21 papers · ranked by Valyu relevance
Stephen Coshatt, He Yang, Shushan Wu, Jin Ye + 5 more
As machine learning and artificial intelligence are being integrated into cyber-physical systems, it is becoming important for engineers to know and understand these topics. In particular, sensor data is on the rise in these systems and therefore engineers need to understand which models are appropriate to time-series…
Cassandra Lucas, Anshul Bihani, Rohini Kukka, Chun-Hua Tsai + 2 more
Generative AI creates new opportunities for programming education, but many existing systems remain overly directive, producing lengthy explanations and premature solutions that can overwhelm K-12 novices. In this paper, we present a participatory design study of how an adaptive tutorial system, SocratiCode, evolved…
Fabrice Bauget, Adama Ndour, Yann Boursiac, Christophe Maurel + 3 more
Drought is a significant factor in agricultural losses, making it imperative to understand how root system architecture (RSA) adapts to environmental condition like water deficit. HydroRoot is a functional-structural plant model (FSPM) aimed at analyzing and simulating hydraulic and solute transport of RSA. The model…
Jesse Yusuf Chan, Haoming Wang, Mingwei Xu, Xianlong Xu
The transition from block-based to text-based programming requires learners to convert visible program structures into abstract textual expressions, which may create a cognitive gap between understanding computational concepts and expressing them in Python syntax. To support this transition, we designed and implemented…
Haley Schuhl, Keely E. Brown, Hudanyun Sheng, Parag K. Bhatt + 58 more
PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data and the newest release, PlantCV version 4, continues to lower the barrier to entry for users…
Matteo De Matola, Giorgio Arcara
Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come…
Julie R. Pivin-Bachler, Egon L. van den Broek
Title: Summary Machine learning struggles with imbalanced data. Although several mitigation approaches exist, their application depends on the extent of imbalance. To determine the latter, a protocol was developed. Across 428 synthetic and 70 real datasets, 8 imbalance measures were benchmarked and evaluated using…
Authors not listed
TurtleMol is an open-source Python package that aims to help users generate large, complex molec- ular systems. In the current version, users can generate systems by filling volumes defined by basic geometric shapes (e.g. cube, sphere), or by shapes of arbitrary gemoetries defined meshes created in other software (such…
Rajshekhar Sunderraman
The functional programming paradigm has a long and storied history with its beginnings in the Lambda Calculus. In recent decades, pure functional languages such as Haskell have been shown to be highly effective in producing robust software due to immutable data structures among other functional features. The advantages…
Han Zhang, John Jonides
We present PupEyes, an open-source Python package for preprocessing and visualizing pupil size and fixation data. PupEyes supports data collected from EyeLink and Tobii eye-trackers as well as any generic dataset that conforms to minimal formatting standards. Developed with current best practices, PupEyes provides a…
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We present an open source collection of scripts and programs for the setup, management and evaluation of calculations with the Vienna ab-initio simulation package (VASP), called utils4VASP. It contains 20 independent Python scripts and Fortran programs, all with a unified and intuitive handling concept based on command…
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With the rapid growth of chemical data and information, there is an increasing need for chemistry undergraduates to master Python tools for analyzing large chemical datasets and extracting key or feature information. Currently, more than 100,000 types of metal-organic frameworks (MOFs), as the material recently awarded…
Endre Bakken Stovner, Max Ticó, Ester Muñoz del Campo, Joan Pallarès-Albanell + 3 more
Sequence interval algebra is key to modern bioinformatics. Pyranges v1 offers a Python Pandas-based interface to a comprehensive palette of Rust-powered operations (e.g., overlap, count, slice intervals), enabling the intuitive development of efficient pipelines for diverse sequence data, including gene annotations…
Gino Carmona-Díaz, William Jiménez-Leal, María Alejandra Grisales, Chandra Sripada + 3 more
Analyzing texts such as open-ended responses, headlines, or social media posts is a time- and labor-intensive process highly susceptible to bias. However, large language models (LLMs) are promising tools for text analysis, using either a predefined (top-down) or a data-driven (bottom-up) taxonomy, without sacrificing…
Zechen Bai, Zhiheng Chen, Yiqi Lin, Kevin Qinghong Lin + 4 more
Human experience in digital environments offers a vast, underexplored resource of authentic, untrimmed interactions that contain rich procedural knowledge. We introduce Demo2Tutorial, a framework that transforms this experience captured via screen recordings and interaction logs into structured, multimodal software…
Jaka Kokošar, Ela Praznik, Martin Špendl, Nancy P. Moreno + 4 more
In biomedicine, survival analysis addresses time-to-event data to study outcomes like patient survival and treatment response, and supports biomarker discovery. Yet, teaching this analysis is often hindered by mathematical and programming barriers. We present a structured, hands-on tutorial that goes beyond a typical…
Robert M. Salati, Geng Li, Spencer Williams, Benjamin J. Fregly
Personalized computational neuromusculoskeletal models have great potential for optimizing the design of clinical treatments for movement impairments. While many software tools address specific parts of the model personalization and treatment optimization processes, they typically require significant programming…
Antonios Saravanos, John Pazarzis, Stavros Zervoudakis, Dongnanzi Zheng
Python libraries often need to maintain a stable public API even as internal implementations evolve, gain new backends, or depend on heavy optional libraries. In Python, where internal objects are easy to inspect and import, users can come to rely on "reachable internals" that were never intended to be public, making…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Authors not listed
Computational methods for predictive modeling have been increasingly utilized in the early stages of drug discovery to supplement high-throughput screening. The advent of highly efficient and complex machine learning architectures necessitates new methods of collating the plethora of topological, geometrical, and…
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Mass spectrometry (MS) generates large datasets that are stored in increasingly optimized and complex file types, demanding technical expertise to extract information rapidly and easily. We wondered whether a simple structured query language (SQL) database could hold raw MS data and allow for easily readable queries…