Modeling of binary nanooxides with solid solutions and mixed phases by V. M. Gun’ko

“… The electronic structure of individual metal (Ti, Al) or metalloid (Si) oxides as well as complex (binary, ternary, etc.) oxides is of importance from a practical point of view. …”
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Possibilities of statistical methodology in the study of economic security of the region by Dmitry V. Dianov, Elena A. Radugina

“…These are demographic and resource indicators, and the results and efficiency of the economic complex. The use of the designated statistical tools allowed obtaining such results as justification of analytical capabilities and approbation of statistical methods in the study of economic security of the Moscow region; formation of clusters, consisting of homogeneous municipal districts of the Moscow region, designated as clustering units; calculation of relative analytical indicators; construction and interpretation of regression models.Conclusion: the complex of the obtained results and conclusions, as well as the scientifically based algorithm of statistical tools application, tested in the work, are undoubtedly an important information component in the management of economic and financial security not only in the Moscow region, but also in any region, both in the Central Federal district and in the whole central Russia.…”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…The proposed DL models, Convolutional Long Short-Term Memory (Conv-LSTM2D) and Convolutional Gated Recurrent Unit (Conv-GRU2D), extend traditional LSTM and GRU architectures with 2D convolutional mechanisms to capture complex spatiotemporal dependencies. Additionally, the statistical Autoregressive Integrated Moving Average (ARIMA)/Seasonal ARIMA (SARIMA) models were enhanced through seasonality removal, automated model selection using the auto_arima algorithm, and parameter fine-tuning via grid search to improve their predictive accuracy. …”
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Performance of Fine-Tuning Techniques for Multilabel Classification of Surface Defects in Reinforced Concrete Bridges by Benyamin Pooraskarparast, Son N. Dang, Vikram Pakrashi, José C. Matos

“…These results highlight the potential of these models to improve automated bridge inspection systems and thus increase accuracy and efficiency in real-world applications, as well as provide guidance for the selection of methods based on whether accuracy or overall consistency is more important for a specific application.…”
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The Personalized Approach to the Chronic Central Serous Chorioretinopathy Treatment Based on the Navigated Micropulse Laser Technology by P. L. Volodin, A. V. Doga, E. V. Ivanova, V. A. Pismenskaya, Iu. I. Kukharskaya, E. S. Khrisanfova

“…The developed personalized technology of laser treatment of chronic central serous chorioretinopathy with a micropulse mode with an individual selection of energy parameters on the Navilas 577s navigation system showed high clinical efficiency and safety. …”
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A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

“…To tackle this issue, this paper proposes a new wind speed prediction model that combines four techniques: Discrete Wavelet Transform, which smooths the wind speed signal; Mutual Information, which selects the most informative part of the wind speed time series; Coot Optimization Algorithm for optimal feature selection; and Bidirectional Long Short-Term Memory for capturing complex patterns. …”
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Research on Numerical Calculation Methods for Modelling the Dynamics of Diesel Engine Crankshaft System Substructures by Zhongxu Tian, Zengbin Sun, Yun Zhou, You Zhou

“…These complexities present challenges in achieving comprehensive and efficient dynamic modelling and analysis. …”
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A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants by Wenting Li, Yonggang Li, Dong Li, Jiayi Zhou

“…To address this issue, this paper proposed a multivariable probability density-based auto-reconstruction bidirectional long short-term memory (MPDAR-Bi-LSTM) soft sensor for predicting effluent BOD, enhancing the prediction accuracy and efficiency. Firstly, the selection of appropriate auxiliary variables for soft-sensor modeling is determined through the calculation of k-nearest-neighbor mutual information (KNN-MI) values between the global process variables and effluent BOD. …”
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A Review of Numerical Techniques for Frictional Contact Analysis by Govind Vashishtha, Sumika Chauhan, Riya Singh, Manpreet Singh, Ghanshyam G. Tejani

