Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…We have evaluated the accuracy of our proposed technique against state-of-the-art biomimetic computing models such as GA, PSO, GWO, DE, and ACO. While ACO achieved up to 89.45% accuracy, our Bayesian Optimization with LSTM outperformed all others, reaching a peak accuracy of 95.55%, demonstrating its effectiveness in enhancing spoken language identification. …”
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Assessment of carbapenems in a mouse model of Mycobacterium tuberculosis infection. by Ravindra Jadhav, Ricardo Gallardo-Macias, Gaurav Kumar, Samer S Daher, Amit Kaushik, Kristina M Bigelow, Eric L Nuermberger, Gyanu Lamichhane, Joel S Freundlich

“…We present further study of a subset of carbapenems, arising from a previously reported machine learning approach, with regard to their mouse pharmacokinetic profiling and subsequent study in a mouse model of sub-acute Mycobacterium tuberculosis infection. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…In recent research, machine learning (ML) methods have achieved considerable success as surrogate models replacing full-wave EM simulation software. …”
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Multisensor Fault Diagnosis of Rolling Bearing with Noisy Unbalanced Data via Intuitionistic Fuzzy Weighted Least Squares Twin Support Higher-Order Tensor Machine by Shengli Dong, Yifang Zhang, Shengzheng Wang

“…Aiming at the limitations of existing multisensor fault diagnosis methods for rolling bearings in real industrial scenarios, this paper proposes an innovative intuitionistic fuzzy weighted least squares twin support higher-order tensor machine (IFW-LSTSHTM) model, which realizes a breakthrough in the noise robustness, adaptability to the working conditions, and the class imbalance processing capability. …”
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Prediction of Water Quality Index of Island Counties Under River Length System—A Case Study of Yuhuan City by Cheng Zhang, Lei Wang, Chuan Lin, Minyuan Lu

“…This case study aims to evaluate the effectiveness of six machine learning models in predicting water quality index (CWQI) and uses SHAP (Shapley Additive exPlans) as an interpretability analysis method to deeply analyze the contribution of each variable to the model’s prediction results. …”
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Revisiting universal extra-dimension model with gravity mediated decays by Kirtiman Ghosh, Katri Huitu, Rameswar Sahu

“…Recognizing that current LHC search strategies are tailored for supersymmetric scenarios and may not fully capture the distinct signatures, we propose optimized strategies using machine learning algorithms to tag boosted SM bosons and enhance signal discrimination against SM backgrounds. …”
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A concept for H2-Diesel engines: CFD-driven dual spray optimization with energy/exergy analysis for enhanced performance and sustainable combustion by Kourosh Ghadamkheir, Mohammad Moghiman, Mohammad Hatami

“…Hydrogen injection improved combustion efficiency, reduced CO and CO2 emissions, and lowered specific fuel consumption, albeit with increased nitrogen oxide and water vapor formation. Finally, a machine learning approach using computational dataset and regression-based optimization was developed to balance engine performance and emissions within knock-limited conditions, providing a practical route toward cleaner and more efficient hydrogen–diesel combustion engines.…”
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TMSB4X is a regulator of inflammation-associated ferroptosis, and promotes the proliferation, migration and invasion of hepatocellular carcinoma cells by Linlin Tang, Yangli Jin, Jinxu Wang, Xiuyan Lu, Mengque Xu, Mingwei Xiang

“…Univariate Cox regression analysis was conducted to screen prognostic genes, and 10 machine learning algorithms were combined to find the optimal strategy to evaluate the prognosis of the patients based on the prognosis-related genes. …”
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A Decision-making Optimization Method for Network Reconfiguration of Power System With New Energy Considering the Synergistic Support of Source-grid by Jian ZHOU, Nan FENG, Yiping JI, Yuyao FENG, Shuai WANG, Shaoyan LI

“…On this basis, a grid reconfiguration optimization model that can coordinate new energy, energy storage, conventional units and transmission network restoration is established and a bi-level optimization strategy is proposed to improve the efficiency of model solution. …”
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High resistance fault detection in DC microgrid using Hilbert Huang transform and vector-based ensemble optimized LSTM networks by H. K. Prashanth Kumar, Ritesh Dash, K. Jyotheeswara Reddy, Nageswara Rao Atyam, Bhabasis Mohapatra

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A lightweight neural attention-based model for service chatbots by Sinarwati Mohamad Suhaili, Mohamad Nazim Jambli

“…Further experiments investigated activation functions and weight initializers integrated into the proposed model to identify optimal configurations that optimize the model’s performance. …”
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Supervised machine learning prediction and investigation of nonlinear optical rectification in Ge/Si0.15Ge0.85 asymmetric coupled triangle quantum wells by A. Cherni, N. Yahyaoui, N. Zeiri, M.L. Bouazizi, M.Al. Zahrani

“…The theoretical data set results are subsequently used to train three machine learning (ML) models, such as artificial neural network (ANN-ML), convolutional neural network (CNN-ML), and Decision Tree (DT-ML), to predict the NOR coefficient based on the structural parameters. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
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Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model by Yiqing Yang, Guoyin Zhang, Yanxia Wu, Zhixiang Zhao, Yan Fu

“…Additionally, the Top-K algorithm optimizes the diagnostic model through a policy network loss function, effectively reducing the number of symptoms and diseases processed and improving the system’s response speed by 1.3–1.9 times compared to the state-of-the-art differential diagnosis systems.…”
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Evolutionary game analysis of stakeholder privacy management in the AIGC model by Yali Lv, Jian Yang, Xiaoning Sun, Huafei Wu

“…The technological development powered by Artificial Intelligence Generated Content (AIGC) models, exemplified by Generative Pre-trained Transformer 4 (GPT-4) and Bidirectional Encoder Representations from Transformers (BERT), has completely transformed machine language processing and fostered substantial technological advancements. …”
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Design and modeling of a nanocomposite system for demineralization of sweet whey by Mina Rezapour, Mohsen Esmaiili, Mehdi Mahmoudian, Alireza Behrooz Sarand

“…The dynamic flux behavior of whey output and salt rejection from whey was modeled using convolutional neural network (CNN) machine learning tools. …”
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Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China by Yanan Zuo, Min Ji, Jiutao Yang, Zhenjin Li, Jing Wang

“…The results indicated that compared with the original RF model, the improved feature optimization model achieves increases of 18.64%, 11.12%, and 11.21% in OOB_score, Accuracy, and F1_score, respectively, and outperforms eight other benchmark models. …”
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Optimizing Biomimetic 3D Disordered Fibrous Network Structures for Lightweight, High‐Strength Materials via Deep Reinforcement Learning by Yunhao Yang, Runnan Bai, Wenli Gao, Leitao Cao, Jing Ren, Zhengzhong Shao, Shengjie Ling

“…Furthermore, the N‐DRL model demonstrates superior performance compared to traditional approaches in optimizing network stability while minimizing mass and computational cost. …”
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Effective Formalization of Design Processes as a Key Factor in Achieving Optimal Solutions When Creating the Final Stages of Steam Turbines by Anatolii O. Tarelin, Iryna Ye. Annopolska