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This project aims to make the Ubuntu Desktop Provision installer fully accessible to visually impaired users by addressing key accessibility issues in its Flutter-based interface. Currently, the installer lacks proper screen reader support, suffers from poor keyboard navigation, and fails to provide audio feedback, making it unusable for blind and low-vision users, especially those relying on Accessible-Coconut, a Ubuntu-based distribution developed by Zendalona. The solution involves fixing both architectural and UI-level problems in how Flutter components interact with Linux accessibility frameworks (AT-SPI). It will include: - Implementing semantic accessibility wrappers - Ensuring proper focus and navigation flow - Enhancing screen reader feedback using Orca - Improving the accessibility of complex UI components, such as partitioning - Conducting extensive user testing and providing detailed documentation Deliverables - A fully accessible Ubuntu installer with complete screen reader compatibility - Keyboard-navigable UI with audio cues and meaningful semantic labels - Documentation and developer guidelines for future accessibility improvements - Tested integration with Accessible-Coconut 24.04 This project will enable independent system installation for visually impaired users and contribute long-term value to Flutter-Linux accessibility efforts and the broader open-source community.

<p>Aim of this project is to use api/stream.json endpoint of loklak_server to continuously fetch new tweets and use them to show results as auto-refreshing media wall. Part of the project is also to implement accounts using firebase and add support for Twitter-Api for logged in users.</p>

The proposal outlines a plan to increase compatibility for two classic games, "Total Distortion" and "The Journeyman Project," on the ScummVM platform. The project aims to fix bugs, thoroughly test the games, and ensure they are production-ready by the end of the timeline. The project's benefits include increased access to classic games, increased community engagement, improved stability of the Director engine, and increased interest in the engine. The deliverables include identifying and fixing bugs, prioritizing issues, regression testing, and rigorous testing for official support!

<p>OAuth 2.0 Dynamic Client Registration Management Protocol specification defines a set of rules to manage the OAuth 2.0 Dynamic Client Registration which is already supported by the WSO2 IS. OAuth 2.0 Dynamic Client Registration Protocol describes how a client dynamically registered in the authorization server. But there can be situations where client needs to modify the registered data or check the current registration data or delete the data from the authorization server. So OAuth 2.0 Dynamic Client Registration Management Protocol came up with methods to enable the above functionalities. The primary scope of this project is to implement the OAuth 2.0 Dynamic Client Registration Management Protocol in the WSO2 Identity Server.</p>

Climate change is the biggest challenge of our time. We need all the help we can get to reduce emissions in every sector. The land sector is particularly important because there are not only emissions but also to potential for removals of greenhouse gases from the atmosphere. The Full Lands INtegration Tool (FLINT) is a platform for estimating greenhouse gas emissions and removals from land. This project: Develops new modules that represent the impacts of environmental changes on growth and mortality rates. Data from South Korea is used as a pilot. Scientifically, the key challenge is to translate information about tree-level responses to environmental changes to stand-level responses. Develops online training in response to COVID-19 to replace classroom training. A coherent approach to online instruction needs to be designed and the existing materials need to be turned into online ready versions.

Fabric Private Chaincode (FPC) leverages modern Confidential Computing technology, such as Intel SGX, to enhance the protection of chaincode and their data while executed at the endorsing peers. Client applications interact with their private chaincode via the FPC Client SDK, which is responsible to encrypt and authenticate the invocation arguments before being sent to the endorsing peers. However, the FPC Client SDK currently does not support the new Fabric Gateway API that simplifies the transaction flow for the clients. The goal of this mentorship project is the design and the implementation of the FPC Client SDK using the new Fabric Gateway API. This also includes the creation of appropriate samples and documentation. The project requires a solid understanding of theory and practice of software development using Golang, distributed systems, and security. During the project you will get hands-on experience with the deployment of Fabric networks, the transaction lifecycle, confidential computing technology.

<p>Business Process Model and Notation (BPMN) is a standard way of representing business processes in graphical representation.The purpose of this project is to implement Web based BPMN editor to construct business processes diagrams, which can be exported as a BPMN-2.0 compatible XML format . This BPMN diagrams can be built using components like tasks, events and gateways etc. Users can implement their BPMN diagrams by dragging, dropping, positioning, resizing, deleting and adding more details to the attributes. Constructed BPMN diagrams can be then exported as png/jpeg or a process definition XML file(BPMN 2.0 standard).BPMN editor also supports the inverted process, which is uploading of a standard BPMN model in XML format to generate a BPMN process diagrams.</p> <p>This piece of software has the capability to build complete Business process diagrams and is also extensible to allow the construction of flow charts, chevron charts and other graph-based diagrams.</p>

