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This project aims to replace Brian’s current just-in-time (JIT) compilation system, which relies on Cython. While functional, Cython introduces slow compile times and adds complexity by requiring separate code generation paths for Python and C++. The goal is to simplify and speed up Brian's runtime by: - Replacing Python-based structures (e.g. dynamic arrays, spike queues) with C++ equivalents - Enabling direct, efficient C++ calls from Python with shared memory - Exploring JIT alternatives like Numba or SciPy Weave - Refactoring the runtime to support this new architecture

<p>This project is a continuous work for the GSoC2018 Dynamic Signal Processing Workflow Designer. The previous existing project is a Web-based GUI to deal with the cumulative signal, offering users configurable component blocks to design their own workflows in the GUI and execute the workflows without making change on code. This year, to make this designer also process the continuous stream and mixed data, and improve the executing efficiency, make the code more understandable and maintainable, redesign and refactor are needed for the workflow designer.</p>

<p>For tedana to expand, more extensive test cases are needed. A new contributor could have introduced an unknown bug into the codebase, but without extensive testing, there is no way to find out until a code review (and even then, it may slip through!) It would be wise to have vast and wide-ranging tests that catch the bug for the contributor!</p> <p>For this project, I will write detailed unit test cases for the tedana codebase, hitting as many lines as I can while testing! I will also make changes to the functions themselves to type check the input parameters!</p>

<p>This project aims to improve the automated testing of the LORIS codebase. This will be achieved through writing both unit and integration tests, as well as improving the datasets available in the LORIS database that can be used for testing. The majority of the automated testing will be for the backend services, although some frontend tests may be developed as well.</p>

<p>ImageJ is an open source Java image processing and analysis library used extensively in biomedical sciences. Active Segmentation is a plugin providing user interface to scientists, allowing them to use Machine Learning algorithms for segmentation and classification tasks. The aim of the Active Segmentation is to provide researchers an extensible toolbox enabling them to select custom filters and machine learning algorithms for their research. Moreover, it provides the support for scientists without strictly technical background (does not require programming skills to apply above mentioned tools). The idea behind this project is to extend active segmentation with modern deep learning methods for image analysis using Deeplearning4j library.</p>

<p>Feature extraction is the core aspect of pattern recognition. In the specific domain of NeuroImaging, researchers in the past have formulated uncountable ways to analyse the data and came up with thousands of inherent spatial and temporal features related to brain activities. However, these feature extraction methods are widely scattered in the web, making it arduous for researchers to focus on the problem statement.</p> <p>Hctsa tool tried solving this problem by creating a zoo of features (&gt;7000) extraction for time series in general. However, adapting hctsa can be computationally expensive and requires licensing to run, limiting widespread adoption for medical and research applications.</p> <p>The idea here is to provide a single robust and portable open-source platform inclined to NeuroImaging domain and pipelined through catch22, wherein all the relevant features (distilled from large literature into a small subset with minimal loss in performance) are natively coded and wrapped up as a library which can be used as an automatic feature extractor modules for independent projects. This will also enable the usability of this system in time and memory-constrained environment.</p>

Several attempts have been made in recent years to develop, collect and analyze data in the field of neuroscience. This proposal aims at helping neuroscience and open-source communities by refactoring and optimizing Disimpy’s code. With this optimization, simulation runtimes and GPU memory usage could be reduced, achieving a higher precision in DW-MRI simulations, which could bring us closer to the real and complex behavior of the system that shapes brain tissue. Disimpy is a GPU-accelerated diffusion-weighted magnetic resonance simulator that is used for developing and validating neuroimaging methods. Diffusion MRI is an imaging modality that provides us with information such as the orientation, the size, or the shape of neurons from the random displacements of water molecules in brain tissue. Water molecule diffusion patterns show how the molecules interact with the environment, revealing microscopic details about tissue structure, either sane or impaired. Diffusion MRI simulations require high precision to represent reality meticulously. Hence, optimizing the code that runs the simulation seems reasonable and extremely important. This study sheds light on this issue by proposing examples on how to improve the code, such as an optimization of Subvoxel-Triangle intersection algorithm, Ray-Triangle intersection algorithm, and the way of saving triangles and an implementation of a new feature that could allow the simulation of more complex systems.

SciCommons aims to revolutionize academic publishing by providing an open peer review platform. The current system faces challenges such as time constraints and limited reviewer capacity. SciCommons addresses these by allowing any user to review, comment, and rate research articles, enhancing article quality and decreasing review time. Anonymity ensures ethical and unbiased reviews. Building upon its existing functionalities, the project will introduce private communities for exclusive peer review, an immersive discussion/chat sections for each article. Deliverables include modularizing the frontend, enhancing user experience, implementing small feature enhancements, and integrating private communities and discussion channels. The project will prioritize code quality and adhere to open-source standards. By democratizing scholarly discourse, SciCommons fosters collaboration and transparent peer review.

