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Being cross-platform and able to sync notes are crucial features of a note-taking app which Joplin implemented very well. Currently, Joplin is on these platforms: desktop, mobile, and terminal, it would be best to separate the current Joplin synchronizer as a standalone syncing library. Such re-implementation can decouple the ecosystem, and allowing more user control over the syncing process. Porting current Joplin's synchronization modules to a separate library. Integrate with some Cloud Providers: Onedrive, Dropbox,... Exposing services to allow more control over syncing process. Adding unit & integration tests for new library.

<p>Searching is an essential feature for any note-taking system. Users expect to be able to search not only the text but also on the type of note, the date it was created/updated, the tags it contains, among other things.</p> <p>On top of implementing these advanced search filters, this project also proposes to upgrade Joplin's ranking function to the popular Okapi BM25 and make fuzzy search possible.</p>

Joplin currently uses sjcl library for end-to-end encryption on all platforms. In the past, this has caused performance issues. Ideally, we would use a native encryption library for faster encryption speed and less CPU/memory usage.

<p>This Project Aims to improve the openmrs-reacts-component repository.</p> <ol> <li>Add a bunch of components</li> <li>Create a open web app out it of so that people can generate multiple types of fully configured projects</li> <li>publish to npm so that it is easily distributable</li> <li>Have an awesome documentation so that it attracts contributers and users.</li> </ol>

<p>The project aims to create a "Sugarizer Server Dashboard" for teachers and deployment admin which can be used to control and manage the work of learners and analyze all various activities on a Sugarizer Server. Teachers won’t have to locally transfer journals from the learners’ device and would be able to launch each activity exactly like it was on the learner’s device. This project would have a great impact on the teachers as they would be able to manage their workflow in a more automated way which would also increase user engagement &amp; product adoption by completing the loop which is missing right now. For the sugar labs community, it would be great as they could view all the statistics directly from the dashboard and work on improving the system in a fact-based way using the information presented in the dashboard.</p>

The APAP MCP server currently routes every tool call through an internal HTTP loop back to its own Express server, adding unnecessary latency, making MCP handlers impossible to unit test, and discarding all HTTP error context behind generic error strings. The MCP layer has zero automated tests and no client-specific documentation beyond a basic setup guide. This project introduces a shared service layer that both MCP tools and REST routes call directly via Drizzle ORM, eliminating the HTTP round-trip. Structured error types replace generic strings with machine-readable codes and HTTP status preservation. Deliverables: 1. Shared service layer refactor with structured error types across all 8 MCP tool handlers 2. Four-tier test suite (unit, integration, contract, E2E) with 90%+ coverage enforced in GitHub Actions CI 3. Client-specific tutorials for Claude, ChatGPT, and MCP Inspector 4. Developer experience improvements: Docker Compose quickstart, Pino structured logging, /healthz endpoint, and updated CONTRIBUTING.md A working proof-of-concept implementing the core refactor with 53 tests and 98.55% statement coverage is already live at github.com/JayDS22/apap-mcp-poc.

<p>Implement Language Server for RBS</p>

<p>This project aims to implement Streams API polyfill for PDF.js, and use it for networking and rendering purpose. PDF.js current uses xhr for networking to fetch data, but it is inefficient in terms of memory as it has to buffer all the response. As xhr is an ever growing buffer, it stores all the data in its internal buffer, this uses lots of memory. Using Streams API, we can use the response incrementally and pass it for parsing and rendering as soon as it is received, hence there is no need to buffer the whole response. For rendering purpose, PDF.js makes chunks of data by parsing pdf commands in worker thread. After chunking the whole data, it is passed to the main thread for painting. Buffering the entire data in the worker thread uses a huge amount memory, and main thread also has to wait for the entire data to be parsed. This creates inefficiency in terms of memory and speed. Using Streams API, we can send the chunks from worker thread to main thread as soon as they are created, reducing the memory usage and increases speed. Since Streams API is a new technology, using it in PDF.js will test Firefox's implementation.</p>

