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KneeBones3Dify is a Python software tool that supports detailed analysis of knee pathologies and preoperative planning for knee replacement surgery based on patient-specific 3D models. It produces printable 3D bones in a stereolithography file format by automatically segmenting the femur, patella, and tibia from high-resolution Magnetic Resonance (MR) images with nearly isotropic voxel dimensions. Our software avoids time-consuming and subjective manual segmentation by specialists, offering an accurate and efficient alternative employing GPU acceleration. We validated the results by computing objective metrics against the ground truth voxel-wise segmentation produced for a 3D MR image by specialists, who also confirmed the reconstruction accuracy qualitatively. KneeBones3Dify and annotated data are publicly available, enabling broader research and clinical practice use.

Visualization is essential for interpreting data, especially in scientific research where datasets often come from experiments or simulations. Data visualization techniques vary based on the data type. For example, mapping can illustrate city traffic incidents, while bar plots can identify the most common incidents. This paper presents VisUAM (Visualizador UAM), a web-based tool for creating graphics from various datasets across any domain. The current version of VisUAM supports data from three scientific software tools: Pore Networks, Voronoi Diagrams, and Particle Diffusive Simulator. VisUAM’s architecture allows easy integration of any data type and supports multi-dimensional visualizations, including 2D, 3D, and animations. Its flexibility, web-based accessibility, and adaptability to new visualization needs make VisUAM a versatile and comprehensive platform for researchers.

The virtual Cross Array Task (CAT) is an educational platform designed to evaluate algorithmic thinking (AT) skills among students within Swiss compulsory education. This tool introduces an adaptable multi-interface system, enabling users to interact via intuitive gesture-based commands or through a visual programming interface that uses drag-and-drop blocks, facilitating a versatile approach to constructing and understanding algorithms. The platform encompasses a comprehensive training module for skill acquisition and a validation module for assessment. The system offers real-time feedback to users during activities, adjusting dynamically based on their actions, providing insights into progress and areas for improvement, thereby facilitating learning and performance enhancement. With multilingual capabilities extended to English, German, French, and Italian, the virtual CAT is intricately crafted to meet the diverse needs of educational contexts across various regions. Preliminary application and evaluation through a small-scale study indicate the virtual CAT’s potential to offer scalable assessment and a robust platform for integrating AT into broader educational and research methodologies, setting the stage for its integration into academic research and daily pedagogical practice.

Spectrep (Spectral Representation) implements a text representation framework for obtaining a multi-view representation that consolidates lexical, syntactic, and semantic features by structuring a workflow with popular text processing tools such as NTLK, Gensim, and Self-Organizing Maps. This framework is intended to be used in text pre-processing for its application in more robust machine learning applications. This software is open-source and implemented in Python. It has been successfully tested with several tasks to prove its functionality.

The application of pruning techniques to convolutional neural networks has made it possible to reduce the size of the model and the time required for inference. However, determining the best pruning policy, i.e. the pair of pruning method and pruning distribution that allows obtaining the highest accuracy or F1 score of the pruned model, is not a task that can be easily performed with the available tools. For this, we propose a library called FlexiPrune, written in Python language and using the Pytorch framework, which allows the user to select an unpruned model and choose the pruning policy from a set of available options. FlexiPrune makes it very easy to compare the impact of different pruning methods and pruning distributions, so that decision making is based on the performance of the pruned model for the specific GPR (Global Pruning Rate) value and classification problem, rather than simply following generic pruning policy recommendations.

UCO DWM1001 is a free software developed to facilitate the work with DWM1001-DEV, one of the most widely used ultra-wideband (UWB) development boards. The software is designed to process, display, and store the relevant information of a UWB network system. The developed tool enables the user to manage the device transparently, establishing a connection, managing communication, and providing a range of features that facilitate the work and study of UWB technology. Communication is based on terminal emulation, whereby received messages are processed in accordance with their properties, the operating mode set, or the application tool used. The software's principal functions comprise real-time data visualisation, data saving, and an integrated terminal emulator for direct communication with the DWM1001-DEV development board. The tool, developed using the Qt framework, is intended to provide researchers with a straightforward method to utilise and assess the performance of DWM1001-DEV in diverse indoor settings, as well as to construct a basic UWB positioning network. Two illustrative examples are presented to demonstrate the capabilities of UCO DWM1001 software.

This study introduces XCompress, a Python-based tool for effectively utilizing various compression algorithms. XCompress offers manual, brute force, and Large Language Model (LLM) methods to determine the most suitable algorithm based on the type of text data. Its modular structure allows easy addition of new algorithms and includes functions for benchmarking and result comparison. Tests on diverse text types demonstrate the efficacy of the LLM-assisted Compression Selection Model (CSM). With XCompress, users can determine the most suitable method for their files. Additionally, in academic research, they can easily compare different methods without needing any scripting or programming language.

Record linkage algorithms require testing on realistic personal identification data to assess their efficacy in real-world settings. Access to this kind of data is often infeasible due to rigid data privacy regulations. Open-source tools for generating realistic data are either unmaintained or lack performance to scale to the generation of millions of records. We introduce Gecko as a Python library for creating shareable scripts to generate and mutate realistic personal data. Built on top of popular data science libraries in Python, it greatly facilitates integration into existing workflows. Benchmarks are provided to prove the library’s performance and scalability claims.

To enhances the security, usability, and intelligence of knowledge management software, this paper develops a novel knowledge management application built upon the Electron cross-platform desktop development framework, Vue JavaScript Framework, and large language models. The software boasts distributed deployment, multi-view information management, and intelligent interaction capabilities. Through distributed deployment, it diversifies the sharing format of information within organizations, effectively addressing conflicts between data security and sharing. The multi-view functionality improves the effectiveness of knowledge presentation, while the large language model facilitates intelligent and natural knowledge querying and application. Finally, illustrative examples from diverse domains such as project management, education, and military applications are utilized to demonstrate the practical utility of the software. Users can significantly enhance the integration and intelligence of knowledge management through this software.