<p>Currently the human assistive system collects the EEG data, processes it and trains customized classifiers. With the increasing number of tested subjects, the goal is to store the rapidly growing data in a distributed storage system such as Apache Hadoop. Data processing would also be implemented on the distributed system using the MapReduce framework and its extension Apache Spark.</p> <p>The goal of this project is to create a scalable system which would enable storage of very large datasets and quick, distributed training of classifiers on those large datasets. Another goal is to provide the users with a GUI for browsing and managing the distributed filesystem as well as building full machine learning pipelines.</p>

I am planning to improve how AnalySim looks by simplifying pages to assure that it is both practical and easy for users to navigate through it. I also plan to modify the aesthetics of the website by ensuring that all pages go by the same color scheme, as there are some pages with similar colors to each other, but not the same hex code. I will also make sure all pages are under the same Angular and Bootstrap technology. I want to create GIFs that will not only aid in navigating the website but also represent the graphs that will be generated on AnalySim.I also plan to create web pages to query, browse and filter a CSV file. -Update the existing interface to the latest Angular -Add Bootstrap technology to all website pages -Design the Website to have a consistent look -Continue implementation of design -Create new pages that are needed for various operations such as browsing projects, filtering projects, searching for topics, etc. -Create a graphical design that is modern and unique to this project, maybe by incorporating some meaningful GIFs. -Create a page to browse CSV files -Create a webpage to query and filter a CSV file -Create a webpage to display various interactive graphics that can be used for -publication by researchers such as histograms -Assure that users can download and print high-quality images -Assure that all web pages are printable -Simplify web pages -Create guidelines that are easy to understand as GIFs to help people navigate the system -Communicate and help other developers on the project to make sure that the system functions properly -Make the footer consistent on all pages, without wasting so much space -Finalize the Contact Us page

While music educators strive to provide personalized learning paths, existing educational tools often lack the flexibility to adapt to diverse student needs. HarmonyHub bridges this gap by integrating Generative AI into a modular, web-based platform, empowering teachers to design customized exercises and dynamically adjust lessons based on individual progress.By leveraging AI-assisted personalization, HarmonyHub enhances the teacher’s ability to cater to different learning styles, ensuring a more engaging and effective music education experience for all students. 2. Key Features This project contributes to the open-source music education ecosystem by: Empowering teachers with AI-driven tools for personalized lesson planning. Providing a no-code interface to enable educators to create and modify exercises. Enhancing inclusivity by tailoring lessons based on students’ technical proficiency, learning speed, and backgrounds. Expanding the Harmony Hub ecosystem by integrating Generative AI for real-time content creation and assessment. Demonstrating how LLMs can be effectively applied to domains involving non-textual data, such as music.

<p>This proposal outlines the steps and experience needed for a javascript based data visualization tool for LORIS through the React framework. A method to validate uploaded data will be needed to be integrated as well with proper testing and documentation after weekly meetings and feedback from mentor(s) to ensure project deadlines are met.</p>

<p>AnalySim is a data sharing platform similar to GitHub, but specialized for scientific projects. It seeks to simplify the analysis and visualization of datasets. AnalySim is designed to promote collaborations and to improve existing datasets through features like forking or cloning, features specialized to allow users to start new projects, collaborations or join existing teams or projects.</p> <p>First feature I would like to add to AnalySim is forking projects, which will help collaboration between researchers. One can fork someone else’s project and improve upon it by adding more data or improving analysis. Second feature I'm interested in is adding a new design template. Finally, I want to improve the existing documentation. If there's extra time, I would like to work on adding a component that allows for CSV file viewing.</p> <p>This project offers me a great opportunity to practice my technical skills of programming the web based technologies I learned in my classes. Specifically, I have experience in working with Angular, web development and web design. I aim at starting a career in software development where I want to put to practice the skills learned during this project.</p>

<p>CBS Tools are specialized Java-based image processing tools for ultra-high field MRI data. Making this potent software more easily accessible to researchers will accelerate progress in the promising field of high-resolution neuroimaging. The goal of my project is therefore to make CBS Tools available through Nipy, a popular “community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data”. First steps have been made to encapsulate CBS Tools’ Java classes using the JCC package, enabling access through Python. Within the Google Summer of Code I would like to take this further and provide easy-to-use and well-documented Python interfaces for the core modules of CBS Tools. Since rapid advances in the dynamic field of high-resolution neuroimaging are to be expected, another focus of my proposal is to facilitate future contribution of other researchers. My three main objectives are (1) to provide straightforward installation routines for different platforms, (2) to create Nipype interfaces for the core modules and (3) to make the code accessible through documentation and realistic examples.</p>

SciCommons is an open-source platform aimed at improving the scientific peer review process through better user experience and web application optimization. It focuses on refining the frontend UI, following best practices, and enhancing performance. Contributors will work on UI improvements, optimizing API performance, and ensuring cross-platform compatibility.

