Filtyp
This paper generalizes a propagation graph model to polarized indoor wireless channels. In the original contribution, the channel is modeled as a propagation graph in which vertices represent transmitters, receivers, and scatterers, while edges represent the propagation conditions between vertices. Each edge is characterized by an edge transfer function accounting for the attenuation, delay spread
We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals and the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust localization from radio signals is challenging due to diffuse multipath propagation, unknown MPC-feature association, and limited visibility of features. In our approach, specul
5G technologies present a new paradigm to provide connectivity to vehicles, in support of high data-rate services, complementing existing inter-vehicle communication standards based on IEEE 802.11p. As we argue, the specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning. Hence, 5G can work in synergy with existing on-vehicle positioning and mapp
The paper focuses on analysis of macro‐ and micromorphological characteristics of relict slope deposits in Serra da Estrela (Portugal) to understand the significance of different slope processes and paleoenvironmental settings. Micromorphology is a useful sedimentology technique allowing significant advances compared to macroscopic techniques. Results show that different processes are involved in
Background: Assessing and communicating software engineering research can be challenging. Design science is recognized as an appropriate research paradigm for applied research, but is rarely explicitly used as a way to present planned or achieved research contributions in software engineering. Applying the design science lens to software engineering research may improve the assessment and communic
Data-driven software is becoming prevalent, especially with the advent of machine learning and artificial intelligence. With data-driven systems come both challenges - to keep collecting and maintaining high quality data - and opportunities - open innovation by sharing data with others. We propose Open Data Collaboration (ODC) to describe pecuniary and non-pecuniary sharing of open data, similar t
Software developers use collection data structures extensively andare often faced with the task of picking which collection to use.Choosing an inappropriate collection can have major negativeimpact on runtime performance. However, choosing the right collectioncan be difficult since developers are faced with many possibilities,which often appear functionally equivalent. One approachto assist develo
We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative ref
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
