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Stream processing applications are naturally described as dataflow programs. Dataflow programs modelled as actor networks are well suited to describe concurrent and computationally intensive problems. Realistic dataflow programs are typically characterized by highly dynamic behaviour, limiting the applicability of static analysis techniques. In this work we explore using dynamic analyses of datafl

A unification of characteristic mode decomposition for all method-of-moment formulations of field integral equations describing free-space scattering is derived. The work is based on an algebraic link between impedance and transition matrices, the latter of which was used in early definitions of characteristic modes and is uniquely defined for all scattering scenarios. This also makes it possible

Quaternary Asian low-latitude hydroclimate cyclicity has long been attributed to insolation forcing, in contrast to the dominant ice-sheet and CO2 controls identified in mid-high-latitude regions. However, debates exist regarding these rainfall variations and forcings due to inconsistent reconstructions and simulations. Here, by combining rainfall proxy records with multi-model simulations, domina

This paper presents a four-stage algorithm for the realization of multi-input/multi-output (MIMO) switched linear systems (SLSs) from Markov parameters. In the first stage, a linear time-varying (LTV) realization that is topologically equivalent to the true SLS is derived from the Markov parameters assuming that the discrete states have a common MacMillan degree and a mild condition on their dwell

We train and compare the performance of two machine learning methods, a multi-variate regression network and a ResNet-50-based neural network, to learn and forecast plant biomass as well as the relative growth rate from a short sequence of temporal images from plants in aeroponic cultivation. The training dataset consists of images of 57 plants taken from two different angles every hour during a 5

We train and compare the performance of two different machine learning algorithms to learn changes in winter wheat production for fields from the southwest of Sweden. As input to these algorithms, we use cloud-penetrating Sentinel-1 polarimetry radar data together with respective field topography and local weather over four different years. We note that all of the input data were freely available.

This chapter gives an overview of key actions by the activist group Gender Relations in New Music, which advocates for increased gender equality and intersectional diversification in contemporary classical music (CCM). The chapter describes this particular group’s activities, which have included creating statistics, organizing events, protesting actions, and connecting interested people in this st

We study the problem of estimating the semi-generalized pose of a partially calibrated camera, i.e., the pose of a perspective camera with unknown focal length w.r.t. a generalized camera, from a hybrid set of 2D-2D and 2D-3D point correspondences. We study all possible camera configurations within the generalized camera system. To derive practical solvers to previously unsolved challenging config

It is well known that user proximity introduces absorption and impedance mismatch losses that severely degrade multiple-input multiple-output (MIMO) performance of handset antennas. In this work, we experimentally verified the potential of adaptive impedance matching (AIM) to mitigate user interaction effects and identified the main AIM gain mechanism in realistic systems. A practical setup includ

Using the metrics of channel capacity and multiplexing efficiency, the adaptive impedance matching (AIM) performances of two multiple-input multiple-output (MIMO) terminals with different antenna designs were evaluated and compared. The evaluation was performed in LTE Band 18 Downlink (860-875 MHz) under realistic usage conditions of two measured user handgrips and simulated propagation channels w

During the last decade, software process simulation has been used to address a variety of management issues and questions. These include: understanding; training and learning; planning; control and operational management; strategic management; process improvement and technology adoption. This paper presents a simulation model that was developed to demonstrate the impact of unstable software requir

The enhancement and protection of coastal ecosystems that sequester carbon for climate change mitigation have developed over the last 15 years, and today are part of climate governance. After an initially challenging start in terms of policy interest, Blue Carbon is now included in some countries’ national inventories, and as such, enters the global sums of emissions and sinks, and becomes relevan

This thesis discusses novel results in the area of code-based cryptography, ranging from cryptanalyses on several code-based cryptographic constructions to proposing a code-based authentication scheme based on a novel Syndrome Decoding variant.To address the looming threat of large-scale quantum computers that wouldbreak many widely-used public-key cryptosystems, the National Institute of Stan-dar

This thesis investigates scalable control design for networked dynamical systems, which are of great importance due to their wide range of practical applications, including large-scale formation control. A central challenge in such systems is enabling agents to coordinate effectively based only on local and relative information, particularly as the system size increases. To address this, the thesi

The Restricted Syndrome Decoding Problem (RSDP) is a variant of the well-known syndrome decoding problem. It has been recently turned into a post-quantum signature scheme named CROSS by Baldi et al.. It is a scheme highlighted for being computationally friendly and providing a compact signature and public key size. This paper investigates an Oracle-based definition of the RSDP that has already pro

We study the problem of obtaining lower bounds for polynomial calculus (PC) and polynomial calculus resolution (PCR) on proof degree, and hence by [Impagliazzo et al.'99] also on proof size. [Alekhnovich and Razborov'03] established that if the clause-variable incidence graph of a conjunctive normal form (CNF) formula F is a good enough expander, then proving that F is unsatisfiable requires high

We study the notion of (additive) separability of a function of several variables with respect to a hypergraph (H-graph). We prove the existence of a unique minimal H-graph with respect to which a function is separable and show that the corresponding minimal decomposition of the function can be obtained through a recursive algorithm. We then focus on (strategic form) games and propose a concept of

Navigating complex environments requires Unmanned Aerial Vehicles (UAVs) and autonomous systems to perform trajectory tracking and obstacle avoidance in realtime. While many control strategies have effectively utilized linear approximations, addressing the non-linear dynamics of UAV, especially in obstacle-dense environments, remains a key challenge that requires further research. This paper intro

In this paper, we unify two already published results on state feedback H-infinity optimality. Previously, optimality has been shown for a particular controller structure in the case that the open-loop state matrix is symmetric, as well as in the case that the closed-loop system is internally positive. By contrast, the main result of the present paper gives optimality based on neither of these two