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<p><em>StatsD</em> is simple, text-based UDP protocol for receiving monitoring data of applications in architecture client-server. As of right now, there is no StatsD implementation for PCP available, other then <a href="https://github.com/lzap/pcp-mmvstatsd" target="_blank">this</a> which is not suitable for production environment.</p> <p>Goal of this project is to write PMDA agent for PCP in C, that would receive StatsD UDP packets and then aggregate and transfer handled data to PCP. There would be 3 basic types of metrics: counter, duration and gauge. Agent is to be build with modular architecture in mind with an option of changing implementation of both aggregator and parsers, which will allow to accurately describe differences between approaches to aggregation and text protocol parsing. Since the PMDA API is based on around callbacks the design has to be multithreaded.</p> <p>Agent is to be fully configurable with either PCP configuration options and/or separate configuration file. Writing integration tests is also in the scope of the project.</p>

The goal is to implement a functional GNSS receiver that is capable of introducing measurements from another sensor into the GNSS receiver chain. This will advance research on sensor fusion, enabling reliable high-accuracy navigation solutions in challenging environments such as the urban cannon. The end product will consist of a SignalSource implementation, responsible for talking with the sensor at a hardware level and synchronizing its measurements with GNSS samples; and the acquisition, tracking and PVT algorithms implementing the sensor fusion model.

<p>This increases the scope of Boost.Intrusive library by adding more data structures into the collection.Every data structure is capable of solving a large range of problems.So adding data structures increases the problem solving ability of intrusive library which increases the number of users using this library.Nowadays, data structures are used in many fields.There are 2 main reasons behind the use of data structures.First, to obtain better performance benefits and Second, to save space required for execution of an algorithm.The data structures i am going to implement are Segment tree , Fenwick tree , Suffix tree and Suffix Automata .segment tree and fenwick tree are very useful when range queries need to be done efficiently.Suffix tree and automata can solve various types of string based problems.Hence , these are very much used in modern world.Hence this project increases the demand for the intrusive library.Every data structure can only solve problems with particular characteristics and it cannot solve or the performance is bad when the same data structure is used for other types of problems.So, one has to select correct data structure.</p>

<p>When analyzing performance, especially in systems that have multi-core processors, it is important to be able to study how each process performs. To do this we use measures such as total processing time, I/O waiting time, and blocked time. In order to understand better the inner workings of the process scheduling algorithm used and their performance we also need to know why certain processes get blocked, what causes them to be blocked and when they are blocked. The purpose of this project is to integrate these measuring tools into Performance Co-Pilot’s pcp-pidstat utility.</p>

<p>A proposal for developing GUI for generating configuration files for GNSS-SDR receiver. The project will deliver a friendly and intuitive GUI for the users.</p>

This project enhances FLOSS by integrating QUANTUMSTRAND’s context-aware rendering to make malware string analysis faster and more actionable. Instead of overwhelming analysts with raw strings, the improved tool will use structural context, tagging (e.g., libraries, APIs, expert rules), and prevalence to highlight important information while muting noise.

My project aims to develop an immersive Augmented Reality (AR) Marine Ecosystem Simulation that will serve as an interactive educational tool within Catrobat's ecosystem. This simulation will allow users to explore marine environments through AR technology, visualizing complex ecological interactions such as food chains, coral reef dynamics, and the impacts of pollution in real-time. The primary challenge lies in creating a physically accurate, engaging simulation that runs efficiently on mobile devices while maintaining educational value. I propose to solve this by: - Developing a modular AR framework using Unity that integrates with ARKit and ARCore - Implementing realistic physics-based interactions between marine organisms - Creating an adaptive AI system that evolves the ecosystem based on user interactions - Designing intuitive interfaces that make complex ecological concepts accessible The project will deliver: - A fully functional AR marine ecosystem simulation compatible with Catrobat's existing applications - A library of interactive marine organisms with realistic behaviors and interactions - Real-time visualization tools for environmental factors (temperature, pH, pollution) - Educational scenarios demonstrating ecological principles - Comprehensive documentation and integration guides

<p>For GSoC2017, I intend to use the Shogun library on health data and show the usefulness of machine learning in applications that could save people's lives and benefit society. More specifically, I want to focus on analyzing health data for applications such as clinical decision support and mortality prediction. The dataset I will work with is the MIMIC database, which is comprised of information relating to patients admitted to the ICU at a large hospital. The data mainly includes demographic, administrative, and clinical data from over 45,000 critical care patients. The project will be divided into two parts: In the first part, I plan to perform data cleaning and apply various machine learning algorithms on the MIMIC dataset for mortality prediction, predict the risk of developing certain diseases, determine the effectiveness of certain drugs, and more. In the final part, I will explore more novel methods like LSTMs to exploit the time-series data. Recent research has shown good results of using deep learning on electronic health records.</p>

