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The problem of planning a trajectory for robots starting in an initial state and reaching a final state in a desired interval of time is tackled. We consider Model Predictive Control as an approach to the problem of point-to-point trajectory generation. We use the developed strategy to generate trajectories for transferring the state of the robot, fulfilling computational real-time requirements. E

Douglas-Rachford splitting and the alternating direction method of multipliers (ADMM) can be used to solve convex optimization problems that consist of a sum of two functions. Convergence rate estimates for these algorithms have received much attention lately. In particular, linear convergence rates have been shown by several authors under various assumptions. One such set of assumptions is strong

During the last two decades a slow but steady change of external factors has set-up new conditions affecting the way in how software producing firms create and leverage innovations. Firms now need to look outside of their boundaries and start interacting with the open environment that encompasses them in order to stay innovative and keep a competitive advantage. To facilitate this shift Requiremen

Numerous tools automating various aspects of software engineering have been developed, and many of the tools are highly configurable through parameters. Understanding the parameters of advanced tools often requires deep understanding of complex algorithms. Unfortunately, suboptimal parameter settings limit the performance of tools and hinder industrial adaptation, but still few studies address the

Insulin therapy for tight glycemia regulation in T1DM strongly depends on patients ́ daily decisions about insulin delivery adaptations in relation to: health status, current BG, target BG, insulin sensitivity, diet and foreseen activities. A personalized predictor providing near future BG predictions would support the users in the decision-making tasks while letting them maintaining control over

The development of a predictive control algorithm for glycaemia regulation in diabetic subjects requires patient-specific models of the glucose metabolism which are physiologically relevant, parsimonious, yet able to accurately forecast blood glucose. Given the measured data: total plasma insulin [mIU/L]; plasma glucose [mg/dL]; plasma glucose rate of appearance after intestinal absorption [mg/kg

Project retrospectives can be a powerful tool for process improvement through obtaining new insights. However pure experience-based reflections may lead to incorrect conclusions. Our method, evidence-based timeline retrospectives (EBTR), mitigates this risk by providing a pre-generated timeline that visualises project history based on evidence rather than relying on subjective opinions and biased

Coordination is an important success factor for a development project. Communication gaps, e.g. between product owners shaping the requirements and testers verifying the developed software can result in wasted effort and unsuccessful products. We propose improving the communication between project members with recommendations of whom to interact with and what to discuss based on link prediction in

A feedback-based scheme for cooperative content distribu- tion for mobile systems aimed at reducing energy and li- censed spectrum usage is presented. The paper is motivated by the problems in implementing peer-to-peer based content distribution in mobile networks due to the risks of unfair en- ergy expenditure. A technique for incentivizing cooperation and for enforcing agreements between peers i

This note proposes a unified approach to analyse linear time-invariant consensus problems via the use of integral quadratic constraints (IQCs) without recourse to loop transformations, which may cloud the inherent structural properties of the multi-agent networked systems. The main technical hindrance to using IQCs lies in the presence of the marginally stable integral action in consensus setups.

The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Con

The interest in modelling, analysis and optimisation of supply chain structures has increased in the last decade. Among the reasons are globalisation, a general speed-up of the rate of change in the business environment, the trend towards more outsourcing of activities, and the rapid development in IT. This development has caused more and more people to realise the benefits of supply chain managem