Hardware Implementation of Next Generation Reservoir Computing with RRAM‐Based Hybrid Digital‐Analog System by Danian Dong, Woyu Zhang, Yuanlu Xie, Jinshan Yue, Kuan Ren, Hongjian Huang, Xu Zheng, Wen Xuan Sun, Jin Ru Lai, Shaoyang Fan, Hongzhou Wang, Zhaoan Yu, Zhihong Yao, Xiaoxin Xu, Dashan Shang, Ming Liu

“…Reservoir computing (RC) possesses a simple architecture and high energy efficiency for time‐series data analysis through machine learning algorithms. To date, RC has evolved into several innovative variants. …”
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Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation by Wu LX, Ding N, Ji YD, Zhang YC, Li MJ, Shen JC, Hu HT, Jin L, Yin SN

“…By analyzing many literatures, the commonly used K-means algorithm and other algorithms such as hierarchical clustering and consensus clustering are summarized. …”
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A genetic association study of serum acute-phase C-reactive protein levels in rheumatoid arthritis: implications for clinical interpretation. by Benjamin Rhodes, Marilyn E Merriman, Andrew Harrison, Michael J Nissen, Malcolm Smith, Lisa Stamp, Sophia Steer, Tony R Merriman, Timothy J Vyse

“…CRP is increasingly being incorporated into clinical algorithms to compare disease activity between patients and to predict future clinical events: our findings impact on the use of these algorithms. …”
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Degradation and reliability assessment of accuracy life of RV reducers by XU Hang, NIE Yixuan, WEN Dongjie, REN Jihua, HONG Zhihui

“…A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. …”
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Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…Abstract A new computational framework based on machine learning was developed for prediction of Hansen solubility parameters in preparation of pharmaceutical cocrystals with improved properties. …”
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The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain by Yu Cong, Yongfeng Gu, Wen J. Wang, Lei Wang, Zhenshan Xue, Yingyi Chen, Yinghua Jin, Jiawei Xu, Mai-He Li, Hong S. He, Ming Jiang

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Development of a method for differential diagnosis of iron deficiency anemia and anemia of chronic disease based on demographic data and routine laboratory tests using machine lear... by N. V. Varekha, N. I. Stuklov, K. V. Gordienko, R. R. Gimadiev, O. B. Shchegolev, S. N. Kislaya, E. V. Gubina, A. A. Gurkina

“…To select an appropriate artificial intelligence algorithm for predicting serum ferritin (SF) levels and to evaluate its applicability for differential diagnosis of iron deficiency anemia and anemia of chronic diseases.   …”
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On the Importance of Learning Non‐Local Dynamics for Stable Data‐Driven Climate Modeling: A 1D Gravity Wave‐QBO Testbed by Hamid A. Pahlavan, Pedram Hassanzadeh, M. Joan Alexander

“…We find that neural network‐based parameterizations, though predicting GW forcings from wind profiles with 99% accuracy, lead to unstable simulations when RFs are too small to capture non‐local dynamics. …”
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Soft Schemes for Earthquake-Geotechnical Dilemmas by Silvia García

“…Models make it possible to predict or simulate a system’s behavior; in earthquake geotechnical engineering, they are required for the design of new constructions and for the analysis of those that exist. …”
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Design Automation of Sheet Materials Cutting Maps in a Production by A. I. Yakimov, D. A. Denisevich, E. A. Yakimov

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Main Results and Directions of Research on the Creation of Antenna Systems for Advanced Radio-Electronic Equipment by S. V. Kozlov, D. A. Kovalevich, N. I. Listopad

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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Since the associated laboratory/field experiments are time-consuming and labor-intensive, pedotransfer functions (PTFs) that rely on statistical predictors are usually integrated with the existing measurements to predict Kfs in other areas of the field. In this study some of the most appropriate machine learning approaches, including variants of artificial neural networks (ANNs) were used for predicting Kfs by some easily measurable soil attributes. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Businesses across industries face challenges in improving customer retention and reducing churn, making predictive models essential for identifying at-risk customers and enhancing revenue. …”
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Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data by B. Li, B. Li, B. Li, B. Li, H. Xie, H. Xie, S. Liu, Z. Ye, Z. Hong, Q. Weng, Q. Weng, Q. Weng, Y. Sun, Q. Xu, X. Tong

“…The results from the validation comparison show that the elevation accuracy of IC2-GDEM is evidently superior to that of the ASTER GDEM product: (1) the RMSE reduction ratio of the corrected GDEM elevation is between 16 % and 82 %, and the average reduction ratio is about 47 %; and (2) from the analysis of the different topographies and land covers, this error reduction is effective even in areas with high topographic relief (<span class="inline-formula">&gt;15<i>°</i></span>) and high vegetation cover (<span class="inline-formula">&gt;60 %</span>). …”
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Enhancing Efficiency and Reducing the Carbon Footprint of Cloud-Based Healthcare Applications through Optimal Data Preprocessing by El Aziz Btissam, Eddabbah Mohammed, Laaziz Yassin

“…Our results demonstrate that the impact of preprocessing on both accuracy and processing speed varies depending on the algorithm and the type of preprocessing applied. Notable improvements in precision and processing time reductions of up to 35% were observed, highlighting the potential of preprocessing to enhance the performance and sustainability of ML algorithms.…”
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A Personalized Energy Expenditure Estimation Method Using Modified MET and Heart Rate-Based DQN by Min-Seo Kim, Ju-Hyeon Seong

“…Therefore, the proposed algorithm can be applied to various heart rate-based energy consumption prediction methods.…”
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The effect of canine lingual attachments during maxillary arch distalization with clear aligner: a 4D finite element analysis and in vitro simulator study by Bochun Mao, Yajing Tian, Hanzhang Zhou, Yan Gu

“…Method A dual-methodological approach was employed: 1) A four-dimensional finite element model (4D FEM) incorporating automated staging simulation was developed, utilizing iterative computations for long-term tooth movement prediction and thermal expansion algorithms for CA morphology adaptation; 2) An electromechanical orthodontic simulator (OSIM) was implemented for in vitro validation. …”
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Energy-efficient outdoor air flow control in ventilation systems by A. B. Sulin, A. A. Nikitin, T. V. Ryabova, S. S. Muraveinikov, I. N. Sankina

“…The expected microclimate parameters predicted assessment in real time opens up the possibility of using such elements and algorithms for controlling the ventilation and air conditioning system, which provide the required air quality with minimal energy consumption. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…Overall, the FLB-PSO algorithm outperforms traditional PSO in terms of robustness to system dynamics, convergence rate, operational cost reduction, and improved energy efficiency.…”
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Application and prospect of artificial intelligence in empowering the operation and managment of oil and gas pipelines by Qi LIAO, Chunying LIU, Jian DU, Hao LAN, Yongtu LIANG, Haoran ZHANG

“…AI methodologies have found extensive application across various research domains, largely focusing on leak detection, corrosion analysis, risk evaluation, identification, prediction, and optimization. The evolution of AI-driven research has transitioned from conventional approaches like neural networks, expert systems, fuzzy logic, and wavelet analysis towards new-generation algorithms, including deep learning, transfer learning, and reinforcement learning. …”
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