Logical reasoning for human activity recognition based on multisource data from wearable device by Mahmood Alsaadi, Ismail Keshta, Janjhyam Venkata Naga Ramesh, Divya Nimma, Mohammad Shabaz, Nirupma pathak, Pavitar Parkash Singh, Sherzod Kiyosov, Mukesh Soni

“…Additionally, the suggested strategy dramatically minimises the quantity of user-provided training data needed in comparison to machine learning-based behaviour identification techniques.…”
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Orbital-free density functionals based on real and reciprocal space separation by Bishal Thapa, Tracey G. Oellerich, Maria Emelianenko, Phanish Suryanarayana, Igor I. Mazin

“…As a demonstration of principle, we choose for the former the Thomas-Fermi-von Weizsäcker (TFW) kinetic energy density functional (KEDF) and for the latter a form derived from the Lindhard function, but with the two system-dependent adjustable parameters. These parameters are machine-learned from Kohn-Sham data using Bayesian linear regression with a kernel method, which employs moments of the Fourier components of the electronic density as the descriptor. …”
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Human–AI collaboration for modeling heat conduction in nanostructures by Wenyang Ding, Jiang Guo, Meng An, Koji Tsuda, Junichiro Shiomi

“…This approach is used to determine the parameters that govern phonon transmission over frequencies and incidence angles. …”
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Acoustic Emission from Concrete: Critical Slowing Down Analysis and Compressive Strength Prediction by Zhiqiang Lv, Annan Jiang, Zhen Tan

“…This work pursues two primary aims: identifying the precursory point by the CSD analysis of AE series and using acoustic emission parameters to predict the compressive strength of concrete utilizing the artificial neural network (ANN), extreme learning machine (ELM), and support vector machine (SVM). …”
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ACCELERATED TEST TO DETERMINE THE CORROSION BEHAVIOR OF STEELS IN BOILERS BURNING SUGARCANE BIOMASS by Abel Rivas Gutierrez, Carlos Lariot Sánchez, Beatriz Concepción Rosabal, Lizet Rodríguez Machín

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Transient simulation of multi-product pipeline driven by flow mechanisms and operational data by Jian DU, Haochong LI, Qi LIAO, Kaikai LU, Jianqin ZHENG, Xiao YU

“…Most existing transient estimation methods rely on precise and reliable physical models, which involve high computational costs to address multi-condition and multi-parameter combinations. In contrast, approaches based on machine learning tend to lack reliability and accuracy, as they often overlook the physical patterns associated with pipeline transients. …”
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Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (<i>δ</i>HBV-globe1.0-hydroDL) by D. Feng, D. Feng, D. Feng, H. Beck, J. de Bruijn, J. de Bruijn, R. K. Sahu, Y. Satoh, Y. Wada, J. Liu, M. Pan, K. Lawson, C. Shen

“…More recently, differentiable physics-informed machine learning models with a physical backbone can systematically integrate physical equations and DL, predicting untrained variables and processes with high performance. …”
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A Review of Degradation and Reliability Analysis of a Solar PV Module by Zafar Ullah Khan, Adnan Daud Khan, Khalid Khan, Soliman Abdul Karim Al Khatib, Shahbaz Khan, Muhammad Qasim Khan, Abid Ullah

“…Data-driven analytical methods, such as DL (Deep Learning) ML (Machine Learning) models, have astounding computational abilities to process large amounts of data, with diverse features, and with minimal computation time. …”
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Accurate prediction of damage depth of multi-story structural footings with Matlab implementation by Ang LI, Weidong WANG, Qian MOU, Feng WANG, Zhenghe MA, Lei ZHAO, Gang HUANG, Yonggen ZHOU, Shengqi TIAN

“…The results show that ① most of the working conditions in the calculation of the damage depth of multilayer structure base plate need to be solved by Taylor expansion and quadratic equation several times, and the manual calculation process is long and complicated, which is very likely to lead to deviations in the calculation results; ② by comparing the maximum damage depth of the base plate under the same working condition with the same parameters by manual calculation and machine calculation (Matlab built-in function), it can be seen that with the increase of the number of layers of the base plate, the manual solution process leads to the maximum damage depth of the base plate due to the repeated application of Taylor expansion. ③ The main interface of the software contains the number of layers, layer thickness, mechanical parameters, input boxes, calculation buttons, etc., which can quickly and intelligently identify the working conditions and calculate the maximum depth of damage of the bottom slab and the maximum depth of damage from the mining face to the bottom slab. ④ will be a mine of flat coal related lithological mechanical parameters into the software solution, by comparing and analyzing the five-layer structure of the maximum depth of destruction of the base plate theoretical value, fitting value, measured value and software value can be seen, the theoretical value and measured results deviation of 0.57 m, software value and measured value of the difference of 0.14 m, the results of multi-layer calculations under the software calculations are more in line with the actual needs, can be for the bottom of the board of the prevention and control of water hazards and safety of mining to provide a reliable technology parameter.…”
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Cálculo de la fuerza de fricción necesaria para extraer el coque de hornos solera para el diseño de prototipos de máquinas de empuje by Oscar Manuel Duque Suarez, Marco José Duarte Márquez, Leopoldo Valero Jaimes, Elio Alarcón Suarez, Sergio Andres Davila Sepulveda

