SC Harvester Papers Database Interface

Exploiting Meta-Model Structures in the Generation of Xtext Editors

Jörg Holtmann, J. Steghöfer, Wei-Xing Zhang. In: . 2023

Abstract: : When generating textual editors for large and highly structured meta-models, it is possible to extend Xtext’s generator capabilities and the default implementations it provides. These extensions provide additional features such as formatters and more precise scoping for cross-references. However, for large metamodels in particular, the realization of such extensions typically is a time-consuming...

Optimizing Parallel Task Execution for Multi-Agent Mission Planning

Branko Miloradovic, Baran Curuklu, Mikael Ekstrom, A. Papadopoulos. In: IEEE Access. 2023

Abstract: Multi-agent systems have received a tremendous amount of attention in many areas of research and industry, especially in robotics and computer science. With the increased number of agents in missions, the problem of allocation of tasks to agents arose, and it is one of the most fundamental classes of problems in robotics, formally known as the Multi-Robot Task Allocation (MRTA) problem. MRTA encap...

Comparing Anomaly Detection and Classification Algorithms: A Case Study in Two Domains

M. Staron, H. O. Hergés, Linda Block, M. Sjödin. In: . 2023

Role of Data in the Building of Legitimacy for Green Bonds - Capturing, Contextualizing, and Communicating

Olgerta Tona, Yixin Zhang, Aleksandre Asatiani, Juho Lindman. In: . 2023

Design Principles for Blockchain-based Applications in Green Bond Reporting

A. Darwish, Juho Lindman, Jesper Hjertqvist, Olgerta Tona. In: . 2023

Abstract: Emerging sustainable capital markets are crucial in reaching global climate goals. These markets’ credibility depends on the trustworthiness of data used to report the green impact of projects financed by sustainable financial instruments such as green bonds. To ensure credibility and thereby support these types of markets, the information systems field has the potential to create designs that lev...

An Empirical Evaluation of System-Level Test Effectiveness for Safety-Critical Software

M. Zafar, Wasif Afzal, Eduard Paul Enoiu. In: . 2023

Abstract: : Combinatorial Testing (CT) and Model-Based Testing (MBT) are two recognized test generation techniques. The evidence of their fault detection effectiveness and comparison with industrial state-of-the-practice is still scarce, more so at the system level for safety-critical systems, such as those found in trains. We use mutation analysis to perform a comparative evaluation of CT, MBT, and industr...

Requirement or Not, That is the Question: A Case from the Railway Industry

Sarmad Bashir, Muhammad Abbas, Mehrdad Saadatmand, Eduard Paul Enoiu, Markus Bohlin et al. In: . 2023

Assessing Risk of Ar and Organizational Changes Factors in Socio-Technical Robotic Manufacturing

Soheila Sheikh Bahaei, Barbara Gallina. In: SSRN Electronic Journal. 2023

A Modular Ice Cream Factory Dataset on Anomalies in Sensors to Support Machine Learning Research in Manufacturing Systems

Tijana Markovic, M. Leon, B. Leander, S. Punnekkat. In: IEEE Access. 2023

Abstract: A small deviation in manufacturing systems can cause huge economic losses, and all components and sensors in the system must be continuously monitored to provide an immediate response. The usual industrial practice is rather simplistic based on brute force checking of limited set of parameters often with pessimistic pre-defined bounds. The usage of appropriate machine learning techniques can be ve...

A Compositional Approach to Creating Architecture Frameworks with an Application to Distributed AI Systems

H. Heyn, E. Knauss, Patrizio Pelliccione. In: J. Syst. Softw.. 2022

Abstract: Artificial intelligence (AI) in its various forms finds more and more its way into complex distributed systems. For instance, it is used locally, as part of a sensor system, on the edge for low-latency high-performance inference, or in the cloud, e.g. for data mining. Modern complex systems, such as connected vehicles, are often part of an Internet of Things (IoT). To manage complexity, architectu...

Evaluating Edge Computing and Compression for Remote Cuff-Less Blood Pressure Monitoring

Ward Goossens, Dino Mustefa, Detlef Scholle, H. Fotouhi, J. Denil. In: J. Sens. Actuator Networks. 2022

Abstract: Remote health monitoring systems play an important role in the healthcare sector. Edge computing is a key enabler for realizing these systems, where it is required to collect big data while providing real-time guarantees. In this study, we focus on remote cuff-less blood pressure (BP) monitoring through electrocardiogram (ECG) as a case study to evaluate the benefits of edge computing and compress...

Emulating future neurotechnology using magic

Jay A. Olson, Marie-Andree Cyr, Despina Z Artenie, Thomas Strandberg, L. Hall et al. In: Consciousness and Cognition. 2022

Emulating future neurotechnology using magic.

Jay A. Olson, Marie-Andree Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall et al. In: Consciousness and cognition. 2022

Abstract: Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their react...

Emulating future neurotechnology using magic.

Jay A. Olson, Marie-Andree Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall et al. In: Consciousness and cognition. 2022

Abstract: Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their react...

Industry Best Practices in Robotics Software Engineering

Robert L. Bocchino, Arne Nordmann, A. Thackston, A. Angerer, Federico Ciccozzi et al. In: ArXiv. 2022

Abstract: Robotics software is pushing the limits of software engineering practice. The 3rd International Workshop on Robotics Software Engineering held a panel on “the best practices for robotic software engineering”. This article shares the key takeaways that emerged from the discussion among the panelists and the workshop, ranging from architecting practices at the NASA/Caltech Jet Propulsion Laboratory,...