Screenshot showing the basic starting Nomogen’s code structure. by Trevor Blight (20685529)

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Nomogram for determining the average interest for a range of years going from 5 to 20. by Trevor Blight (20685529)

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Nomogram for the variables <i>u</i>, <i>v</i>, and <i>w</i> that satisfies the Eq 1. by Trevor Blight (20685529)

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Nomogram for determining the geometric burden in blast design. by Trevor Blight (20685529)

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Mean and standard deviation of the survey answers. by Trevor Blight (20685529)

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Variables in the Eq 4 for two retaining walls. by Trevor Blight (20685529)

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Nomogram for determining the hydrocyclone apex diameter in mining engineering studies. by Trevor Blight (20685529)

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Example nomogram for deriving the hydraulic radius of a circular section. by Trevor Blight (20685529)

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Diagram showing the 5-step approach to assess the student perceived importance of nomograms in academic context. by Trevor Blight (20685529)

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Investigating the far-right online: Using text data to understand online subcultures by L Brace (18374691)

“…While these analytical techniques are new, they are actually fairly easy for social researchers to implement due to the nature of contemporary high-level programming languages such as Python.…”

Mushroom Classification Using Support Vector Machines (SVM) Focusing on Cap Features. by Gabriel Minato (22462099)

“…The predictor variables were</p><p dir="ltr">20 pre-processed features of the mushroom cap, and the target variable was the mushroom's class</p><p dir="ltr">(edible 'e' or poisonous 'p'). The tools used were the Python programming language and its</p><p dir="ltr">libraries, primarily Scikit-learn to build and optimize the SVM classifier. …”

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by Pierre-Alexis DELAROCHE (22092572)

Deciphering pseudouridylation profiles and their biogenesis from deep sequencing data using psiFinder by zhirong chen (20863529)

Core-Based Smart Sampling Framework: A Theoretical and Experimental Study on Randomized Partitioning for SAT Problems by DURGHAM QARALLEH (21904172)

“…We provide theoretical guarantees on complexity reduction and probabilistic completeness, apply the method to SAT instances, and evaluate its performance using experimental Python implementations. The results show that smart sampling drastically reduces the effective complexity of SAT problems and offers new insights into the structure of NP-complete problems.…”

A free tutorial book from NSF Cybertraining C2D: Cybertraining for Chemical Data scientists by Xiangliang Zhang (19460047)

“…In the following chapters, 4 through 9, we focus on specific chemical tasks, dedicating each chapter to solving a distinct problem using these machine learning techniques, including molecular property prediction, molecular optimization, reaction outcome prediction, retrosynthesis, yield prediction and Large Language Models (LLMs) for Chemistry. …”

The Twin Prime Conjecture: Collapse-Band Parity Cancellation and Operator Proof by Jennifer Bulyaki (22283308)

Data Sheet 1_The development and use of data warehousing in clinical settings: a scoping review.pdf by Shiyang Lyu (20910008)

“…We searched four databases (PubMed, CINAHL, Scopus and IEEE-Xplore), identifying peer-reviewed, English-language studies from 1st January 2014 to 1st January 2024, that focus on data warehousing in healthcare, covering either general or specialised data warehouse applications. Python programming was used to extract the search results and transform the data into a tabular format for analysis.…”

Complex Eigenvalues, Orthogonality, and QR Factorization: Analytical Proofs and Numerical Verification by Umar Tabbsum (22058780)

“…These results are then validated through computational experiments using Python with the NumPy and SciPy libraries.</p><p dir="ltr">Key computational techniques include:</p><ol><li>Eigenvalue and Eigenvector Computation: Generation of random Hermitian matrices and computation of their eigenvalues and eigenvectors. …”

Affinity Molecular Assay for Detecting Candida albicans Using Chitin Affinity and RPA-CRISPR/Cas12a by Deqiang Wang (19817560)

“…Raw reads were obtained from Tsingke Biotechnology (Beijing, China) and analyzed using Python scripts (Python 3.11.8), filtering reads with an average Phred quality (Q score) of at least 25. …”

<b>MSLU-100K: A multi-source land use dataset of Chinese major cities</b> by Yao Yao (7903457)

“…<p dir="ltr">The project includes the code of a deep learning model related to the paper "MSLU-100K: A Multi-Source Land Use Dataset for Major Cities in China". This paper presents a model for classifying irregular land parcels by land use. …”