<p>Release-bot helps upstream maintainers deliver their software to users, via automated releases at GitHub and PyPI. However, release-bot can be smarter in many ways. The workflow of the bot would be much easier if we create Github app and get rid of some bothering configuration. In the current state release-bot work with Github releases, one of the possible improvements is to extend functionalities for more git forges as pagure.io which is used by many projects in Fedora world. Also, release-bot can work with a single project at one time, let’s change it.</p>

This project aims to implement a Vector Tracking Loop (VTL) architecture in GNSS-SDR, a widely used open-source software-defined GNSS receiver. Traditional scalar tracking architecture tracks satellite signals independently, limiting robustness in dynamic or degraded signal environments. In contrast, VTL integrates tracking and navigation tasks into a single algorithm, where all channels collaborate to enhance signal tracking performance, particularly under challenging conditions such as interference or temporary outages. The proposed work will design and integrate a modular, configurable VTL architecture supporting multi-constellation and multi-frequency operation, aligning with the existing capabilities of GNSS-SDR. Deliverables include: VTL algorithm implementation, real-time feedback to tracking channels, multi-constellation and multi-frequency support, benchmarking, and documentation. This contribution will enable researchers and developers to explore advanced GNSS techniques related to the VTL architecture within a real-time, open-source SDR.

This project aims to extend Rizin's OOP binary analysis capabilities across multiple languages. It completes support for Objective-C and Swift binaries, and introduces support for Rust and Java, focusing on vtable detection, devirtualization, and inheritance graph reconstruction. It also adds Windows Structured Exception Handling for both x86 and x64. Demanglers for Swift and D will be integrated into rz-libdemangle.

<p>Boost.Real aims at providing a data-type that can represent all types of computable real numbers and provides the flexibility of performing arbitrary precision arithmetic, the user can always decide and control the amount of precision to be used for a calculation thus controlling the computational power used by the machine. I propose to benchmark the library and compare it against other similar libraries. There is a scope of optimization for Trigonometric functions and performance can be improved by a significant amount. I also plan for several other small optimizations</p>

<p>This project involves developing a new library which tries to cover the major concepts of a complex and diverse field of Astronomy. This library will provide functionalities to mitigate the complexities of astronomical calculations using C++.</p> <p><strong>1) Celestial Coordinate System:</strong><br> For any Astronomical observation, it is essential to know the location of any object on the celestial sphere. These classes will provide functionalities (e.g.: find sun, find the moon, the angular separation between two points in the sky, find the constellation of coordinate, conversion from cartesian coordinates to spherical polar coordinates and vice versa, etc.) for using different coordinate systems, process them for different purposes and convert them into each other.</p> <p><strong>2) Handling FITS (Flexible Image Transport System) File:</strong><br> This library will provide functionality for reading, manipulating and verifying file which can further be used for other processes like making light curves or spectroscopy. It will deal with data unit consisting of 8 bit, 16 bit and 32 bit also. It will also provide functionality for converting the normal image to FITS and applying Astrometry to find positions of objects in the data unit</p>

The goal of this project is to add the JSON_* functions support in Select Handler mode. After the project, we can use json function with Columnstore in Select Handler mode. We can design and implement JSON functions. My implementation idea is as follows(take the JSON_VALID function as example): ● Related files and classes: define the relevant files required by the JSON_VALID function according to the specification of the SQL function definition in Columnstore 1. functor_json.cpp: According to the return value of the function, create new class Func_json_valid derived from class Func_bool. 2. func_json_valid.cpp: the JSON_VALID function is implemented here. Implement any other methods that behave differently from the default. 3. funcexp.{h,cpp}: in FuncExp::FuncExp(), add a new entry fFuncMap["json_valid"] = new Func_json_valid(). 4. CMakeLists.txt: Add any source files to build. ● Borrow and translate: 1. JSON_* functions are already implemented in MariaDB leveraging its own JSON format parser 2. The parser itself is couple files only library. Here is the main file. 3. So the next step is to read/understand this implementation and translate the code into Columnstore using the mentioned JSON format parser.

