Related papers: Enabling Cross-Language Data Integration and Scala…

There has been an unprecedented surge in the number of service providers offering a wide range of machine learning prediction APIs for tasks such as image classification, language translation, etc. thereby monetizing the underlying data and…

The rapid growth of memory and computation requirements of large language models (LLMs) has outpaced the development of hardware, hindering people who lack large-scale high-end GPUs from training or deploying LLMs. However, consumer-level…

The growing interconnection between software systems increases the need for security already at design time. Security-related properties like confidentiality are often analyzed based on data flow diagrams (DFDs). However, manually analyzing…

As the demand grows for scalable and privacy-aware AI systems, Federated Learning (FL) has emerged as a promising solution, allowing decentralized model training without moving raw data. At the same time, the combination of high-performance…

A detailed exploration of blockchain technology and its applications across various fields is provided, beginning with an introduction to cryptography fundamentals, including symmetric and asymmetric encryption, and their roles in ensuring…

While several attempts have been made to construct a scalable and flexible architecture for analysis of streaming data, no general model to tackle this task exists. Thus, our goal is to build a scalable and maintainable architecture for…

Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used,…

Dependency analysis is recognized as an important field of software engineering due to a variety of reasons. There exists a large pool of tools providing assistance to software developers and architects. Analysis of inter- and intra-project…

The deployment of large-scale models, such as large language models (LLMs), incurs substantial costs due to their computational demands. To mitigate these costs and address challenges related to scalability and data security, there is a…

In the rapidly evolving landscape of GameFi, a fusion of gaming and decentralized finance (DeFi), there exists a critical need to enhance player engagement and economic interaction within gaming ecosystems. Our GameFi ecosystem aims to…

Effective risk management solutions become absolutely crucial when financial markets embrace distributed technology and decentralized financing (DeFi). This study offers a thorough survey and comparative analysis of the integration of…

Large scale cloud services use Key Performance Indicators (KPIs) for tracking and monitoring performance. They usually have Service Level Objectives (SLOs) baked into the customer agreements which are tied to these KPIs. Dependency…

IntraLayer presents an innovative framework that enables comprehensive interconnectivity in digital finance. The proposed framework comprises a core underlying infrastructure and an overarching strategy to create a pioneering "platform of…

Data-intensive systems handle variable, high volume, and high-velocity data generated by human and digital devices. Like traditional software, data-intensive systems are prone to technical debts introduced to cope-up with the pressure of…

Considering the market's competitiveness and the complexity of organizations and projects, analyzing data is crucial to decision support on software development and project management processes. These practices are essential to increase…

The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector. Financial data is often embedded in intricate relationships across…

Low-code application development as proposed by the OutSystems Platform enables fast mobile and desktop application development and deployment. It hinges on visual development of the interface and business logic but also on easy integration…

Modern cryptocurrencies exploit decentralised blockchains to record a public and unalterable history of transactions. Besides transactions, further information is stored for different, and often undisclosed, purposes, making the blockchains…

Deep learning has shown remarkable results on Euclidean data (e.g. audio, images, text) however this type of data is limited in the amount of relational information it can hold. In mathematics we can model more general relational data in a…

The reliance of Large Language Models and Internet of Things systems on massive, globally distributed data flows creates systemic security and privacy challenges. When data traverses borders, it becomes subject to conflicting legal regimes,…