Pose errors of 5PUS-RPUR robot with different algorithms. by Zesheng Wang (15244172)

Parameters of joint significance test. by Yixuan Lu (9987980)

Non-linear/linear energy conversion curve. by Pingxin Wang (16747662)

Stress and frequency optimization of prismatic sandwich beams with structural joints: Improvements through accelerated topology optimization by Shengyu Yan (21450735)

“…Although they resemble conventional beams, optimized core topologies with joints highlight additional improvements and underscore the importance of joint design in optimization. …”

Overview of the segmentation algorithm. by Michael C. Robitaille (11949174)

Flow diagram of the reachable workspace. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

Size parameters of the 5PUS-RPUR parallel robot. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

Structure diagram of branched PUS with errors. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

PK subproblem 3. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

The two recognized basic PK sub-problems. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

Structure diagram of branched RPUR with errors. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

5PUS-RPUR parallel robot system. by Zesheng Wang (15244172)

“…Based on measurement data from an onboard IMU and joint encoders, the identification results are obtained. …”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…To address this, the research integrates a modified A* pathfinding algorithm with a U-Net convolutional neural network, a custom statistical binary classification method, and a personalized Min-Max connectivity threshold to automate the detection of astrocyte connectivity.…”

Table_1_Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning.DOCX by Nina de Lacy (6559520)

“…We apply IEL to three gold standard machine learning algorithms in challenging, heterogenous biobehavioral data: deep learning with artificial neural networks, decision tree-based techniques and baseline linear models. …”

Table_2_Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning.DOCX by Nina de Lacy (6559520)

“…We apply IEL to three gold standard machine learning algorithms in challenging, heterogenous biobehavioral data: deep learning with artificial neural networks, decision tree-based techniques and baseline linear models. …”

Table_1_Probabilistic Optimal Power Flow Calculation Method Based on Adaptive Diffusion Kernel Density Estimation.docx by Guoqing Li (23674)

“…<p>To accurately evaluate the influence of the uncertainty and correlation of photovoltaic (PV) output and load on the running state of power system, a probabilistic optimal power flow (POPF) calculation method based on adaptive diffusion kernel density estimation is proposed in this paper. …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Table_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.docx by Qi Wan (271320)

“…</p>Conclusions<p>After algorithm optimization, 2D feature-based radiomics models yield favorable results in differentiating malignant and benign SPLs, but 3D features are still preferred because of the availability of more machine learning algorithmic combinations with better performance. …”

A. Top – 14 days of continuous glucose monitor (CGM) data for a patient that spends all of their time within an optimal glucose range. by Jamison H. Burks (21029607)

DataSheet_2_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv by Qi Wan (271320)

“…</p>Conclusions<p>After algorithm optimization, 2D feature-based radiomics models yield favorable results in differentiating malignant and benign SPLs, but 3D features are still preferred because of the availability of more machine learning algorithmic combinations with better performance. …”