Maximising student engagement in higher education requires more than traditional lecture methods; it requires the integration of interactive virtual tools that foster active learning. With increasing shifts towards blended and online learning environments, there is a growing need for innovative educational technologies to enhance interactivity and student involvement. This study investigates the impact of audience response systems and tools within virtual learning environments (VLEs) on student engagement within a blended learning context. Data were collected from two Engineering modules - a first-year Mathematics module and a final-year Software Project Management module - capturing distinct cohorts and learning objectives. The first-year course focuses on developing foundational analytical skills, while the final-year course emphasises higher-order skills such as critical thinking and problem-solving. Using a mixed-methods approach, this study combines quantitative metrics (participation frequency, interaction types, participation rates, and temporal patterns) with qualitative insights (interaction dynamics) to examine student engagement and how students across these academic levels interact with these virtual tools. Results indicate that platforms, such as Padlet and Kahoot!, can effectively engage students who may be less active in traditional classroom settings, while chat-enabled lectures facilitate immediate feedback and active learning, creating opportunities for deeper engagement. The findings highlight both the strengths and limitations of these tools providing for educators in engineering and related disciplines with insights and strategies for implementing virtual tools to enhance student engagement. By embracing these technologies, educators can create inclusive, interactive experiences adapted to suit the diverse needs and learning preferences of students.

This article proposes a user-adaptable and personalized authentication paradigm for healthcare organizations, which anticipates to seamlessly reflect patients’ episodic and autobiographical memories to graphical and textual passwords aiming to improve the security strength of user-selected passwords and provide a positive user experience. We report on a longitudinal study that spanned over 3 years in which three public European healthcare organizations participated to design and evaluate the aforementioned paradigm. Three studies were conducted ( n = 169) with different stakeholders: (1) a verification study aiming to identify existing authentication practices of the three healthcare organizations with diverse stakeholders ( n = 9), (2) a patient-centric feasibility study during which users interacted with the proposed authentication system ( n = 68), and (3) a human guessing attack study focusing on vulnerabilities among people sharing common experiences within location-aware images used for graphical passwords ( n = 92). Results revealed that the suggested paradigm scored high with regard to users’ likeability, perceived security, usability, and trust, but more importantly it assists the creation of more secure passwords. On the downside, the suggested paradigm introduces password guessing vulnerabilities by individuals sharing common experiences with the end users. Findings are expected to scaffold the design of more patient-centric knowledge-based authentication mechanisms within today's dynamic computation realms.

Modern technologies of integrated circuits allow billions of transistors arranged into a single chip, enabling to implement complex systems, which need a scalable and parallel communication architecture. Network-on-Chip (NoC) is a natural candidate to fulfill such communication requirements, providing high performance when the communication demands are balanced. This work proposes a new static balancing method that uses the application's traffic pattern for NoC latency reduction. This method allows the generation of a deterministic routing algorithm with simplistic implementation and low latency. Experimental results compare four balancing methods, showing the improvement of the proposed static balancing concerning the average NoC latency.

Measuring productivity in globally distributed projects is crucial to improve team performance. These measures often display information on whether a given project is moving forward or starts to demonstrate undesired behaviors. In this paper we are interested in showing how analytical models could deliver insights for the behavior of specific distributed software collaboration projects. We present a model for distributed projects using stochastic automata networks (SAN) formalism to estimate, for instance, the required level of coordination for specific project configurations. We focus our attention on the level of interaction among project participants and its close relation with team’s productivity. The models are parameterized for different scenarios and solved using numerical methods to obtain exact solutions. We vary the team’s expertise and support levels to measure the impact on the overall project performance. As results, we present our derived productivity index for all scenarios and we state implications found in order to analyze popular preconceptions in GSD area, confirming some, and refusing others. Finally, we foresee ways to extend the models to represent more intricate behaviors and communication patterns that are usually present in globally distributed software projects.

Networks-on-chip (NoCs) are already a common choice of communication infrastructure for complex systems-on-chip (SoCs) containing a large number of processing resources and with critical communication requirements. A NoC provides several advantages, such as higher scalability, efficient energy management, higher bandwidth and lower average latency, when compared to bus-based systems. Experiments with applications running on NoCs with more than 10% of bandwidth usage show that most of a typical message latency refers to buffered packets waiting to enter the NoC, while the latency portion that depends on packets traversing the NoC is often negligible. This work proposes a Monitored NoC called MoNoC, which is based on a monitoring mechanism and on the exchange of high-priority control packets. Practical experiments show that our fast adaptation method enables transmitting packets with smaller latencies, by using non-congested NoC areas, which reduces the most significant part of message latency.

