Related papers: PSI Draft Specification
Contracts are a well-established approach for describing and analyzing behavioral aspects of web service compositions. The theory of contracts comes equipped with a notion of compatibility between clients and servers that ensures that every…
Transfer learning (TL) for high-dimensional regression (HDR) is an important problem in machine learning, particularly when dealing with limited sample size in the target task. However, there currently lacks a method to quantify the…
Collaboration models and tools aim at improving the efficiency and effectiveness of human interactions. Although social relations among collaborators have been identified as having a strong influence on collaboration, they are still…
Service Function Chaining (SFC) is a networking technique that ensures traffic traverses a predefined sequence of service functions, realizing arbitrary network services through dynamic and efficient communication paths. Inspired by this…
Port scanning is the process of attempting to connect to various network ports on a computing endpoint to determine which ports are open and which services are running on them. It is a common method used by hackers to identify…
This paper presents the methodology for the system requirements and architecture w.r.t. their decomposition and refinement. It also introduces ideas of refinement layers and of refinement-based verification.
This report presents the design of the Scope infrastructure for extensible and portable benchmarking. Improvements in high- performance computing systems rely on coordination across different levels of system abstraction. Developing and…
The purpose of this paper is to address some of the challenges of formally specifying components of shared-memory concurrent programs. The focus is to provide an abstract specification of a component that is suitable for use both by clients…
This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different…
Research on decision support applications in healthcare, such as those related to diagnosis, prediction, treatment planning, etc., have seen enormously increased interest recently. This development is thanks to the increase in data…
Developments in artificial intelligence (AI) are likely to affect social engineering and change cyber defense operations. The broad and sweeping nature of AI impact means that many aspects of social engineering could be automated,…
Machine learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking emerge.…
Despite recent advances in machine learning and explainable AI, a gap remains in personalized preventive healthcare: predictions, interventions, and recommendations should be both understandable and verifiable for all stakeholders in the…
As more and more devices connect to Internet of Things, unbounded streams of data will be generated, which have to be processed "on the fly" in order to trigger automated actions and deliver real-time services. Spark Streaming is a popular…
The security features of current digital services are mostly defined and dictated by the service provider (SP). A user can always decline to use a service whose terms do not fulfill the expected criteria, but in many cases, even a simple…
The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine…
Senior project is a typical essential course in computing educational programs. The course involves the selection of a project problem, the submission of various documents, and intensive communication among the project team members and…
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…
We describe our ongoing research that centres on the application of natural language processing (NLP) to software engineering and systems development activities. In particular, this paper addresses the use of NLP in the requirements…
This master thesis describes an algorithm for automated categorization of scientific documents using deep learning techniques and compares the results to the results of existing classification algorithms. As an additional goal a reusable…