“…The selection of an appropriate friction constitutive model is crucial; while the Coulomb friction law is common, more sophisticated models are necessary to represent real-world complexities, including surface roughness and temperature dependence. …”
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Harnessing the Power of Improved Deep Learning for Precise Building Material Price Predictions by Zhilong Guo, Yayong Luo, Tongqiang Yi, Xiangnan Jing, Jing Ma

“…However, due to the influence of various complex factors, building material prices exhibit high nonlinearity and instability, often making traditional prediction methods inadequate for achieving optimal results. …”
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PIV-inspired triboelectric nanogenerator for airflow velocity sensing by Sijie Li, Hongyang Ning, Rui Lei, Fujian Zhang, Zhen Liu, Zhongqiang Zhang

“…Fluid diagnostic technologies play a central role in elucidating flow mechanisms, optimizing the performance of aerospace systems, supporting energy transition, and enhancing the operational efficiency of underwater equipment. However, conventional flow field measurement techniques are often limited by high costs, poor adaptability to complex environments, and demanding system requirements. …”
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Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…Large-scale match data from esports games like League of Legends are stored in complex JSON files that often exceed the input token limitations of large language models (LLMs), restricting advanced analysis and applications such as automated commentary and strategic insight generation. …”
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Enhancing Autonomous Truck Navigation in Underground Mines: A Review of 3D Object Detection Systems, Challenges, and Future Trends by Ellen Essien, Samuel Frimpong

“…Integrating autonomous haulage systems into underground mining has revolutionized safety and operational efficiency. However, deploying 3D detection systems for autonomous truck navigation in such an environment faces persistent challenges due to dust, occlusion, complex terrains, and low visibility. …”
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Enhanced Software Testing Model Under Software Warranty Policy Considering Debugger Learning and Time Postponement Factors by Wang Li, Chih-Chiang Fang

“…This allows for the selection of the most effective option. The model takes into account the learning curve, which can significantly impact the efficiency of the software testing process. …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…This approach outperforms existing methods in delineating narrow river systems and resolving water bodies with weak spectral contrast under complex backgrounds, such as vegetation or cloud shadows. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…The implications of these findings that the selection of fall detection algorithms must consider system priorities, whether focused on high accuracy or processing efficiency. …”
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Optimized Navigation for SLAM Using Marker-Assisted Region Scanning, Path Finding, and Mapping Completion Control by Luigi Maciel Ribeiro, Nadia Nedjah, Paulo Victor Rodrigues de Carvalho

“…Specifically, it achieves a 64.39% reduction in poses compared to ACO and 71.07% compared to zigzag navigation, highlighting its efficiency in complex environments.…”
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Balancing Depth for Robustness: A Study on Reincarnating Reinforcement Learning Models by Gang Li, Zhuxiao Wang, Shaowei He, Xiyuan Chen, Yunlei Xie, Jiajun Hu, Kehe Wu, Jingping Jia

“…While deeper networks risk overfitting, shallower architectures struggle to cope with complex task dynamics. Our results highlight the key role of adaptive depth in enhancing the generalization, stability, and efficiency of RRL models.…”
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Spectrum Allocation and Power Control Based on Newton’s Method for Weighted Sum Power Minimization in Overlay Spectrum Sharing by Yang Yu, Xiaoqing Tang, Guihui Xie

“…Maximizing weighted sum energy efficiency (WSEE) requires solving complex multiple-ratio fractional programming (FP) problems. …”
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Matrix Theory for Neutrosophic Hypersoft Set and Applications in Multiattributive Multicriteria Decision-Making Problems by Muhammad Naveed Jafar, Muhammad Saeed

“…Lastly, decision-making issues have been presented by establishing a new algorithm based on a score function, and it has been interpreted with the help of numerical example for the selection of teachers at the college level. In this study, NHSM algorithm is elaborated efficiently and conveniently for optimal choice selection to solve decision-making problems.…”
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