Principles of flexibility demand in different directions. by Tianhe Sun (21145341)

Subjects:

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…<p dir="ltr">The main focus of this thesis is to develop appropriate morphology modelling strategies for typical deformable structures by integrating physics-aligned prior knowledge and deep learning algorithms. To perform accurate control for soft continuum robots, a reinforcement-learning (RL)-based framework is proposed, which integrates conventional piecewise curvature constant (PCC) model and adaptive learning strategies. …”

(a). Comparison of Translation Accuracy. by Na Wang (193263)

Model code by Waltraud Schulze (20695250)

“…The latter provides insights into the inherent texture complexity of the image data due to the lossless coding. For classification of leaf surfaces from tree species based on the computed features, we utilized the k-nearest neighbors (kNN) algorithm with k=3. …”

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Data Sheet 1_Strategies for population-level identification of post-acute sequelae of COVID-19 through health administrative data.pdf by Cristina Mazzali (22090328)

“…From each included study, we extracted data on design, algorithms used for outcome identification (sources, coding systems, codes, time criteria/thresholds), and whether significant associations with SARS-CoV-2 infection were reported.…”

Code snippet from “Apache Dubbo” GitHub project. by Matthew Yit Hang Yeow (20721206)

“…Our approach uses cross-project code clone detection to establish the ground truth for software reuse, identifying code clones across popular GitHub projects as indicators of potential reuse candidates. …”

Dataset for 'An Automated Workflow of Deep Learning Ensemble Model with Principal Component Analysis for Enhanced Material Characterisation in Energy Dispersive Spectroscopy' by Fanzhi Su (21005174)

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…At the beginning of the code, there is a help section that explains how to use it.…”

Visualization of algorithm detection results. by Xinpeng Yao (18882573)

“…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …”

An overview of the organization of the study program. by Marialuisa Gandolfi (8639238)

Subjects:

Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. by Marialuisa Gandolfi (8639238)

Subjects:

The schedule of enrolment, interventions, and assessments. by Marialuisa Gandolfi (8639238)

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Parameters of stimuli used in the study. by Elnaz Nemati (21402730)

“…<div><p>This study introduces a neurobiologically inspired computational model based on the predictive coding algorithm, providing insights into coherent motion detection processes. …”

CSSI Elements: Multi-GPU and Network Modeling and Simulation in SST by Kishwar Ahmed (21792083)

Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

Zero-Shot Discovery of High-Performance, Low-Cost Organic Battery Materials Using Machine Learning by Jaehyun Park (2402962)

“…We demonstrate that SPARKLE significantly outperforms alternative black-box machine learning algorithms on interpolation and extrapolation tasks. …”

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Vibration Nondestructive Testing of Continuous Welded Rails: A Finite Element Analysis by Alireza Enshaeian (20360253)

“…The frequency content of the vibrations below 700 Hz and across a range of different longitudinal stress and support conditions is computed using the power spectral density, which constitutes the input matrix of a machine learning algorithm able to learn the complex relationship among frequencies, axial stress, and support conditions. …”

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone by Michael J. Pasterski (11726741)

“…We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithmsk-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. …”