Problem: Brian2CUDA offers significant GPU acceleration for neural simulations, but its current "beta" state contains friction points that hinder widespread adoption. Key issues include unreliable Windows support due to POSIX-specific build assumptions, slow incremental compilation that often exceeds simulation time, silent GPU failures that are difficult to debug, and startup crashes related to preference file validation. Solution: This project aims to make Brian2CUDA "production-ready" by modernizing its backend infrastructure without adding heavy external dependencies. The plan involves: Stabilizing the Windows workflow by implementing a robust nmake/MSVC build path and platform-independent path handling. Optimizing compilation speed through deterministic source grouping and granular dependency tracking in generated Makefiles. Implementing a synchronized C++/Python logging system with structured CUDA error-checking to eliminate silent failures. Resolving preference validation conflicts to ensure reliable configuration loading. Deliverables: - A validated cross-platform build system supporting Windows (nmake) and Linux/macOS (Makefile). Optimized code-generation templates for faster incremental builds. A unified diagnostic logging framework. A suite of regression tests and "Getting Started" documentation for Windows users.

<p>The major goal of this project is to Extend the work of making plugin which was developed in last year. This year we need to come up with some current architecture change to incorporate learning from entire images which can be further used to image classification. Other then this we need to add some additional features selection to the existing platform and change the current GUI according to this.</p>

This project aims to improve the reliability and maintainability of the LORIS electrophysiology browser through scoped enhancements to browser behavior, validation, testing, and documentation. I plan to begin by reviewing and reproducing known issues or limitations, then implement targeted improvements in small, reviewable stages with mentor feedback. The expected deliverables include a practical browser improvement, expanded automated test coverage, and developer-facing documentation that helps make the contribution sustainable within the LORIS codebase.

The platinum open access overlay neuroscience journal - Neurons, Behavior, Data Analysis, and Theory – NBDT is ready for inclusion in PubMed Central (PMC). However, PMC requires full-text machine-readable XML article file deposits. These files contain the complete article text in machine-readable language, with front-matter metadata. At the moment, final paper submissions to NBDT are in LaTeX format. While there are tools that provide LaTeX to XML conversion (as required by PMC), no single tool does it seamlessly without errors for the template corresponding to NBDT. The current project aims to build an application providing this functionality. The project will build over the LaTeXML tool to enhance custom bindings as required for NBDT submissions. The first step would be to enhance the bindings for body matter, as Scholastica (which hosts NBDT) already provides it for front-matter binding. In addition, to make the application platform-independent, it will be extended to provide custom front-matter and back-matter bindings. It shall also contribute verification engines to automate XML verification, JATS verification, and PMC-specific verification. The application shall make it convenient to bridge NBDT submissions and the PMC archival process.

<p>The purpose of this project is to create functions which convert a wxMaxima worksheet to Texinfo. The functions to convert a worksheet will be written in Common Lisp, which is the implementation language for Maxima itself.</p>

The measurement of visual function in infants and young children is crucial for early detection and treatment of eye conditions that can lead to visual deprivation and affect visual development. However, the limited cooperation and inability to provide verbal responses in infants make the accurate and efficient measurement of visual function challenging. This project aims to develop a ready-to-deploy application suite that will address these limitations by integrating hardware devices or deep learning-based infant eye trackers, and visual stimuli analysis into a user-friendly graphical user interface (GUI).

<p>The project is to provide a set of demo packages, including sample python code and user-friendly webpages to clinical researchers for the reproducibility of their results. This project will make The Virtual Brain easier adaptable to clinical researchers.</p>

<p>The project aims to provide a robust mechanism for cell tracking using 2D raw image object.Through the use of Viterbi Dynamic Programming based Algorithm it is aimed to implement an efficient Cell Tracking system aided by Multi Class Classifiers for Cell Event Probability definition.Trajectory estimate will be de-noised using modern filters such as IMM,Weiner and Multiple Channel Linear Correlation Filter.</p>