Related papers: Flexible Educational Software Architecture
Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not…
E-learning is nowadays one of the most interesting of the "e- " domains available through the Internet. The main problem to create a Web-based, virtual environment is to model the traditional domain and to implement the model using the most…
The university management is perpetually in the process of innovating policies to improve the quality of service. Intellectual growth of the students, the popularity of university are some of the major areas that management strives to…
As large pre-trained language models become increasingly critical to natural language understanding (NLU) tasks, their substantial computational and memory requirements have raised significant economic and environmental concerns. Addressing…
A freely available educational application (a mobile website) is presented. This provides access to educational material and drilling on selected topics within mathematics and statistics with an emphasis on tablets and mobile phones. The…
This paper proposes Edge-FIT (Federated Instruction Tuning on the Edge), a scalable framework for Federated Instruction Tuning (FIT) of Large Language Models (LLMs). Traditional Federated Learning (TFL) methods, like FedAvg, fail when…
This paper formalises the literature on emerging design patterns and paradigms for Large Language Model (LLM)-enabled multi-agent systems (MAS), evaluating their practical utility across various domains. We define key architectural…
Currently, organizations are transforming their business processes into e-services and service-oriented architectures to improve coordination across sales, marketing, and partner channels, to build flexible and scalable systems, and to…
Microservice-based systems are often complex to understand, especially when their sizes grow. Abstracted views help practitioners with the system understanding from a certain perspective. Recent advancement in interactive data visualization…
Microservice Architecture (MSA) is a popular architectural style that offers many advantages regarding quality attributes, including maintainability and scalability. Developing a system as a set of microservices with expected benefits…
Modern ML methods excel when training data is IID, large-scale, and well labeled. Learning in less ideal conditions remains an open challenge. The sub-fields of few-shot, continual, transfer, and representation learning have made…
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…
Use of online platforms for education is a vibrant and growing arena, incorporating a variety of software platforms and technologies, including various modalities of extended reality. We present our Enhanced Reality Teaching Concierge, an…
The euphoria around microservices has decreased over the years, but the trend of modernizing legacy systems to this novel architectural style is unbroken to date. A variety of approaches have been proposed in academia and industry, aiming…
For efficiency reasons, the software system designers' will is to use an integrated set of methods and tools to describe specifications and designs, and also to perform analyses such as dependability, schedulability and performance. AADL…
Microservice applications are created as loosely coupled application components and they leverage cloud elasticity to reduce costs and increase development speed. However, microservice applications exhibit complex interactions among…
An application is a logical image of the world on a computer. A scalable application is an application that allows one to update that logical image at run time. To put it in operational terms: an application is scalable if a client can…
ML 2.0: In this paper, we propose a paradigm shift from the current practice of creating machine learning models - which requires months-long discovery, exploration and "feasibility report" generation, followed by re-engineering for…
Our entire society is becoming more and more dependent on technology and specifically on software. The integration of e-learning software systems into our day by day life especially in e-learning applications generates modifications upon…
Federated learning involves training machine learning models over devices or data silos, such as edge processors or data warehouses, while keeping the data local. Training in heterogeneous and potentially massive networks introduces bias…