<p>Nowadays, sharing and use of human biomedical data is heavily restricted and regulated by multiple laws. Such data-sharing restrictions allow keeping privacy of the patients but at the same time it impedes the pace of biomedical research, slows down the development of treatments of various diseases and often costs human lives. COVID-19 pandemic is unfortunately a good illustration of how inaccessibility of clinical training data leads to casualties that can be otherwise avoided. Even the World Health Organization which is supposed to become a data hub for COVID-19 data, refuses to share most of the clinical data even in anonymous form due to the complexity of regulations. Such problems are also common for bioinformatics as training classifiers and regressors on patient *-omics data often involves dealing with medical records of the patients.</p> <p>To address these problems, we propose to develop a package, HRC, which will be built on top of Federated Learning (FL) framework, to bridge the gap between healthcare provides and researchers.<br> This package will allow biomedical researchers to quickly modify and deploy FL for typical bioinformatic use-cases.</p>

<h5>Introduction to Image Sequencer</h5> <p>Image Sequencer is a non-destructive image processing library built with JavaScript which creates a new image at each step in a sequence of steps. Image Sequencer is in early-development phase. The core functionality is being implemented. There are a few modules present. Calculations aren’t GPU accelerated. As a result, there is a lag when images larger than 700KB are handled. Also, Image Sequencer works only for browsers currently as it uses a browser dependency (the JavaScript Image Class). Image Sequencer currently supports only one image at a time.</p> <h5>Aim of my project</h5> <p>The aim of my Project is to expand the module library by implementing powerful processing modules (As listed at the end of this proposal) followed by enabling GPU-backed calculations for browser based clients and hence enhance performance, reliability and speed. And, ultimately, to develop Image Sequencer as an importable library for image manipulation and publish it on NPM. Also, support for Node.js based clients and JSON input/output will be generated.</p>

Libraries worldwide face challenges in adopting digital lending due to restrictive licenses and costly, vendor-locked systems that limit independence. Lenny is an open-source, self-hosted lending system inspired by the Internet Archive and Koha. Its mission is to give libraries ownership of their digital collections while offering a flexible and cost-effective alternative to proprietary platforms. At its core, Lenny based on python features a FastAPI backend that handles borrowing, returning, and waitlists, with support for Readable, Borrowable, and Print-Disabled books. Security and compliance are provided through LCP DRM and Geo-IP restrictions, while PostgreSQL triggers automate loan expirations. An OPDS feed enables integration with Open Library, Thorium, and other reading systems. Deployment is simple with Docker (Alpine + Nginx), and a React dashboard allows librarians to set lending rules like loan durations and waitlists. To improve accessibility, the companion Lenny-app (TurboRepo monorepo) includes: 1. A sandbox demo preloaded with 500+ e-books to showcase the system in action powered by Lenny. 2. A documentation site that supports integration, open-source contributions, and extensions. Built with TypeScript, React, Next.js, Node.js, and Express.js, Lenny-app is production-ready yet flexible for experimentation. Together, Lenny + Lenny-app deliver both the backend infrastructure and the user interface needed to power community-driven digital lending. By combining secure architecture, a ready-to-use demo, and developer-focused documentation, Lenny provides libraries with a scalable and future-proof solution to manage digital lending independently and expand access for their patrons.

Cellfinder currently expects full 3D whole-brain volumes with both signal and background channels, so brain slices (2.5D) and single-channel acquisitions are not first-class citizens. The codebase also mixes axis conventions, which makes dimensionality changes error-prone. A recent data-loading refactor introduces explicit axis tracking and a new class hierarchy for cube generation and augmentation; the 2D/2.5D and single-channel work proposed here will build on that foundation. The core deliverables are to standardise axis semantics as the foundation, add a 2D detection path for brain slices and refactor classification to support both 2D and 3D inputs, and make the background channel optional across the main API and classification pipeline.

<p>Fabio Gandolfi gsoc username: zwerg4 email: fab.gan@hotmail.de github: zwerg4</p> <p>My name is Fabio Gandolfi, I am a 24 years old computer science student of Italy but currently living and studying in Austria.</p> <p>I am very interested in programming in a lot of different programming languages. Currently I am studying Computer Science in Graz (Austria). I would propose to the iOS team where I already contributed some new features and therefore already have an overview how the app is built.</p> <p>INTEREST: Pocket Code for iOS: Support for Catrobat Language version 0.994 - 0.99992. This task seems interesting to me and I would like to implement it during the summer to bring also some new compatibilities to the iOS app.</p> <p>Since I already contributed to your amazing project and really liked it a lot also because I learned a lot of new things and because I think it has a lot of potential I am really looking forward to work with you also in the Google Summer of code.</p>

Currently the wasm-emscripten port of VLC (Vlc.js) does not support compilation with shared module. This project enables shared module loading for vlc.js, while finding and mitigating the limitations from underlying tools like Emscripten, Libtool and VLC itself to achieve it.

