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In this paper, we focus on ultra-dense network modelingwhere both the Base Stations (BSs) and Mobile Terminals(MTs) are UAVs. In this case, two communication nodes canbe very close to each other. However, existing cellular networkanalyses typically use the standard unbounded path loss modelwhere received power decays like r^beta over a distance r. Thisstandard model is a good approximation for the
Ice multiplication by fragmentation during collision-freezing of supercooled rain or drizzle is investigated. A zero-dimensional dynamical system describes the time evolution of number densities of supercooled drops and ice crystals in a mixed-phase cloud. The characteristic time scale for this collision-freezing ice fragmentation is controlled by the collision efficiency, the number of ice fragme
• The Arctic is continuing to warm faster than any other region on Earth, but key uncertainties remain in our knowledge of the Arctic carbon cycle. • We review the most current knowledge pertaining to estimates of arctic greenhouse gas components and discuss uncertainties associated with these measurements and models. • While the Arctic Ocean is consistently estimated as a carbon sink, we have yet
Recent advances have extended the scope of Bayesian optimization (BO) to expensive-to-evaluate black-box functions with dozens of dimensions, aspiring to unlock impactful applications, for example, in the life sciences, neural architecture search, and robotics. However, a closer examination reveals that the state-of-the-art methods for high-dimensional Bayesian optimization (HDBO) suffer from degr
A central challenge within pharmacometrics is to establish a relation between pharmacological model parameters, such as compartment volumes and diffusion rate constants, and known population covariates, such as age and body mass. There is rich literature dedicated to the learning of functional mappings from the covariates to the model parameters, once a search class of functions has been determine
Static checker frameworks support software developers by automatically discovering bugs that fit general-purpose bug patterns. These frameworks ship with hundreds of detectors for such patterns and allow developers to add custom detectors for their own projects. However, existing frameworks generally encode detectors in imperative specifications, with extensive details of not only what to detect b
Empirical software engineering research relies on good communication with industrial partners. Conducting joint research both requires and contributes to bridging the communication gap between industry and academia (IA) in software engineering. This study aims to explore communication between the two parties in such a setting. To better understand what facilitates good IA communication and what pr
We present a strategy for failure resilient cloud control using model predictive control (MPC) extended with explicit recovery. Based on an arbitrary and unmodified device controller, the remotely operated MPC can safely manipulate the network controlled plant through temporary adjustment of an error signal generator. We show ways to implement the reliable cloud controller, relate it to two-degree
Uppenbarelseboken avtäcker med sina fasansfulla syner – sin Apokalyps – vad som ska ske på den yttersta dagen, då allt ont ska förgås och ett nytt rike ska upprättas. Men numera menas ofta med apokalyps enbart den skräckfyllda, mytologiska spådomen om en framtida katastrof. Kan man istället förstå Uppenbarelsebokens syner som en varning, för den katastrof vi själva är med om att skapa här och nu,
Bayesian Optimization has emerged as a crucial technique for optimizing costly, black-box functions where each evaluation comes at a high cost, such as in scientific experiments, and machine learning hyperparameter optimization. By combining probabilistic modeling with sequential decision-making, Bayesian Optimization achieves efficient exploration, guiding the search toward optimal parameters wit
This thesis explores the challenges and advancements in high-dimensional Bayesian optimization (HDBO), focusing on understanding, quantifying, and improving optimization techniques in high-dimensional spaces.Bayesian optimization (BO) is a powerful method for optimizing expensive black-box functions, but its effectiveness diminishes as the dimensionality of the search space increases due to the cu
In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on Lie groups. Our idea is to view the manifold as a constrained set that is embedded in Euclidean space, and then propose the sufficient conditions for the existence of a CCM and the associated controller design. Nota
Incumbent firms face growing pressure to transform their business towards sustainability. However, business models for sustainability (BMfS) and circularity are grounded in fundamentally different institutional logic which, for incumbents, creates tensions with existing business models, structures and routines. How organizations manage tensions from conflicting logics is explored comprehensively i
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and Audio (LuViRA) dataset, where all the sensors are synchronized and measured in the same environment. Some of the challenges of using each specific sensor for in
The LACIS Experiment in November (LExNo) campaign was conducted in November 2005 at the Atmospheric Composition Change the European Network of Excellence (ACCENT) site Leipzig Aerosol Cloud Interaction Simulator (LACIS). The goal of LExNo was to provide deeper insight into the activation properties of coated soot particles imitating aged combustion aerosol particles. The aerosols were prepared by
Due to increased urbanisation, and climate change, there have been calls for a more sustainable management of stormwater. Blue-green measures have been recognised as a sustainable solution and a necessary complement to pipe-bound approaches. The aim of this study is to identify barriers and drivers in the implementation of blue-green measures in a Swedish context, to increase the understanding of
The likelihood and magnitude of the impacts of climate change on potential vegetation and the water cycle in Mesoamerica is evaluated. Mesoamerica is a global biodiversity hotspot with highly diverse topographic and climatic conditions and is among the tropical regions with the highest expected changes in precipitation and temperature under future climate scenarios. The biogeographic soil-vegetati
This paper presents an adaptive video encoder that can be used to compare the behavior of different adaptation strategies using multiple actuators to steer the encoder towards a global goal, composed of multiple conflicting objectives. A video camera produces frames that the encoder manipulates with the objective of matching some space requirement to fit a given communication channel. A second obj
The number of ice fragments generated by breakup of large graupel in collisions with small graupel fluctuates randomly owing to fluctuations in relative sizes and densities of colliding graupel particles and the stochastic nature of fracture propagation. This paper investigates the impact of the stochasticity of breakup on ice multiplication. When both the rate of generation of primary ice and the