<p>One of the capabilities of the robot is to efficiently communicate with humans, either through voice or gestures. Currently, EBO is equipped with components that enable it to perform social tasks like face detection, emotion recognition, people identification, etc. The aim of this project is to add upon the existing functionalities by integrating a ‘Hand Gesture Recognition Component’. Hand Gestures are very significant for human-robot interaction. This component can be used as a tool to enable communication between robots and humans. Furthermore, this component will enable the robot to understand American Sign Language (ASL), which will be a really efficient way of communication.</p> <p>RoboComp is also working on the Human Activity Recognition project. Hand Gestures are a key component in both natural and social human activities. This component when integrated with the Human Activity Recognition Component can be used for various use cases (like detecting commands given by hands), which adds value to this project.</p>

<p>BioJS is a library of over one hundred JavaScript components enabling users to visualise and process data using current web technologies. BioJS makes it easy for users to integrate their visualisations into their own website or web application.</p> <p>The process of updating the BioJS standard to version 3.0 is going on. The Yeoman generator to upgrade BioJS components by wrapping them in a Web Component has already been created which enables users to embed and use visualisation of various BioJS components.</p> <p>This project involves improving the Yeoman generator by adding new features and tests to make it easier for developers to implement old BioJS components as Web Components and to make new BioJS Web Components. It also involves clearly documenting the whole process of using the generator so as to make the task of working with the generator, making new components easy for developers as well as easily creating visualisations so that even non-technical persons can embed and use the visualisations in their work.</p>

<p>The aim of this project is to improve the Rust developer experience via the Rust Language Server by introducing few notable improvements. The scope includes supporting more workspace configurations (multiple targets and active crates) as well as popularly requested IDE features, such as implementing code action mechanism on the server side, e.g. used for refactoring or running specific tests, or improving diagnostic data required for better code navigation. Providing good out-of-box IDE experience will substantially help with widespread adoption of Rust and support writing not only quality self-contained libraries, but also incentivize writing advanced end-user oriented applications.</p>

<p>Learnbot is a small low-cost robot designed to develop computational thinking in kids of age 10 and above. Presently, Learnbot can be programmed to show emotions via a display. However, it does not have the ability to recognize human emotions. Having this ability would help improve the Human-Robot Interaction(HRI) functions in Learnbot.</p> <p>This project aims at applying state-of-the-art techniques to create a fast, accurate and robust emotion recognizer. It would be able to recognize 5 basic emotions: Happiness, Sadness, Anger, Surprise, Neutral, based on facial expressions. This involves training a Convolutional Neural Network based classifier.</p> <p>The ability to recognize emotions would be added as a new component in Learnbot. Other components would be able to access the data generated by this component through an interface.</p>

<p>The AeroGear UnifiedPush Server is a powerful and scalable server that allows sending push notifications to different (mobile) platforms. And now it’s time to extend it and add supporting for a new WebPush protocol, which will allow to send push notifications to the web browsers, such as Google Chrome and Mozilla Firefox.<br> The project also supposes integration of AeroGear WebPush Server with UPS, which will allow to send push notifications to any device without requirement to use vendor’s push-messaging systems (Google Cloud Messaging, Mozilla Push Service).</p>

<p>Two main reason for this to be an important idea. (1) Sometimes we will have to work with component networks which contains hundreds of components.The current manager is not enough for managing such a huge network system which in effect dwarf the usefulness of the framework . (2)The possible users of the framework include people who are working in electrical and mechanical domains of robotics also, People who mostly use the inbuilt components.For them it will be good to have all the functionalities under one roof.So it is necessary to have a tool which helps to launch, control and edit the components.</p>

<p>A better automatic system for documenting EUI TypeScript components that extract the acceptable values for each prop on the API. This would be done through automatic transversal of the EUI components itself, combined with the type values from TS and inline comments.</p>

<p>The streams based workflow engine will organize tasks into streams, allow parallelization of this streams, and work locally as well as integrated into common external HPC services. As well dat can be integrated to store intermediate and final data. This provides a framework for efficient, reproducible, and understandable bioinformatics pipelines.</p>

Orcanode repository contains a set of projects distributed in different directories that provide a number of tools to deal with capturing, processing, and uploading audio files archived at the Ocean Observatories Initiative (OOI) site. However, there are a few issues that need to be resolved and other enhancements to be made. This project focuses on the following: 1. Handling lags in miniSEED audio data fetched from the OOI website. The missing data issue also needs to be resolved. 2. Leveraging cloud tools for continuous pulling and streaming of data to reduce local system dependence. 3. Integrating the data with the Orcasound website and streaming hls format for users to listen.

