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When it comes to innovation, economic growth, affluence and international attractiveness, there are currently few places in the world that can compare with the San Francisco Bay Area. However, new megatrends such as Sustainability, can challenge its attractiveness. Scholars talk about the “Nordic approach”.In the geographical area of Southern Scandinavia, ‘The Strait Area’, the focus is on Sustain

We study an information design problem to reduce congestion in transportation networks. In presence of an uncertain network state, the central planner may sends private signals to the users, with the goal of steering the user equilibrium towards the system optimum flow. We consider private signals and provide sufficient conditions under which optimality may be achieved by information provision in

We deal with a control problem for a complex social network in which each agent has an action and an opinion, evolving according to a coevolutionary model. In particular, we consider a scenario in which a committed minority - a set of stubborn nodes - aims to steer a population, initially at a consensus, to a different consensus state. Our study focuses on determining the conditions under which su

We consider the averaging process on an infinite connected graph with bounded degree and independent, identically distributed starting values or initial opinions. Assuming that the law of the initial opinion of a vertex has a finite second moment, we show that the opinions of all vertices converge in L2 to the first moment of the law of the initial opinions. A key tool in the proof is the Sharing

In this technical note, we introduce a novel approach to studying consensus of continuous-time nonlinear systems with varying topology based on Hilbert metric. We demonstrate that this metric offers significant flexibility in analyzing consensus properties, while effectively handling nonlinearities and time dependencies. Notably, our approach relaxes key technical assumptions from some standard re

With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary staging. This study employed advancements in deep learning to comprehensively evaluate routine mammograms for preoperative lymph node metastasis prediction. Mammograms and clinicopathological data from 1265 cN0 T1-T2 breast cancer patients (primary surge

The formation of platoons, where groups of vehicles follow each other at close distances, has the potential to increase road capacity. In this paper, a decentralized control approach is presented that extends the well-known constant headway vehicle following approach to the two-dimensional case, i.e., lateral control is included in addition to the longitudinal control. The presented control scheme

Variance-reduced stochastic gradient methods have gained popularity in recent times. Several variants exist with different strategies for storing and sampling gradients, and this work concerns the interactions between these two aspects. We present a general proximal variance-reduced gradient method and analyze it under strong convexity assumptions. Special cases of the algorithm include SAGA, L-SV

In this survey, we present the current status on robots performing manipulation tasks that require varying contact with the environment, such that the robot must either implicitly or explicitly control the contact force with the environment to complete the task. Robots can perform more and more manipulation tasks that are still done by humans, and there is a growing number of publications on the t

Engineering, in general, is a non-diverse profession around the globe. Women are one group of minorities in engineering. Despite the fact that control engineering is heavily based on mathematics, which has a larger number of female students, it has the same proportion of women as other engineering disciplines. To address the issue of low female participation in engineering disciplines both at univ

We present a new world-coordinate tracking algorithm for road users seen from static surveillance cameras, denoted GUTS. It is based upon the previously published UTS method but simplifies and replaces parts allowing association logic to work in world coordinates, by using a novel convolutional neural network denoted SAMHNet to convert every detection into world coordinates. Experimental evaluatio

Self-Adaptive Systems (SAS) and Cyber-Physical Systems (CPS) have received significant attention in recent computer engineering research. This is due to their ability to improve the level of autonomy of engineering artefacts. In both cases, this autonomy increase is achieved through feedback. Feedback is the iteration of sens- ing and actuation to respectively acquire knowledge about the current s

Microservice applications consist of a set of smaller services interacting in a graph structure to deliver the full application. Jobs will traverse this graph in different paths, both depending on the type of job, but also on the current load of different service replicas. Different paths will incur different scenario-specific costs, dependent on, e.g., deployment and the underlying cloud system.

In this paper, we explore the use of Reinforcement Learning (RL) to improve the control of cooling equipment in Data Centers (DCs). DCs are inherently complex systems, and thus challenging to model from first principles. Machine learning offers a way to address this by instead training a model to capture the thermal dynamics of a DC. In RL, an agent learns to control a system through trial-and-err

Optimization problems occur in many areas in science and engineering. When the optimization problem at hand is of large-scale, the computational cost of the optimization algorithm is a main concern. First-order optimization algorithms—in which updates are performed using only gradient or subgradient of the objective function—have low per-iteration computational cost, which make them suitable for t

Motivated by the novel coronavirus disease (COVID-19) pandemic, this paper aims to apply Gunter Stein's cautionary message of respecting the unstable to the problem of controlling the spread of an infectious disease. With this goal, we study the effect that delays and capacity constraints have in the test, trace, and isolate (TeTrIs) process, and how they impact its ability to prevent exponential

We describe the design and implementation of a new constraint programming solver that can produce an auditable record of what problem was solved and how the solution was reached. As well as a solution, this solver provides an independently verifiable proof log demonstrating that the solution is correct. This proof log uses the VeriPB proof system, which is based upon cutting planes reasoning with

Free-energy calculations are crucial for investigating biomolecular interactions. However, in theoretical studies, the neglect of electronic polarization can reduce predictive capabilities, specifically for free-energy calculations. To effectively mimick polarization, we explore a Charge Switching (CS) model, aiming to narrow the gap between computational and experimental results. The model requir