Deep learning-based technique for investigating the behavior of MEMS systems with multiwalled carbon nanotubes and electrically actuated microbeams by Muhammad Amir, Jamshaid Ul Rahman, Ali Hasan Ali, Ali Raza, Zaid Ameen Abduljabbar, Husam A. Neamah

“…Numerical simulations and graphical demonstrations are presented to verify the accuracy and efficiency of the algorithm. • The study develops a novel DNN-based model to solve non-linear systems in MEMS, particularly for oscillators with MWCNTs. • Deep learning optimizers are applied to improve the accuracy and efficiency of predicting MEMS behavior. • Numerical simulations confirm the effectiveness of the proposed methodology.…”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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An Enhanced Phenology Dataset for Global Drylands from 2001 to 2019 by Yuqi Dong, Yu Zhou, Li Zhang, Feng Tian, Qiaoyun Xie, Yiyang Chen, Linlin Ruan, Bo Zhang

“…Existing land surface phenology (LSP) products exhibit low accuracy in drylands due to coarse spatiotemporal data sources and algorithms optimized for other ecosystems. Here we present the Global Dryland Phenology Dataset (GDPD) for 2001–2019, derived from daily 500-m two-band Enhanced Vegetation Index using MODIS NBAR data and an improved retrieval algorithm with dynamic, pixel-wise amplitude thresholds. …”
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A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images by Hassaan Haider Syed, Muhammad Attique Khan, Usman Tariq, Ammar Armghan, Fayadh Alenezi, Junaid Ali Khan, Seungmin Rho, Seifedine Kadry, Venkatesan Rajinikanth

“…The proposed method includes four core steps: (i) preparing a database of three different classes such as COVID-19, pneumonia, and normal; (ii) modifying three pretrained deep learning models such as VGG16, ResNet50, and ResNet101 for the classification of COVID-19-positive scans; (iii) proposing an activation function and improving the firefly algorithm for feature selection; and (iv) fusing optimal selected features using descending order serial approach and classifying using multiclass supervised learning algorithms. …”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…There is an urgent need to overcome bottlenecks in areas such as algorithmic fusion, dynamic data sharing, and deep AI integration to enable a leap from localized optimization to system-wide intelligent decision-making. …”
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A state-of-the-art review of soft computing-based monitoring and control in the machining of hard alloys by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak, Abhijit Bhowmik

“…These innovations are supported by suitable modeling and metaheuristic techniques, including adaptive neuro-fuzzy inference systems (ANFIS), simulated annealing, teaching-learning-based optimization (TLBO), the finite element method (FEM), and the non-dominated sorting genetic algorithm II (NSGA-II). …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…We carefully split the reference data into training and test sets, allowing for independent and robust model validation. Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. …”
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Enhanced Real-Time Simulation of ROV Attitude and Trajectory Under Ocean Current and Wake Disturbances by Yujing Zhao, Shipeng Xu, Xiaoben Zheng, Lisha Luo, Boyan Xu, Chunru Xiong

“…The proposed system significantly improves trajectory evolution stability and consistency, compared to traditional models. …”
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Real-Time Common Rust Maize Leaf Disease Severity Identification and Pesticide Dose Recommendation Using Deep Neural Network by Zemzem Mohammed Megersa, Abebe Belay Adege, Faizur Rashid

“…Additionally, ResNet50 exhibited lower time complexity during model development. This study demonstrates the potential of ResNet50 models for improving maize disease management.…”
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Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping by Alexander Gresch, Martin Kliesch

“…They are helpful for identifying measurement settings that improve the energy estimate the most. This task constitutes an NP-hard problem. …”
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AMNED: An Efficient Framework for Spiking Neuron Coding in AirComp Federated Learning by Juncheng Ji, Chan-Tong Lam, Ke Wang, Benjamin K. Ng

“…This paper advances ACFL technologies by proposing the Adaptive Memristor Neuron Encoding-Decoding (AMNED) framework for AirComp Federated Learning (ACFL), enabling efficient, privacy-preserving model aggregation optimized for resource-constrained wireless environments. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…This model improves coefficient of determination (R2) and ratio of performance to interquartile distance (RPIQ) by 0.09 and 0.28, respectively, and reduces root mean square error (RMSE) by 0.52 g kg−1 compared to Model (ii). …”
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An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting by Haipeng Zhang, Hua Luo

“…Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. …”
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Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction by Bo Sun

“…The study investigates the revolutionary possibilities of Gated Recurrent Neural Networks (GRNN) to improve ELL-tailored training. The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks by Deyu Lin, Quan Wang, Deqin Lin, Yong Deng

“…The issues which exist in WSNs are proposed and the primary reason why cluster head election is hard to control is then presented. A mathematical model aiming to ease the hot spots problem via optimizing the cluster size is proposed and an optimal cluster size (OCS) algorithm is given firstly. …”
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Joint source–channel rate allocation with unequal error protection for space image transmission by Dan Dong, Shaohua Wu, Dongqing Li, Jian Jiao, Chanjuan Ding, Qinyu Zhang

“…This separate design, although simple to be implemented, cannot explore the transmission performance to the most. In this article, we propose a joint source–channel rate allocation framework to improve the space image transmission performance. …”
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Research on adaptive motion methods of flexible knee joints based on the artificial potential field by LUO Tianhong, LI Chaoyang, MA Xiangyu, FU Qiang, FANG Shangchen

“…ObjectiveConsidering the tracking error of the motion trajectory of the flexible knee joint and the influence of the flexibility on the joint motion, an adaptive impedance control method based on the artificial potential field (APF) was proposed.MethodsThe method took the pneumatic artificial muscle as the power source, and by establishing a kinetic model between the human-machine interaction moment and the knee joint motion angular velocity, the size of the impedance control parameter could be adjusted in real time, so as to realize the following of the motion of the exoskeleton knee joint and the human leg; the control parameter was optimized using the APF concept to enhance the effect of the motion following, and the effectiveness of the algorithm was verified by simulation and test.ResultsThe results show that the proposed APF-based adaptive impedance control method enables the exoskeleton to adaptively track the human motion trajectory and can reduce the error of trajectory tracking, thus improving the suppleness of the flexible knee joint control and enhancing the human-machine synergy of the system.…”
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Enhancing Airport Traffic Flow: Intelligent System Based on VLC, Rerouting Techniques, and Adaptive Reward Learning by Manuela Vieira, Manuel Augusto Vieira, Gonçalo Galvão, Paula Louro, Alessandro Fantoni, Pedro Vieira, Mário Véstias

“…The system also enables accurate indoor localization without relying on a Global Positioning System (GPS), supporting seamless movement and operational optimization. By combining VLC, adaptive AI models, and rerouting strategies, the proposed approach contributes to safer, more efficient, and human-centered airport mobility.…”
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High‐Precision Prediction of Ionospheric TEC in the China Region Based on CMONOC High‐Resolution Data and an Auxiliary Attention Temporal Convolutional Network by Jianghe Chen, Pan Xiong, Haochen Wu, Xiaoran Zhang, Xuemin Zhang, Rongzi Chai, Ting Zhang, Kaixin Wang, Chaoyu Wang

“…At the data level, a non‐integrated spherical harmonic model and Differential Code Bias correction method are employed to significantly reduce interpolation errors and improve model accuracy. …”
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