The rainfall-runoff model for the Carpathian flysch catchment using the SWAT+ hydrological software by Wiktor Halecki, Dawid Bedla

“…A soil and agricultural map, supplemented with lithological content from a detailed geological map, was used as the input layer for QGIS ver. 3.16. In the next stage, multiannual meteorological data (1991–2020) were added to the SWAT+ model, which included: minimum and maximum daily air temperature, daily rainfall, average daily radiation and average daily wind speed. …”
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Modeling thermal-technical parameters of a solar pond using COMSOL multiphysics by Elmurodov N.S., Kodirov I.N., Toshboev A.R., Makhamov Kh.T., Ruzieva Z.K., Kurbonov B.E.

“…The article presents the experiments of scientific study of the temperature changes of the pond layers at the given solar radiation values inside the solar pond device modeled using Comsol Multiphysics. …”
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Event-Tree Based Sequence Mining Using LSTM Deep-Learning Model by János Abonyi, Richárd Károly, Gyula Dörgö

“…During the operation of modern technical systems, the use of the LSTM model for the prediction of process variable values and system states is commonly widespread. …”
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Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long‐Term Observations at ARM Eastern North Atlantic Site by Jingjing Tian, Jennifer Comstock, Andrew Geiss, Peng Wu, Israel Silber, Damao Zhang, Parvathi Kooloth, Ya‐ Chien Feng

“…The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.…”
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U-Net-based VGG19 model for improved facial expression recognition by Xiaohu ZHAO, Jingyi ZHANG, Mingzhi JIAO, Lixun XIE, Lanfei WANG, Weiqing SUN, Di ZHANG

“…While maintaining the deep feature extraction capability of VGG19, which is well-regarded in the field, the model employs specially designed convolutional layers and skip connections. …”
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VFQB: A Novel Deep Learning Model for Rolling Bearing Fault Diagnosis by Zhiru Xiao, Yanfang Xu, Junjie Cui

“…To address this issue, we propose the VMD/FFT-Quadratic-BiGRU diagnostic model. First, the original vibration signals are processed with variational mode decomposition (VMD) and fast Fourier transform (FFT) and then stacked as quadratic neural network inputs. …”
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A Study of Analytical Solution for the Special Dissolution Rate Model of Rock Salt by Xin Yang, Xinrong Liu, Wanjun Zang, Zhiyong Lin, Qiyun Wang

“…By calculating the concentration distributions of rock salt solutions at the boundary layer, an ordinary differential equation for describing a special dissolution rate model of rock salt under the assumption of an instantaneous diffusion process was established to investigate the dissolution mechanism of rock salt under transient but stable conditions. …”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…This may cause some effective information to be mistaken for redundant information and discarded, which in turn causes object segmentation confusion. As a convolutional layer deepens, the loss of spatial detail information makes the segmentation effect achieved at the object boundary insufficiently accurate. …”
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Object Recognition and Positioning with Neural Networks: Single Ultrasonic Sensor Scanning Approach by Ahmet Karagoz, Gokhan Dindis

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MalFormer: A Novel Vision Transformer Model for Robust Malware Analysis by In-Woong Jeong, Han-Ju Lee, Gwang-Nam Kim, Seok-Hwan Choi

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Modeling of Electron Mobility of GaN at Low Temperature and Low Electric Field by Souradeep Chakrabarti, Shyamasree Gupta Chatterjee, Somnath Chatterjee

“…The discrepancy of this model above temperature 200 K presumably results from the following factors: ignoring the role of optical phonon, at low temperature consideration of parabolic band i.e. neglecting the effect of inter-velly scattering and ignoring the effect of very few interfacial charges in the degenerate layer at the GaN-substrate interface.…”
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End-to-End Multi-Modal Speaker Change Detection with Pre-Trained Models by Alymzhan Toleu, Gulmira Tolegen, Alexandr Pak, Jaxylykova Assel, Bagashar Zhumazhanov

“…The extracted features are fused and processed through a fully connected classification network, with layer normalization and dropout for stability and generalization. …”
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An Interpretable Weather Forecasting Model With Separately‐Learned Dynamics and Physics Neural Networks by Mengxuan Chen, Jinxiao Zhang, Runmin Dong, Yidan Xu, Haoyuan Liang, Juepeng Zheng, Lanning Wang, Haohuan Fu

“…Abstract Machine learning (ML) offers a promising alternative for weather forecasting by reducing computational costs and modeling complex non‐linear atmospheric processes. …”
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Ultimate Compression: Joint Method of Quantization and Tensor Decomposition for Compact Models on the Edge by Mohammed Alnemari, Nader Bagherzadeh

“…The process includes training floating-point models, applying tensor decomposition algorithms, binarizing the decomposed layers, and fine tuning the resulting models. …”
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Homeostatic synaptic normalization optimizes learning in network models of neural population codes by Jonathan Mayzel, Elad Schneidman

“…This ‘reshaping’ of projections is akin to changing synaptic connections in just one layer of the corresponding neural circuit model. …”
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Machine Learning‐Driven Surrogate Modeling for Optimization of Triboelectric Nanogenerator Design Parameters by Mohammad Abrar Uddin, Myeongju Lim, Rubiga Kim, Barrett London Burgess, Ken Roberts, Junghyun Kim, Taeil Kim

“…To address this problem, this study takes four process parameters such as thickness, pore ratio, applied force, and frequency into account and leverages advanced design methods (e.g., Design of Experiment) and machine learning‐based regression models to systematically explore the design space. …”
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An air target intention data extension and recognition model based on deep learning by Bo Cao, Qinghua Xing, Longyue Li, Weijie Lin

“…Second, the intention data generation model is built based on the denoising diffusion model, and the improved knowledge distillation method is applied to the denoising diffusion model to accelerate the sampling process of the model. …”
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TFTformer: A novel transformer based model for short-term load forecasting by Ahmad Ahmad, Xun Xiao, Huadong Mo, Daoyi Dong

“…A SHAP-based interpretability analysis, using surrogate models, is conducted to elucidate the decision-making process of TFTformer, highlighting the critical role of time factors and weather features in its predictions.…”
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A deep multiple self-supervised clustering model based on autoencoder networks by Ling Zhu, Zijin Liu, Guangyu Liu

“…Furthermore, to boost the efficiency of the multi-layer clustering module within our model and minimize algorithmic overhead, we integrate a distance-based Two-stage fuzzy C-Means clustering method. …”
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BERT-Residual Quantum Language Model Inspired by ODE Multi-Step Method by Shaohui Liang, Yingkui Wang, Shuxin Chen

“…Therefore, in this paper, we propose the BERT-Residual quantum language model inspired by the multi-step method of ordinary differential equations (ODE), using the density matrix to capture the semantic high-order interaction features missing in the BERT modeling process, and obtain the sentence representation, and perform the first step Residuals. …”
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