<p>The current OGR core doesn't include three geometries according to OGC standards - Triangular Irregular Networks, Polyhedral Surfaces and Triangles. The proposal addresses the addition of the same in OGR core as well as the introduction of support in existing OGR drivers for these geometries.</p>

The core goal of this mentorship consists in implementing the much requested feature of adding support for the F-extension to Ripes. This involves two major steps: first, constructing inside Ripes source code a working implementation of the extension for correctly simulating the instructions with VSRTL (a Ripes-specific, Hardware-Description-Language-like C++ Domain Specific Language created ad-hoc for Ripes); second, implement the required additional Ripes GUI interface for correctly visualizing meaningful insights into the inner working of cores implementing the F-extension. The mentee should expect to fully complete all complementary tasks to the development process, as writing and running comprehensive tests and updating the documentation to reflect the latest version of the project.

The Fabric Token SDK allows developers to create token-based distributed applications on Hyperledger Fabric. While the Fabric Token SDK offers many features (i.e., configurable privacy, p2p transaction orchestration, atomic swaps, and audits,...), performance is yet another important aspect. The Hyperledger Caliper project is a blockchain performance benchmark framework, which allows the evaluation of blockchain solutions. How about using Caliper to benchmark token-based applications built on top of the Fabric Token SDK? The goal of this project is the design and the implementation of a Caliper plugin to evaluate applications using the Fabric Token SDK. This includes the creation of appropriate documentation and performance evaluation of sample applications. The project requires a solid understanding of theory and practice of software development using Golang and Node.JS, distributed systems, and performance benchmarking. During the project you will get hands-on experience with the deployment of Fabric networks, the transaction lifecycle, the Fabric Token SDK, and Hyperledger Caliper.

<p>Users of Plasma Desktop Environment expect to find all their necessary system configurations through the System Settings application. So it plays an important role for the overall user experience of Plasma. But the current application is largely designed using the legacy QWidget framework, and does not meet the requirements for more responsive / modern design required for use in touch screens and mobile platforms. For that, it is necessary to port the KCMs to Qt Quick, which is quite tedious work and requires a lot of manpower. My primary goal is to help the KDE Community in this immense task, by porting the keyboard input modules, with modern designs provided by the KDE Visual Design Group (VDG).</p> <p>Another additional goal is to integrate the input method configurations, such as ibus or fcitx, into the System Settings application. Currently, the only way to install / configure these input methods is to install it from a package manager and use the GUI provided by the input method, which is far from discoverable. The ability to add / remove and configure IMEs will improve user experience for a global audience.</p>

<p>JyNI is a compatibility layer with the goal to enable Jython to use native CPython extensions like NumPy or SciPy. So far it was developed on Linux and some additional effort was spent to let the core part work properly on OSX. In principle the current version of JyNI is workable on POSIX platforms. I propose to create a proper Windows version of JyNI. A fully accurate implementation of this proposal includes to establish workability of all extensions and features that are currently supported on POSIX platforms.</p>

<p>The majority of the code in Homebrew is written in Ruby which is a dynamic language. This means that types are checked when the code is run. My project aims to incorporate Sorbet, a static type checker which would provide the benefits of static type checking to a developer. Adding static type checking helps developers rectify potential errors before the actual runtime. It also provides faster debugging of pre-existing bugs even by new developers, as they can easily jump to class/method definitions without having prior knowledge of the directory structure of the project. Sorbet serves as a tool to reduce brittle code, increases a developer’s confidence in their work and is a great tool for refactoring. I believe that this project has a lot of potential and the impact that it is going to have on the overall development cycle is going to be huge.</p>

While generating Package Repository kctrl to create the tar version of the Package Repository instead of pushing the OCI Image to a registry. - Expected Outcome: - Proposal containing design discussions and options considered.

Graphite is a powerful graphics editor, but it currently struggles to handle complex SVG files perfectly. Important details like custom text styles or advanced shapes may sometimes get lost when opening or saving files. My goal is to fix this by building a reliable, complete SVG pipeline. Firstly, I plan to add missing core features like gradients, patterns, and a proper Text-on-Path node so that Graphite can edit more SVG artwork natively. Followed by this, for any highly complex SVG features that Graphite still would not be able to edit directly, I will build a fallback system. This system will automatically convert those unsupported parts into static images rather than silently dropping them, ensuring the artwork looks exactly right when opened. Finally, I will improve how Graphite exports files, making sure layer names are saved as clean SVG IDs. Altogether, these changes will make Graphite a tool that artists can fully trust for professional SVG work.

Currently libcamera's ability to set control over each frame and stream is not reflected by the test applications. We don't have any way to set the controls using the test applications (qcam and cam). This proposal aims to address that. It would add a clear set of GUI controls to qcam and a cmd line friendly way for cam to set the control over the frames.

<p>This project aims at integrating IFTTT (IF This Then That) feature to the Wikidata extension and extending RSS views and writing Unit tests for the existing Wikipedia triggers on IFTTT. IFTTT technology being one of the most popular ways of making chains of web services communicate with one another, will be used to make Wikidata to communicate with other web services (IFTTT web service) across the web. This project involves studying the Wikidata API, IFTTT technology internals and providing a new and friendly way to communicate to Wikidata. Adding RSS views will enable users to connect with the service independent of IFTTT and writing tests will automate testing of the application saving time and improving on productivity.</p>