“…Theoretically, a procedure is presented, using parameters such as coke cake weight and friction coefficients, to determine the friction and thrust forces. …”
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SegTrackDetect: A window-based framework for tiny object detection via semantic segmentation and tracking by Aleksandra Kos, Karol Majek, Dominik Belter

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Investigating the stability of the yield strength of the friction stir welding joint of similar amorphous thermoplastic based on the Ordered Weighted Averaging operators by N. Sadeghian, A.R. Chaji

“…Welding is carried out using a steel tool mounted on a milling machine. The pin of the tools consists of cylindrical and conical profiles. …”
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Stacking modeling with genetic algorithm-based hyperparameter tuning for uniaxial compressive strength prediction by Tanveer Alam Munshi, Khanum Popi, Labiba Nusrat Jahan, M. Farhad Howladar, Mahamudul Hashan

“…Measuring rock strength using an uniaxial testing machine is destructive and costly, requiring high-quality rock samples. …”
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The Mathematical Model of Coupling Calculation the Electromagnetic Field and Heats of End Zone Powerful Turbogenerator by O. H. Kensytskyi, D. I. Hvalin, K. O. Kobzar

“…Having taken the distribution of electromagnetic parameters obtained in the load mode of the machine as the initial data, the thermal losses in the elements and nodes of the end zone are determined. …”
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Skeleton-Based Data Augmentation for Sign Language Recognition Using Adversarial Learning by Yuriya Nakamura, Lei Jing

“…However, it is difficult to collect sign language data, and many datasets suffer from data lack and imbalance, leading to overfitting and reduced accuracy in machine learning. In general, data augmentation is used as a solution to the problems but model training and data augmentation are performed independently, and it is difficult to adjust the parameters for data augmentation. …”
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Artificial Intelligence Systems for Solving Problems of Agro­Industrial Complex Digitalization and Robotization by A. L. Ronzhin, A. I. Savel'ev

“…Machine learning numerical methods were applied. Possible ways of formulating recommendations for the land revegetation and amelioration were demonstrated. …”
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Robustness of Neural Ratio and Posterior Estimators to Distributional Shifts for Population-level Dark Matter Analysis in Strong Gravitational Lensing by Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur

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Enhanced Performance by Time-Frequency-Phase Feature for EEG-Based BCI Systems by Baolei Xu, Yunfa Fu, Gang Shi, Xuxian Yin, Zhidong Wang, Hongyi Li, Changhao Jiang

“…We introduce a new motor parameter imagery paradigm using clench speed and clench force motor imagery. …”
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Conceptual Basis for Developing Electric Plot Combine Harvester with Combined Power-Generating Plant by Mikhail E. Chaplygin, Ivan A. Starostin, Alexander S. Ovcharenko

“…There was carried out the analysis of machine harvesting technologies, technical characteristics and operating modes of modern plot grain combine harvesters. …”
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Single-cell microbiota phenotyping reveals distinct disease and therapy-associated signatures in Crohn’s disease by Lisa Budzinski, Gi-Ung Kang, René Riedel, Toni Sempert, Leonie Lietz, René Maier, Janine Büttner, Bettina Bochow, Marcell T. Tordai, Aayushi Shah, Amro Abbas, Tanisha Momtaz, Jannike L. Krause, Robin Kempkens, Katrin Lehman, Gitta A. Heinz, Anne E. Benken, Stefanie Bartsch, Kathleen Necke, Ute Hoffmann, Mir-Farzin Mashreghi, Robert Biesen, Tilmann Kallinich, Tobias Alexander, Bosse Jessen, Carl Weidinger, Britta Siegmund, Andreas Radbruch, Anja Schirbel, Benjamin Moser, Hyun-Dong Chang

“…To exploit the discriminatory potential of both, immunoglobulin coated bacteria and the altered surface sugar expression of bacteria in CD, we developed a multiplexed single cell-based analysis approach for intestinal microbiota. By multi-parameter microbiota flow cytometry (mMFC) we characterized the intestinal microbiota of 55 CD patients and 44 healthy controls for 11-parameters in total, comprising host-immunoglobulin coating and the presence of distinct surface sugar moieties. …”
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