang Pang, Yang Zhang, Yang Jiao

“…MATLAB 2021 simulations demonstrate the proposed algorithm’s superior trajectory tracking performance compared to conventional sliding mode control, effectively eliminating control chattering. …”
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A Blockchain-Based Secure Distributed Authentication Scheme for Internet of Vehicles by Zhanfei Ma, Jing Jiang, Hui Wei, Bisheng Wang, Wenli Luo, Haoye Luo, Dongxiang Liu

“…Second, in the IoV authentication process, smart contract technology is used to achieve automatic triggering of the authentication process, and an optimized Practical Byzantine Fault Tolerant Consensus (PBFT) algorithm is designed to add the authentication information to the blockchain ledger so that the authentication results can be reused. …”
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Handover Strategy for LEO Satellite Networks Using Bipartite Graph and Hysteresis Margin by Sahar Eydian, Maryam Hosseini, Gunes Karabulut Kurt

“…The proposed approach utilizes the Kuhn-Munkres (KM) algorithm to achieve optimal matching with maximum weight, thereby ensuring efficient load distribution and high-quality communication. …”
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Experimental study on mechanical properties of triaxial geogrid reinforced marine coral sand-clay mixture based on 3D printing technology by Danda Shi, Kaiwei Xu, Zhiming Chao, Zhiming Chao, Peng Cui, Peng Cui

“…Based on the experimental results, a dataset was established, while a novel machine learning model named GP-BPNN was proposed, integrating genetic algorithm (GA), particle swarm optimization (PSO), and backpropagation neural network (BPNN). …”
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