Determination of cyclic behavior of various cross-section composite column-beam connections reinforced with FRP composite using FEM analysis and ML models by Yasemin Simsek Turker (22340676)

“…Mean learning (XGBoost and the random forest algorithm) and numerical methods were used to identify the data collected experimentally due to the rotation behavior. …”

List of the time used by each algorithm. by JiaMing Gong (20427837)

“…To this end, this paper proposes an entropy-based dynamic ensemble classification algorithm (EDAC) to consider data streams with class imbalance and concept drift simultaneously. …”

Sanitized databases using MLHProtector algorithm. by Loan T. T. Nguyen (20660789)

“…<div><p>Privacy is as a critical issue in the age of data. Organizations and corporations who publicly share their data always have a major concern that their sensitive information may be leaked or extracted by rivals or attackers using data miners. …”

ML algorithms used in this study. by Toheeb Salahudeen (21368040)

Notations and definitions used in the algorithm. by Nazym Alimbekova (22766158)

Data augmentation is applied both geometrically and in terms of intensity. Geometrically, the images are mirrored, flipped, rotated, and randomly cropped. For intensity augmentatio... by Yide Di (20969124)

The flowchart of GWO-VMD method. by Zhenjing Yao (22189970)

“…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Implementation of TIPC, a computational method utilizing hexagonal tessellation and a classifier that evaluates multiple spatial parameters against a tumor region-specific null mod... by Mai Chan Lau (3135303)

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Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”

Model’s measure methods. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

Description of the dataset used for the machine learning algorithm. by Tri Ngo Quang (20390189)

Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4 by Berith Atemoztli De la Cruz Sánchez (21758708)

“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”

Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025) by Brian Bockelman (5128082)

Three-Dimensional Afterglow Luminescence–MRI Fusion Tomography with Magnetically Targeted Luminescent-Magnetic Nanoparticles for Deep-Seated Tumor Imaging by Ying Zhang (40767)

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The mAP for all algorithms and 80% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 80% of the data used for training.</p>…”

The mAP for all algorithms and 50% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 50% of the data used for training.</p>…”

The mAP for all algorithms and 60% of the data used for training. by Mohammad Amin Fraiwan (20469541)

“…<p>The mAP for all algorithms and 60% of the data used for training.</p>…”

Point cloud data registration using the original ICP algorithm. by Mengyuan Yan (14200322)

“…<p>Point cloud data registration using the original ICP algorithm.…”

Summary of key parameters used in the CSCAP algorithm. by Manxing Shi (22367181)

Features selection using the Boruta algorithm. by Nishat Tasnim Thity (21755858)

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