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ChestVolume: An R package and shiny app for analyzing chest expansion using 3D coordinate data

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2025.102040

Patrick Wai-Hang Kwong , Eng Keong Lua , Clive Ho-Yin Wong , Allan Chak-Lun Fu , Fadi Mohammad Al Zoubi , Sharon Man-Ha Tsang

ChestVolume is an R package and Shiny web application developed to facilitate the analysis of chest expansion using three-dimensional (3D) coordinate data obtained from optical motion capture systems. This software provides an end-to-end solution for respiratory analysis, including data preprocessing, marker position adjustment, volume calculation, and interactive visualization. The package includes functions for reformating marker data, adjusting marker positions, and calculating chest segment volumes using convex hull algorithms. Visualization tools allow users to explore chest expansion across time, providing a dynamic view of respiratory motion. The interactive Shiny app integrated with ChestVolume offers a user-friendly interface for individuals without advanced programming expertise, making chest volume analysis accessible to a wider audience. Users can upload 3D motion capture data, define custom chest segments, select specific time ranges, and visualize chest expansion patterns in both static and animated formats. These features enable researchers and clinicians to assess regional chest expansion and detect asymmetries in respiratory motion, which are crucial for understanding respiratory mechanics and evaluating conditions such as chronic obstructive pulmonary disease and spinal deformities. ChestVolume advances respiratory health research by providing an open-source, customizable, and accessible tool for the quantitative assessment of chest wall movement. The package supports personalized rehabilitation strategies by enabling the identification of asymmetric respiratory motion, facilitating targeted interventions to improve respiratory function, and ultimately contributing to enhanced clinical assessments and health outcomes.

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引用次数: 0

HISAPS: High-order smoothing spline with automatic parameter selection and shape constraints

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2025.102049

Peter H. Broberg , Esben Lindgaard , Asbjørn M. Olesen , Simon M. Jensen , Niklas K.K. Stagsted , Rasmus L. Bjerg , Riccardo Grosselle , Iñigo Urcelay Oca , Brian L.V. Bak

Obtaining a good functional fit with noisy data is difficult. This is especially true when the derivative of the fitted function is needed, which is often the case in engineering applications. One solution is to use smoothing splines. However, most conventional and readily available smoothing spline software implementations are cubic with a penalty on the 2nd order derivative, which results in poor and sometimes noisy derivatives. In this paper, we present new software that can be used to make smoothing splines with a penalty on the 1st, 2nd, 3rd, or 4th order derivatives. Furthermore, the presented software allows for applying constraints to the function to impose prior knowledge, including automatic parameter selection through cross-validation for an optimum and user-independent fit.

引用次数: 0

Code-Review-as-an-Educational-Service: A tool for Java code review in programming education

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2025.102048

Matthew Beattie, Moira Watson, Desmond Greer, Bee-Yen Toh, Zheng Li

High-quality source code is the foundation of successful and sustainable software development, while code review plays a crucial role in ensuring code quality. We place a special emphasis on the educational application of code review, aiming to assist novice students who are entry-level programmers establish industry-standard programming practices while reducing the likelihood of vulnerabilities and technical debt. Given that existing code review tools often require complex setups and are designed for large-scale, enterprise-level software projects, we advocate for the development of an easy-to-use, zero-configuration, and lightweight tool that is specifically tailored to the needs of educational environments. This paper reports our development of such a cloud-native code review tool as an educational service. Although still at the proof-of-concept stage, our internal and preliminary assessment has confirmed the promising usability and usefulness of this tool both for students (e.g., self-reviewing an individual exercise) and for educators (e.g., examining cohort exercises and prioritising teaching materials). By integrating this tool into our innovative project Automating Programming Education in Java, we believe that such an educational service would be able to make contributions to faster maturation of programming skills in students.

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引用次数: 0

Timeseria: An object-oriented time series processing library

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2025.102036

Stefano Alberto Russo , Giuliano Taffoni , Luca Bortolussi

Timeseria is an object-oriented time series processing library implemented in Python, which aims at making it easier to manipulate time series data and to build statistical and machine learning models on top of it. Unlike common data analysis frameworks, it builds up from well defined and reusable logical units (objects), which can be easily combined together in order to ensure a high level of consistency. Thanks to this approach, Timeseria can address by design several non-trivial issues which are often underestimated, such as handling data losses, non-uniform sampling rates, differences between aggregated data and punctual observations, time zones, daylight saving times, and more. Timeseria comes with a comprehensive set of base data structures, data transformations for resampling and aggregation, common data manipulation operations, and extensible models for data reconstruction, forecasting and anomaly detection. It also integrates a fully featured, interactive plotting engine capable of handling even millions of data points.

引用次数: 0

MIMOSNN: Software implementation for MIMO sampling neural network

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2024.102017

Lingyan Wu , Gang Cai

This is a software tool that provides the program implementation for MIMO Sampling Neural Network (SNN) and Wide Learning. MIMO SNN is a novel neural network that combines SISO SNN with SLFNs structure to fill the gap of SISO SNN and trains the neurons with trainable activation functions in SISO SNN instead of weights. Wide Learning is an extended algorithm of MIMO SNN and trains the network by adding and updating the new neurons. The experimental results show that the algorithm has good accuracy and convergence features. The software is beneficial to expand the application prospect of the algorithm in instant training, self-growth, big data, and other aspects.