<p>The primary goal of this project is to build a native PCP MMV instrumentation library in Rust with a high-level API that developers can use in their applications to report arbitrary metrics at runtime. Metrics will be written out in the Memory Mapped Values format v1/2, which can then be read by a Performance Metric Domain Agent. Sub-goals include building a Rust API and command line utility to dump metrics from an MMV file, and examples of embedding the MMV instrumentation library inside popular Rust projects (such as Iron and Hyper).</p>

<p>Now in MariaDB if in a query [NOT] IN predicate is used with a long list of values, SEL_TREE structures are built to check if the range access based on this predicate can be used. Building SEL_TREE structures takes a huge amount of memory. In this case it will be better to transform the predicate into [NOT] IN subquery with built over the list of values in its FROM list.</p> <p>This project includes addition of to SQL of MariaDB and implementation of the above-mentioned transformation.</p>

<p>Tensors provide a natural and compact representation for massive multidimensional data with a high dimensionality which occur in disciplines like computational neuroscience, neuroinformatics, pattern/image recognition, signal processing and machine learning. My tensor project proposal is based on the foundations Boost’s uBlas implementation and focuses on extending uBLAS by a tensor and tensor operations. The extension shall primarily support dense tensors that can be projected on subtensors with ranges or slices. I also want to provide expressions templates for basic tensors operations using static polymorphism with generic lambdas. The library shall support all basic multilinear algebra operations such as the modal tensor contractions and tensor transpositions. Tensor object shall be able to communicate with Boost’s matrix and vector objects through expression templates and free functions. Repeating the primary design goals of uBlas, the tensor library shall be efficient with almost no abstraction penalties, functional, compatible and provide a convenient mathematical notation.</p>

Indigo Night is planned to be a beautiful Audio Visual journey, focused on storytelling. Based on pixel art, it will contain retro vibes and an old school style, which is immensely trending as of today. Salient features of this project include: Smooth Animations, Multiple Playable Characters, Beautiful environments as well as a musical delivery of several elements. Overall, I aim to create a groundbreaking modern experience in the Luna&Cat IDE app, by bringing together all those hours I invested into 2D games, indie as well as mainstream, and the game design experience I have, in Unity and RPG Maker.

<p>Goal of this project is to improve and build upon existing Grafana intergration for Performance Co-Pilot.</p> <ul> <li>Developing a <strong>reactive dashboard</strong> and using PCP metrics</li> <li>Implementing support for PCP <strong>derived metrics</strong> in the Vector data source, as described in the PCP REST API documentation</li> <li>Improving the <strong>metric search</strong> process by creating a new page for live, full-text search on PCP metric names, instances, instance domains and their descriptions, if any</li> </ul> <p>Based on performance metrics from PCP and a predefined rule set, the <strong>reactive dashboard</strong> should display only relevant metrics to the user. For example, if the CPU utilization is high, it should show an overview of CPU statistics and processes contributing load. The user should then be able to drill down into more specific areas of interest - e.g. present graphs about lock contention. For each recognized performance issue a link should be presented to the user on how to resolve the issue. In this way the dashboards guide users toward possible root cause of performance problems.</p>

<p>To implement the dataframes library for uBLAS using Expression Templates and Meta-programming paradigm in C++ that is capable of doing simple manipulations with data sets. It requires studying the existing implementations (data.table/data.frame in R and Pandas in Python) and analyzing the limitations (that occur due to template meta-programming paradigm) and possible optimisations (instantiation of type parameters which is not possible in R and python because of generic implementation of data.frame).</p>

<p>Add support for timeless debugging in r2. This requires r2 to create tracing session and read, write memory at any moment in tracing sessions. Same for registers.<br> Add new reverse execution commands, like ‘dsb’, that may read previous tracing sessions, and seek program counter to backward. And moreover, r2 should load recorded tracing sessions from tools like, rr or QIRA.</p>

The FLOSS: Language Specific Strings project aims to enhance the FLARE tool called FLOSS, which is used to deobfuscate protected strings found in malware. The proposed framework will extract language and runtime-specific strings from executables. The project will develop a language identification module, with initial focus on Go and Rust. We will research language string embeddings and create extractor code, leveraging existing knowledge and code to bootstrap this. The project will identify strings related to runtime and library code for targeted programming languages and extend standard output format to render the results. The successful completion of this project will make FLOSS more useful for security analysts and manifest its success as the default tool used for malware analysis.

<p>Signal intelligence describes the gathering of information out of intercepted radio signals with unknown origin and unknown parameters. GNU Radio has already the ability to do signal intelligence, but it is only possible through some detours. Real-time signal intelligence is hardly possible. The tool <code>gqrx</code> has some of this ability (real-time AM/FM demodulation), but there is no final solution for this problem at this time. The target of this project is to develop an easily accessible and extendible solution for this workflow including automatic signal detection and automatic modulation classification. Further deliverables are a radio service allocation database, blind synchronization methods and an automatic demodulation block.</p>