The MusicBrainz XML/JSON API makes you stack inc= parameters just to get related data, and looking up multiple entities of the same type in one request isn't possible at all. This project aims to build a GraphQL server in Rust to fix that properly. It covers five entity types: Artist, Release, Release Group, Recording, and Label with MBID based lookup including transparent redirect handling for merged entities, keyset cursor pagination, and field coverage matching the existing API: aliases, annotations, tags, genres, ratings, ISRCs, IPIs, and release tracklists through the correct Medium and Track chain. Artist credits are exposed as structured types rather than raw joins. DataLoaders batch database queries across all relationship resolvers to prevent N+1 problems. Depth and complexity limits reject expensive requests before they touch the database. Caching is only applied where load testing shows it actually helps, not speculatively. Deliverables include a working server with Docker setup, integration tests, a documented performance baseline, and API docs auto-generated via magidocs CLI.

<p>Firefox Profiler is a tool which visualizes performance data recorded from various performance analysis tools, which helps us to have an insight into our app’s responsiveness, Javascript and layout performance. By using it efficiently we can optimize our app in terms of performance. Currently, it supports Gecko, chrome, and perf(Linux) profile formats. This project will provide support for visualizing profiles from Instruments which is a powerful and flexible performance-analysis and testing tool that’s part of the Xcode toolset.</p>

Overview The middleware server in the CARE project, currently implemented in TypeScript, requires a rewrite in Django to enhance integration and maintainability within the existing ecosystem. The implementation includes a couple of steps Research Compatible ONVIF Packages for Python Identify and select Python packages compatible with ONVIF standards for interacting with ONVIF-enabled devices. Implement WebSocket functionality using Django Channels Utilize Django Channels to enable real-time transmission of vital data from various healthcare system sources. Integrate authentication mechanisms for HTTP requests and WebSockets Ensure proper authentication mechanisms for both HTTP requests and WebSocket connections from CARE and CARE_FE applications. Ensure Proper Typing Support Enhance codebase readability and maintainability by implementing type annotations throughout the Django middleware. Write Migrations to Align Tables with Django Models Create and apply Django migrations to modify existing database tables to align with Django model definitions. Deliverables A new django app which has all the functionalities of the existing typescript middleware Authentication for websockets and http requests Ensuring Proper Typing throughout the django app

<p>Dendrite is a matrix server built in GO.<br> It's known that our state of the art Synapse is reaching it's limits in terms of performance.<br> Dendrite is an effort to provide fast, scalable and efficient alternative.<br> Although very promising, dendrite has a long way to go before it's ready to handle matrix's rooms.<br> This project is an effort to push dendrite towards feature completion.</p> <h4>Goals</h4> <p>Go over the current state of federation in dendrite and fill in the missing APIs.<br> Improve the reliability and stability of several components, while freeing them of known issues.<br> Add commonly used but missing functionalities.</p>

<p>This Project deals with writing a new component in RoboComp that will provide a naming and port service. When starting, components will now contact this new service to advertise its name, available interfaces and request a valid port. Other components starting later will be able to query the service for component names and interfaces, and therefore being able to establish their proxy connections in real time, eliminating the need for complex and tedious configuration files. Extensive tests with large networks of components will be performed and more advanced query capabilities for the service will be explored.</p>

<p>The goal of this project is to bring error recovery and streaming support in the graphql reference parser while maintaining the code readability, spec compliance and parser performance. This will enable this parser to be used by IDE like applications such as CodeMirror and GraphiQL. This project will also cover the migration of GraphiQL, GraphQL LSP server and CodeMirror Graphql to use the updated graphql reference parser.</p>