引用次数: 0

PyDicer: An open-source python library for conversion and analysis of radiotherapy DICOM data

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2024.102010

Phillip Chlap , Daniel Al Mouiee , Robert N Finnegan , Janet Cui , Vicky Chin , Shrikant Deshpande , Lois Holloway

The organisation, conversion, cleaning and processing of DICOM data is an ongoing challenge across medical image analysis research projects. PyDicer (PYthon Dicom Image ConvertER) was created as a generalisable tool for use across a variety of radiotherapy research projects. This includes the conversion of DICOM objects into a standardised form as well as functionality to visualise, clean and analyse the converted data. The generalisability of PyDicer has been demonstrated by its use across a range of projects including the analysis of radiotherapy dose metrics and radiomics features as well as auto-segmentation training, inference and validation.

引用次数: 0

microStabilize: In-plane microstructure stabilization in optical microscopy via normalized correlation coefficient matching method

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2025.102065

Marek Grzegorz Mikulicz

In this work, an automatic vision-guided accurate positioning of a microstructure in an optical microscope is presented. Microscopes for near-infrared spectroscopy are using actuators with micrometer and nanometer precision to investigate semiconductor nanostructures. The cryostats used to cool down the structures and other mechanical elements are an inevitable source of vibrations and sample drift in the optical setup. This is one of the challenges of long-term experiments in obtaining reliable data that require excitation and detection from the same spot on the sample. Consequently, the need for setup design and software that utilizes active stabilization of a sample position has emerged. Presented Python-based software with GUI utilizes the normalized correlation coefficient matching method from the openCV library to localize microstructure and automatically compensate for any misalignment with pixel accuracy and

0.2 μ m

precision in real-time.

引用次数: 0

Odatix: An open-source design automation toolbox for FPGA/ASIC implementation

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2024.101970

Jonathan Saussereau, Christophe Jego, Camille Leroux, Jean-Baptiste Begueret

In modern hardware digital design, optimizing performance, resource utilization, and power consumption across different technological targets remains a critical challenge. Indeed, the drive for greater computational power, alongside the need to reduce power consumption, stems from a wide range of applications, from data centers to mobile devices. However, this push encounters significant cost barriers, as the manufacturing cost is closely tied to the technological nodes used and the area for integrated circuits, and is particularly influenced by the amount of available resources for FPGAs. These three criteria are inherently conflicting, as improving one often negatively impacts the others. Finding the best balance between these factors requires significant effort. To address these complexities, design automation tools are increasingly valuable. Odatix is an open-source toolbox designed for the automated implementation and validation of parametrizable digital architectures. It supports synthesis, placement and routing for various FPGA and ASIC tools and simulators. It simplifies key stages such as synthesis, place and route, simulation, and validation, allowing designers to efficiently navigate multiple configurations and identify optimal solutions tailored to specific application constraints. Indeed, Odatix enables comparative analysis of multiple architectural configurations through various metrics such as maximum operating frequency, resource utilization, and power consumption. This paper presents an overview of Odatix’s capabilities and its application to the AsteRISC processor, demonstrating its utility in choosing the best architectural configuration, technological target and EDA tool for specific application constraints.

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引用次数: 0

OpenTorsion: Python library for torsional vibration analysis

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2024.102013

Sampo Laine, Urho Hakonen, Eetu Nieminen, Riku Ala-Laurinaho, Raine Viitala

Torsional vibration analysis is a crucial part of rotordynamic analyses during powertrain design for various industry applications. The torsional analysis is typically performed using specialized codes to model and simulate the system dynamics, with the goal of computing the torsional stresses to optimize performance and prevent failures. This paper presents OpenTorsion, a Python library for conducting torsional vibration analysis. The library enables the modeling of torsional dynamics across a wide range of applications, including vehicles, maritime systems, and energy production. As methods for torsional vibration modeling continue to evolve, an openly developed and freely distributed open-source library such as OpenTorsion provides an excellent platform for systematic dissemination and sharing of new research developments.

引用次数: 0

TAMAG: A python library for Transformation and Augmentation of solar Magnetograms

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX

Pub Date : 2025-02-01 DOI: 10.1016/j.softx.2024.102032

Temitope Adeyeha, Chetraj Pandey, Berkay Aydin

Solar line-of-sight (LoS) magnetograms consist of two-dimensional representations of magnetic field strength of Sun’s photosphere, typically ranging from (

\sim \pm

4500 Gauss). However, directly employing these original high-depth rasters with 32-bit floating-point precision in predictive modeling tasks can be computationally inefficient due to their large size. This can result in deficient patterns, often caused by missing raster values due to instrumental errors. Furthermore, this data is primarily used for data-driven solar physics research and space weather forecasting, where one of the most prominent challenges is class imbalance and data scarcity. Due to the scarcity of such data, predictive models may suffer from reduced generalizability, potentially impacting the reliability of forecasts. This paper introduces an open-source Python library named “TAMAG”, motivated by the need to address these challenges. TAMAG streamlines the preprocessing of solar magnetograms by offering appropriate transformations and domain-appropriate augmentations to generate new data that closely matches the distribution of the original data. It generates the output as 8-bit (grayscale) or 24-bit (RGB) images, as well as 2D arrays as specified by the user. TAMAG aims to benefit researchers by improving efficiency, usability, and integration of various appropriate data augmentation methodologies into existing workflows, ultimately enhancing research outcomes, analysis, and data-driven solutions in solar physics and space weather forecasting.

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引用次数: 0

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