Velocity-Constraint Kalman Filtering for Enhanced Bubble Tracking in Motion-Compensated Ultrasound Localization Microscopy by Yifei Zhu, Lingyin Jiang, Qi Zhang, Jun Yin, Bingze Du, Guofeng Zhang, Haijun Zhang, Bo Ding, Han Lin, Honghui Xue, Xiasheng Guo, Xiao-Yang Zhang, Jing-Ning Zhu, Dong Zhang, Juan Tu, Ning Gu

“…Unlike traditional methods relying on observed bubble positions, the proposed algorithm combined statistical information derived from historical data with Kalman-filter-predicted positions to enable more accurate bubble localization. …”
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Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis by Minsung Kim, Taeyong Park, Jaewoong Kang, Min-Jeong Kim, Mi Jung Kwon, Bo Young Oh, Jong Wan Kim, Sangook Ha, Won Seok Yang, Bum-Joo Cho, Iltae Son

“…It was analysed using a two-stage binary algorithm with transfer learning. The algorithm predicted three categories: non-, simple, and complicated appendicitis. …”
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The RESOLVE and ECO Gas in Galaxy Groups Initiative: The Group Finder and the Group H i–Halo Mass Relation by Zackary L. Hutchens, Sheila J. Kannappan, Andreas A. Berlind, Mehnaaz Asad, Kathleen D. Eckert, David V. Stark, Derrick S. Carr, Ella R. Castelloe, Andrew J. Baker, Kelley M. Hess, Amanda J. Moffett, Mark A. Norris, Darren Croton

“…We discuss interesting tensions with theoretical predictions and prior measurements of the M _H I,grp – M _halo relation. …”
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TraxVBF: A hybrid transformer-xLSTM framework for EMG signal processing and assistive technology development in rehabilitation by Seyyed Ali Zendehbad, Athena Sharifi Razavi, Marzieh Allami Sanjani, Zahra Sedaghat, Saleh Lashkari

“…This allows the model to predict movement trajectories accurately, enabling motor learning and functional recovery of patients through real time feedback without the expensive hardware. …”
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A statistical method for high-throughput emergence rate calculation for soybean breeding plots based on field phenotypic characteristics by Yan Sun, Mengqi Li, Meiling Liu, Jingyi Zhang, Yingli Cao, Xue Ao

“…Secondly, the deep learning object detection model was used to infer and predict the processed images to label soybean seedlings. …”
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Riparian habitat quality and seasonality drives spatiotemporal habitat ecology of sympatric Asian otters in southern Western Ghats by Ankit Moun, Tharmalingam Ramesh, Tharmalingam Ramesh, Riddhika Kalle, Riddhika Kalle

“…The low-quality habitat with low sign encounter rates or no evidence of otters had anthropized stream buffers, with high proportion of agriculture, weed cover and anthropogenic disturbance as influential factors predicted by the RF algorithm. SCO distribution was restricted to the higher-order streams in close proximity to hydro-power dams. …”
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Self-Driving Car Navigation With Single-Beam LiDAR and Neural Networks Using JavaScript by Trung Thi Hoa Trang Nguyen, Thanh Toan Dao, Thanh Binh Ngo, Vu Anh Phi

“…The proposed neural network architecture, consisting of four output neurons, processes data from ten distinct angular measurements of the LiDAR sensor to predict necessary steering and speed adjustments for autonomous navigation. …”
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Rules-Based Energy Management System for an EV Charging Station Nanogrid: A Stochastic Analysis by Gabriel Henrique Danielsson, Leonardo Nogueira Fontoura da Silva, Joelson Lopes da Paixão, Alzenira da Rosa Abaide, Nelson Knak Neto

“…The methodology includes forecasting models based on an Artificial Neural Network for photovoltaic generation, a parametric estimation for wind generation, and a Monte Carlo simulation to predict the energy consumption of electric vehicles. …”
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The Interconnection Between Pharmaceutical Development and Preclinical Research (Review) by I. N. Ampilogova, M. V. Karlina, V. G. Makarov, M. N. Makarova

