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It is reported that the China–Pakistan Economic Corridor has been affected by extreme precipitation events. Since the 20th century, extreme weather events have occurred frequently, and the damage and loss caused by them have increased. In particular, the flood disaster caused by excessive extreme precipitation seriously hindered the development of the human society. Based on CRiteria Importance Th
This article aims at providing insights for a comprehensive understanding of THz propagation channels. Specifically, we discuss essential THz channel characteristics to be well understood for the success of THz communications. The methodology of establishing realistic and 6G-compliant THz channel models based on measurements is then elaborated on, followed by a discussion on existing THz channel m
This paper presents the hardware/software generation backend of a code generation framework. The backend aims at synthesizing complete systems based on RISC-V cores with accelerators from a single-language description. The framework takes the dataflow description of an algorithm as input and generates a combination of hardware (in Chisel) and software (in C) that interacts with the hardware. The h
With the purpose of examining biased updates in variance-reduced stochastic gradient methods, we introduce SVAG, a SAG/SAGA-like method with adjustable bias. SVAG is analyzed in a cocoercive root-finding setting, a setting which yields the same results as in the usual smooth convex optimization setting for the ordinary proximal-gradient method. We show that the same is not true for SVAG when biase
This paper proposes a belief propagation (BP)-based algorithm for sequential detection and estimation of multipath component (MPC) parameters based on radio signals. Under dynamic channel conditions with moving transmitter/receiver, the number of MPCs, the MPC dispersion parameters, and the number of false alarm contributions are unknown and time-varying. We develop a Bayesian model for sequential
The exact spatial and temporal behaviour of rapid climate shifts during the Last Glacial– Interglacial Transition are still not entirely understood. In order to investigate these events, it is necessary to have detailed palaeoenvironmental reconstructions at geographically spread study sites combined with reliable correlations between them. Tephrochronology, i.e., using volcanic ash deposits in ge
In recent decades, the Barents Sea has warmed more than twice as fast as the rest of the Arctic in winter, but the exact causes behind this amplified warming remain unclear. In this study, we quantify the wintertime Barents Sea warming (BSW, for near-surface air temperature) with an average linear trend of 1.74 °C decade-1 and an interdecadal change around 2003 based on a surface energy budget ana
An approach to resilient planning and control of autonomous vehicles in multi-vehicle traffic scenarios is proposed. The proposed method is based on model predictive control (MPC), where alternative predictions of the surrounding traffic are determined automatically such that they are intentionally adversarial to the ego vehicle. This provides robustness against the inherent uncertainty in traffic
The MeerKAT radio telescope consists of 64 Gregorian-offset antennas located in the Karoo in the Northern Cape in South Africa. The antenna system consists of multiple subsystems working collaboratively to form a cohesive instrument capable of operating in multiple modes for defined science cases. We focus on the channelizing subsystem (F-engine), the correlation subsystem (X-engine), and the beam
This chapter focuses on the Arctic since ocean-land interactions are more important for the Arctic than the Antarctic carbon cycle. It explores the complexity of connections between the ocean and land of the North Pole region, and possible impacts on greenhouse gas exchange and lateral carbon flows thereof. Ocean-land interactions in the Arctic integrate the terrestrial and marine environments. Th
This chapter describes the Back to the Future (BTF) approach with illustrations of different data sets and their conclusions and stimulates the growth of such studies. The BTF Project included several studies that "discovered" old data sets, digitized them, carried out analyses and made data and analyses available in publications. An important aspect of the BTF approach is that the evidence of cha
This study focused on improving the performance of the near real-time Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E) product based on a newly developed bias-correction scheme, LSCDF. The LSCDF was established by integrating the mean-based Linear Scaling (LS) and quantile-mapping Cumulative Distribution Function (CDF) matching approaches. The
In this thesis, we present and study a few approaches for constructing controllers for uncertain systems, using a combination of classical control theory and modern machine learning methods. The thesis can be divided into two subtopics. The first, which is the focus of the first two papers, is dual control. The second, which is the focus of the third and last paper, is multiple-input multiple-outp
Motivated by a need to characterize transient behaviors in large network systems in terms of relevant signal norms and worst-case input scenarios, we propose a novel approach based on existing theory for matrix pseudospectra. We extend pseudospectral theorems, pertaining to matrix exponentials, to an input-output setting, where matrix exponentials are pre- and post-multiplied by input and output m
Control systems are by design robust to various disturbances, ranging from noise to unmodelled dynamics. Recent work on the weakly hard model---applied to controllers---has shown that control tasks can also be inherently robust to deadline misses. However, existing exact analyses are limited to the stability of the closed-loop system. In this paper we show that stability is important but cannot be
A new approach to feedback control design based on optimal control is proposed. Instead of expensive computations of the value function for different penalties on the states and inputs, we use a control Lyapunov function that amounts to be a value function of the optimal control problem with suitable cost design and then study combinations of input and state penalty that are compatible with this v
Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we were interested in the challenges and benefits repor
