Deep Transfer Learning-Based Performance Prediction Considering 3-D Flux in Outer Rotor Interior Permanent Magnet Synchronous Motors by Moo-Hyun Sung, Soo-Hwan Park, Kyoung-Soo Cha, Jae-Han Sim, Myung-Seop Lim

“…Accurate performance prediction in the design phase of permanent magnet synchronous motors (PMSMs) is essential for optimizing efficiency and functionality. While 2-D finite element analysis (FEA) is commonly used due to its low computational cost, it overlooks important 3-D flux components such as axial leakage flux (ALF) and fringing flux (FF) that affect motor performance. …”
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Elevator Control Simulation Using Fuzzy Logic Management by Mehr Ali Qasimi, Asmatullah Nashir

“…Within a set of fuzzy rules, three important linguistic variables are added to improve the performance of the elevator group. …”
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Can digital transformation improve the transparency and accountability of Indonesian public governance? by M. Irwan Tahir, Ani Martini, Anak Agung Ngurah Gunawan, Yogi Makbul, Nirma Yossa, Wisber Wiryanto, Moch Fahrudin, Rahmat Ilya

“…Public administration can increase transparency, efficiency, public participation and data-based decision-making. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…This study investigates an advanced diagnostic strategy to assess particulate filter health based on resistive soot sensors and available engine variables. The sensor data are projected to generate a 2D signature that reflects the changes in filtration efficiency. …”
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Gut health modulation through phytogenics in poultry: mechanisms, benefits, and applications by Aderanti Ifeoluwa Oni, Oyegunle Emmanuel Oke

“…These plant-derived compounds, such as polyphenols, alkaloids, flavonoids, and essential oils exhibit various bioactive properties that improve gut microbiota composition, support immune function, and improve nutrient absorption by influencing gut morphology and digestive enzyme activity. …”
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Compilation of the Accelerated Test Spectrum of Transmission based on Low Loading Strengthening Effect by Zou Xihong, Yang Zhenliang, Yuan Dongmei, Peng Jigang, Zhou Yujun

“…The indoor simulation bench test of transmission is an important method of assessment,evaluation and promotion of its performance.Taking transmission as an example,a program load spectrum compiling method for transmission accelerated fatigue test is presented.The actual road load spectrum of automobile transmission is collected on Automobile Proving Ground in Dianjiang used wireless telemetry technology.The actual load spectrum is pretreated divided gear position,the second gear load spectrum is selected as an example.The frequency distribution matrix of load is obtained based on rainflow counting method,the distributions of mean and range are found to confirm with normal distribution and two- parameter Weibull distribution respectively.The mean of the normal distribution is 91.77 N·m,and the standard deviation is 163.27 N·m,the shape parameter of Weibull distribution is 1.346,and the scale parameter is 305.489,the distributions of load range and mean is independent.The two- dimensional load spectrum with 8×8 levels is established with joint probability distribution function.After two- dimensional load spectra is transformed into one- dimensional 8-level load spectra with variable mean method.Based on damage and low loading strengthening property of half shaft,the equivalent strengthening rule between strengthening loads is explored.By transferring the strengthening loads to the most effective level,the load loading frequency reduced,test efficiency is improved.…”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
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Dynamic Gesture Recognition Algorithm Combining Global Gesture Motion and Local Finger Motion for Interactive Teaching by Li Jiashan, Li Zhonghua

“…Aiming at the problems of complex time sequence and spatial variability of dynamic gestures, this paper proposes a gesture recognition method combining global motion and local motion of fingers. …”
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Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

“…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
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Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis by K. M. Sansum, B. Bond, R. M. Pulsford, A. McManus, A. O. Agbaje, A. M. Skinner, A. R. Barker

“…Abstract This study adopted a compositional framework to cross-sectionally examine the associations between physical activity (PA) and sedentary time (ST) with vascular structure and function and clustered cardiovascular disease (CVD) risk factors in 4277 children (2,226 girls), aged 10.6±0.2 years. …”
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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors by Reem Yousif MEKKI, Mohamed Hassan MUDAWI, Manahil Saidahmed MUSTAFA, Altaiyb Omer Ahmed MOHMMED, Ahmed Bakheet Abd ALLA, Abdel Rahman AHMED

“…Based on the Cox-Snell Residuals and AIC, BIC, and Gompertz (PH) model is an efficient model than other when the values of (AIC=662.21), (BIC=703.83) and (R2=0.211) where maintained Study assessed that the variables dealing with univariate models were signifi cant but had a signifi cant effect on hemodialysis survival. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. …”
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Fokker-Planck Central Moment Lattice Boltzmann Method for Effective Simulations of Fluid Dynamics by William Schupbach, Kannan Premnath

“…This can be interpreted as a new path for the collision process in terms of the relaxation of the various central moments to “equilibria”, which we term as the Markovian central moment attractors that depend on the products of the adjacent lower order moments and a diffusion coefficient tensor, thereby involving of a chain of attractors; effectively, the latter are nonlinear functions of not only the hydrodynamic variables, but also the non-conserved moments; the relaxation rates are based on scaling the drift coefficient by the order of the moment involved. …”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

“…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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Serum Interleukin-6, Interleukin-17A, and transforming growth factor beta are raised in systemic sclerosis with interstitial lung disease by Anupam Wakhlu, Rasmi Ranjan Sahoo, Jyoti Ranjan Parida, Mohit K Rai, Durga P Misra, Vinita Agrawal, Vikas Agarwal

“…Serum IL-6, IL-17A and TGF β1 levels were assayed using ELISA kit and compared among disease subtypes and clinical parameters. Spearman coefficient was used to test correlation between continuous variables. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Firstly, we design a loss function that deliveries the physical relationship among temperature, salinity and density by fusing the Thermodynamic Equation. …”
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