“…Pharmaceutical development of an innovative highly effective and competitive drug is a long and expensive process, the result of which is quite difficult to predict in advance. To speed up the entry of a new drug to the treatment and reduce the developer's material costs, it is advisable to include preclinical experiments in the process of creating a drug.Text. …”
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Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

“…The final results of the detected lighting fixtures to the raw point cloud data are validated by using F1-score and IoU to determine the accuracy of the predicted object classification and the positions of the detected fixtures. …”
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Inland wetlands mapping and vulnerability assessment using an integrated geographic information system and remote sensing techniques by C.E. Akumu, J. Henry, T. Gala, S. Dennis, C. Reddy, F. Tegegne, S. Haile, R.S. Archer

“…A weighted geospatial vulnerability analysis was developed using variables such as roads, land cover/ land use (developed and agricultural areas) and climate data (temperature) to predict potentially vulnerable inland wetland types. …”
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Ship Hull Steel Plate Deformation Modeling Based on Gaussian Process Regression by Zhiliang Zhang, Ryojun Ikeura, Soichiro Hayakawa, Zheng Wang

“…In this study, a steel plate model is established by the Gaussian regression method, which can predict the steel plate deformation according to the selected steel plate material, size and thickness, heating temperature, and heating position. …”
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B-value Based Damage Source Localization and Classification Using Acoustic Emission (AE) Data for Concrete Cylinders Wrapped with Hybrid FRCM Composites by Nikhil Holsamudrkar, Sauvik Banerjee

“…Whereas, spatial b-value-based damage localization, implemented using a wrapped cylinder algorithm, accurately predicts severe damage locations. …”
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MSaD-Net: A Mix Self-Attention Networks for 3D Point Cloud Denoising by Xusheng Zhu, Shuai Ma, Daixin Chen, Li Zhou, Haibo Tang

“…However, most of the existing methods adopt a pointnet-like structure to predict point offsets. Simple pooling operation loses much important information, such as local neighborhood information, and global information. …”
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Hazard analysis of future surface displacements on active faults based on the recurrence interval of strong earthquakes by Zhou Qingyun, Liu Jingnan, Tian Peng, Luo Weidong, Bai Xianfu, Yang Yue, Zou Zhenyu

“…The results indicate that the predicted future surface displacements using our method are greater than the true displacements of seismic events. …”
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Machine learning based multi-parameter droplet optimisation model study by Ting Li, Likun Lu, Qingtao Zeng, Kexin Liao

“…Moreover, the Pareto solution of the 10 sets of predicted parameters output using the BO-GP method tends to be stable with fluctuations around 0.1, and it takes only 1 h to derive the control conditions for achieving high roundness, high yield and uniform size droplets.…”
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On Detection of Sybil Attack in Large-Scale VANETs Using Spider-Monkey Technique by Celestine Iwendi, Mueen Uddin, James A. Ansere, P. Nkurunziza, J. H. Anajemba, Ali Kashif Bashir

“…An artificial spider-monkey technique is used to examine the Sybil attacking strategies on VANETs to predict the number of vehicular collisions in a densely deployed challenge zone. …”
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Experimental Demonstration of 73 Gb/s QPSK and 150 Gb/s QAM-32 Wireless Data Links in the Sub-THz Band Through Frequency Selective Surface Filters by Walter Fuscaldo, Daniele Pirrone, Dimitrios C. Zografopoulos, Antonio Ferraro, Pascal Szriftgiser, Guillaume Ducournau, Romeo Beccherelli

“…Measurement results for the EVM are predicted through an innovative use of the k-means algorithm which is here suitably modified to deal with FSS-based communications. …”
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Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study by C. Banerjee, K. Nguyen, C. Fookes, G. Hancock, T. Coulthard

“…The IMC process substantially improves the agreement between CL predictions and observed data (in the context of gully catchment landscape evolution), surpassing both uncalibrated and manual approaches.…”
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Rheological changes in melts and magmas induced by crystallization and strain rate by Vetere, Francesco, Iezzi, Gianluca, Perugini, Diego, Holtz, Francois

“…This highlights the fact that a general experimental protocol is needed in order to compare and model viscosity data to predict the dynamic rheological evolution for volcanic rocks.…”
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