The advances in deep submicron technology have made the development of large Multiprocessor Systems-on-Chip (MPSoC) possible and Networks-on-Chip (NoCs) have been recognized to provide an efficient communication architecture for such systems. With the positive effects on the device's integration some drawbacks arise, such as the increase of fault susceptibility during the MPSoC manufacturing and operation. This work presents Phoenix, which is a direct mesh NoC that implements fault tolerant mechanisms in order to enable end-to-end communication when some links fail. Phoenix implements a distributed fault tolerant mechanism in software (i.e. in each processor) and in hardware (i.e. in each router). Experimental results show that Phoenix is scalable and allows the MPSoC operation even in the presence of several faulty links.

The emergence of wireless networks has contributed to a growing number of studies and protocols regarding its performance and reliability requirements, among others. Several issues have to be considered when deploying such devices under harsh environmental conditions. These issues often force the designer to adopt decisions that are usually difficult to verify in real world settings. In order to mitigate such problems, an alternative resides in the use of simulation models for both homogeneous and heterogeneous devices. This paper describes an event-based Wireless Network Simulator (WiNeS) for devices operating in several topologies and configurations of networks. WiNeS is a Java-based framework specially built to support customized network options that offers hybrid simulation for virtual and physical nodes in the same environment. Some of WiNeS' features include the computation of maximum communication distances among devices in 2D and 3D spatial node distributions as well as pairing rules to evaluate the nodes connectivity.

Advances in design integration have enabled the integration of large Multiprocessor Systems-on-Chip (MPSoC). Such systems are prone to the execution of complex applications if high degree of parallelism is employed on the communication infrastructure. Network-on-Chip (NoC) has emerged as a new communication paradigm for large MPSoCs with advantages such as the increase of reliability on components interactions. However, device's integration may convey few shortcomings during MPSoC manufacturing and operation, for instance, the vulnerability to faults. This paper describes Phoenix, which is a direct mesh NoC with fault detection scheme. The proposed architecture explores a fault-tolerant mechanism, which is implemented in a distributed manner as a fault monitor on processors and routers. Results demonstrate that Phoenix can be scalable in view of the stabilization time regarding to faults incidence, allowing MPSoC operation even with the occurrence of a large number of faults.

3D NoC-based architectures have emerged to reduce the network latency, the energy consumption and total area in comparison to 2D NoC topologies. However, they are characterized by various trade-offs with regard to the three dimensional structure and its performance specifications. In this paper, we present a 3D NoC mesh architecture called Lasio, whose latency and the throughput achieved, for both network and application, are evaluated considering two types of traffic patterns, varied buffer depth and a range of packet sizes. Cycle-accurate simulations demonstrated that there is a high impact of buffer depth and packet size on the NoC latency and on the application latency. Applying an appropriate buffer depth, for several sizes of packets, the application latency is reduced and throughput is increased.

Global software engineering is an area of increasing research challenges, in which teams are dispersed in multiple sites collaborating across borders and time zones. In spite of its potential competitive advantages, globally distributed projects must deal with difficulties when distributing resources such as teams with cultural diversities, different skills and experience levels. Both industry and academia demonstrate a special interest in the modeling and prediction, mainly representing systems in order to extract interesting indices, for example, evaluating whether or not a project will succeed. This paper demonstrates the usefulness of analytical modeling techniques in order to predict the outcome of geographically-distributed projects. We focus our attention to the participants interaction and its interplay when it affects team productivity. The models are parametrized considering single-site and multi-site scenarios, varying resources availability, teams expertise and support levels. Performance indices from both scenarios are presented and conclusion indicates possible model extensions.

The solution of state-based stochastic models is usually a demanding application, then it is a natural subject to high performance techniques. We are particularly interested in the speedup of Bootstrap Simulation of structured Markovian models. This approach is a quite recent development in the performance evaluation area, and it brings a considerable improvement in the results accuracy, despite the intrinsic effect of randomness in simulation experiments. Unfortunately, Bootstrap Simulation has higher computational cost than other alternatives. We present experiments with different options to optimize the parallel solution of Bootstrap Simulation applied to three practical examples described in Stochastic Automata Networks (SAN) formalism. This paper contribution resides in the discussion of theoretical implementation issues, the obtained speedup and the actual processing and communication times for all experiments. Additionally, we also suggest future works to improve even more the proposed solution and we discuss some interesting insights for parallelization of similar applications.

New guidelines and methods for teams and organizational structures are crucial to improve efficiency and scalability for globally distributed software development. Our work introduces a simplified process to be used by local teams working globally. The process is derived from the Agile Unified Process proposal and is highly centered in team motivation using game principles