Phase unwrapping is the reconstruction of an absolute phase given its values modulo 2π. It is a commonly applied post-processing technique in synthetic aperture radar interferometry applications, such as topographic height and deformation estimation. Established InSAR phase unwrapping approaches focus on large scene phase retrieval, aiming for good overall performance and relying on auxiliary data, such as additional acquisitions, to correct the resulting large local deviations. Given recent progress in quantum algorithm development for optimization problems and phase unwrapping, we are further exploring the feasibility of leveraging gate-based quantum computers and hybrid quantum algorithms to improve small-scale high-accuracy phase unwrapping. We consider a new quantum approach to L1-norm phase unwrapping and a multistage combined approach leveraging the potential advantages of L0quantum and L1phase unwrapping.

Cognitive radar involves a closed loop between the radar receiver, radar transmitter, and the environment, similar to the perception-action cycle in human cognition. It adapts acquisition parameters based on the acquired information, which offers more efficient resource management of future SAR missions in varying scenes. We propose a spaceborne cognitive SAR concept for ship detection, which uses a two-stage process to improve ship detection capabilities. This radar concept can be implemented on a single platform using a hybrid mode or distributed on separate SAR satellites operated in a convoy configuration. We implement variational quantum circuits for the adaptation to the scene in a reinforcement learning approach to explore possible advantages of quantum computing combined with parameter optimisation on classical computers.

Phase unwrapping is the reconstruction of a phase given its values mod 2π. It is an important image processing technique used in synthetic aperture radar interferometry, e.g., in the context of topography and ground deformation. In light of recent quantum algorithm developments for mathematical optimization problems, we explore the usage of gate-based quantum computers and hybrid quantum algorithms to create novel phase unwrapping approaches.

Universities are isomorphic not because of the effectiveness of their processes but because of the legitimacy assigned by institutional logic. However, sustainable development discourses invoke a novel mission for producing knowledge and innovation for sustainable development. Accordingly, this research collected data from five types of internal stakeholders' intellections of the four pillars of green university infrastructure. The analysis of data collected from 89 university stakeholders sufficient for a 90% confidence level with 5% relative tolerable error was organized as five groups in a contingency table for the chi-square test. The statistical analysis, that is, the chi-square value, indicates that all five stakeholders perceive in the same direction – that the four pillars of the green university soft infrastructure need to be reconfigured to produce green knowledge and innovation. Hence, the findings inspire the conventional universities and policymakers to transform their universities into sustainable institutions with four pillars of soft green infrastructure.

This paper presents some of the research needs to overcome the constraints of different approaches to analyse harmonic instabilities in low voltage (LV) networks. Harmonic instabilities that refer to interactions of the control of power electronic (PE) devices and the network impedance have been observed increasingly in the past due to a growing share of renewable energy generators and other applications that are connected to the LV network via PE devices. Detailed white-box models can be derived if the device parameters are available while measurement-based identification approaches are required to parametrize black-box models. However, both approaches face individual challenges such as the computational effort, restrictions to small signal analysis and unknown system components, e.g. for manufacturers of PE devices the network impedance and for network operators the device specifications. The aim of this study is to present important challenges and constraints of the present methods to analyse harmonic instabilities in LV networks and consequently identify the research needs to overcome these challenges. In addition, measurements are shown to support the argumentation.

We present a Tool Suite which supports the (re-)construction of a behavioral model of a legacy component based on a learning approach by exploiting knowledge of known models of the existing component environment. This in turn enables to check whether the legacy component can be integrated correctly into its environment.

We present TakaTuka, a tiny Java Virtual Machine (JVM) for wireless sensor motes. TakaTuka's preliminary version successfully runs on Crossbow's mica2 motes. Furthermore, TakaTuka also runs on Windows and Unix.

The Electronics Research Laboratory at the Norwegian Institute of Technology has since 1974 studied PCM-transmission in the local subscriber plant. A short discussion of this work is presented together with choice of design parameters and concept for a digital subscriber set. Construction and laboratory testing of the digital subscriber set are described. The paper concludes with a discussion on future development.