Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx by Yanfen Zheng (3814507)

“…In this study, we describe an enhanced gradient-based optimizer that includes the Cauchy and Levy mutation strategy (CLGBO) to construct DNA coding sets, which are used as primer and address libraries. …”

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

“…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

“…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”

Priority rule-based heuristics for distributed multi-project scheduling considering global resource failures by Xuejun Hu (2003440)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Fig 3 - by Ali Ahmed (2567584)

Sample image for illustration. by Indhumathi S. (19173013)

“…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”

Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

“…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

“…The image is then cleaned in c) using morphological filtering with an <i>opening</i> operation to remove small-scale noise. …”

Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

Comparison analysis of computation time. by Indhumathi S. (19173013)

“…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”

Process flow diagram of CBFD. by Indhumathi S. (19173013)

“…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”

Precision recall curve. by Indhumathi S. (19173013)

“…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”