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Interesting approaches to counteract performance variability within cloud datacenters include sending multiple request clones, either immediately or after a specified waiting time. In this paper we present a performance model of cloud applications that utilize the latter concept, known as speculative execution. We study the popular Join-Shortest-Queue load-balancing strategy under the processor sh
Control systems can be vulnerable to security threats where an attacker gathers information about the execution of the system. In particular, side-channel attacks exploit the predictability of real-time control systems and of their schedules. To counteract their action, a scheduler can randomize the temporal execution of tasks and limit the amount of information the attacker can gather. Schedule r
As the Arctic warms, vegetation is responding, and satellite measures indicate widespread greening at high latitudes. This ‘greening of the Arctic’ is among the world’s most important large-scale ecological responses to global climate change. However, a consensus is emerging that the underlying causes and future dynamics of so-called Arctic greening and browning trends are more complex, variable a
Just like current software systems, conceptual models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated, validated and serialized. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform incremental analysis e
Event-based sampling has been proposed as a general technique for lowering the average communication rate, energy consumption and computational burden in remote state estimation. However, the design of the event trigger is critical for good performance. In this paper, we study the combination of innovation-based triggering and state estimation of nonlinear dynamical systems using the particle filt
Efficient unit propagation for clausal constraints is a core building block of conflict-driven clause learning (CDCL) Boolean satisfiability (SAT) and lazy clause generation constraint programming (CP) solvers. Conflict-driven pseudo-Boolean (PB) solvers extend the CDCL paradigm from clausal constraints to integer linear constraints, also known as (linear) PB constraints. For PB solvers, many diff
Context: The changes that are taking place with respect to environmental sensitivity are forcing organizations to adopt a new approach to this problem. Implementing sustainability initiatives has become a priority for the social and environmental awareness of organizations that want to stay ahead of the curve. One of the business areas that has, more than others, proven to be a vital asset and a p
The prevalence of Artificial Intelligence (AI) in the business landscape is indisputable. However, there are considerable gaps between the visionary ideas businesses communicate and their operational use of AI. The goal of this market survey is to identify companies currently working with AI in the Øresund Region - referred to as AI companies. The survey, conducted between June and September 2020,
The Eurasian (née European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary arch
Software engineering research aims to help improve real-world practice. With the adoption of empirical software engineering research methods, the understanding of real-world needs and validation of solution proposals have evolved. However, the philosophical perspective on what constitutes theoretical knowledge and research contributions in software engineering is less discussed in the community. I
Turbulent fluxes make a substantial and growing contribution to the energy balance of ice surfaces globally, but are poorly constrained owing to challenges in estimating the aerodynamic roughness length (z0). Here, we used structure from motion (SfM) photogrammetry and terrestrial laser scanning (TLS) surveys to make plot-scale 2-D and 3-D microtopographic estimations of z0 and upscale these to ma
Background and objective: New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limit
Deep learning has proven itself to be a powerful tool to develop datadriven signal processing algorithms for challenging engineering problems. By learning the key features and characteristics of the input signals instead of requiring a human to first identify and model them, learned algorithms can beat many human-made algorithms. In particular, deep neural networks are capable of learning the comp
The damping ratio is a key performance measure in systems that can be modelled as networks of masses and springs. We derive a lower bound on this quantity that applies to such networks when the masses are subject to viscous damping. The result allows the size of the damping ratio to be understood as a function of the system parameters. We use this to derive a decentralised criterion which, if sati
Background: Despite the mutual benefit of the industry-academia partnership, the level of joint work is still low. For this reason, the interest in connecting research and practice has increased recently in the academic community. Objective: This research aims to design and apply approaches to improve the knowledge exchange between academic researchers and software engineering practitioners. Metho
Automated consistent software updating is challenging for distributed internet-of-things applications. We are developing a solution based on allowing several versions of the software to coexist on the same device, so that new and old software can be gradually phased in and out. We demonstrate our solution using a smart-city application for preventing thefts of bike batteries.
A technique for enhancing the bandwidth of a broadside tri-modal patch antenna is described. The key idea of the technique is to incorporate a dual-resonance structure into the broadside tri-modal patch geometry. By increasing one edge of the tri-modal patch while decreasing its size at the opposite edge, the resulting structure can be viewed as two super-imposed Y-shaped structures of different r
Background: Open innovation highlights the potential benefits of external collaboration and knowledge-sharing, often exemplified through Open Source Software (OSS). The public sector has thus far mainly focused on the sharing of Open Government Data (OGD), often with a supply-driven approach with limited feedback-loops. We hypothesize that public sector organizations can extend the open innovation
