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The resilience of Amazon tree cover to past and present drying

The Amazon forest is increasingly vulnerable to dieback and encroachment of grasslands and agricultural fields. Threats to these forested ecosystems include drying, deforestation, and fire, but feedbacks among these make it difficult to determine their relative importance. Here, we reconstruct the central and western Amazon tree cover response to aridity and fire in the mid-Holocene—a time of less

Towards a Complete Safety Framework for Longitudinal Driving

Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework enables the calculation of minimum safe inter-vehicular distances for arbitrary ego vehicle control policies in a computationally efficient manner. We use this framework to enhance and generalize the Respons

Cooperation for Ethical Autonomous Driving

The success in the adoption of autonomous vehicles is dependent on their ability to solve rarely occurring safety-critical corner cases. Vehicular communications (V2X) aim at improving safety and efficiency of autonomous driving by adding the capability of explicit inter-vehicular information exchange. We argue that V2X enables another important function, namely the support of ethical driving deci

Fully Declarative Specification of Static Code Checkers

Static code checkers are tools that help software engineers by automatically finding defects without executing the programs. These tools contain a set of detectors that rely on static program analyses to find common programming defects or to enforce coding guidelines.While existing code checker frameworks package a rich collection of detectors, aimed at common bug defects, the effort to adapt thes

Unified framework for entropy search and expected improvement in Bayesian optimization

Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function's optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective

Understanding high-dimensional Bayesian optimization

Recent work reported that simple Bayesian optimization methods perform well for high-dimensional real-world tasks, seemingly contradicting prior work and tribal knowledge. This paper investigates the 'why'. We identify fundamental challenges that arise in high-dimensional Bayesian optimization and explain why recent methods succeed. Our analysis shows that vanishing gradients caused by Gaussian pr

Threshold Saturation for Quantitative Group Testing with Low-Density Parity-Check Codes

We recently proposed a quantitative group testing (GT) scheme with low-complexity peeling decoding based on low-density parity-check (LDPC) codes. Based on finite length simulations and a density evolution analysis we were able to demonstrate that simple (dv,dc)-regular LDPC codes can be more efficient for GT than existing generalized LDPC (GLDPC) code constructions based on BCH component codes. E

Radio Channel Characterization for Distributed MIMO

Future wireless systems are envisioned to be able to deliver ultra-reliable and low-latency communication.The third generation partner project (3GPP) has identified three different usage scenarios such as enhanced mobile broadband, massive machine-type communication, and ultra-reliable low latency communication.In each of those scenarios, several services and applications can be implemented, e.g.

Towards understanding inter-organizational data sharing practices and technical tools needs

Background: Data quickly emerges as a core driver of businesses across the worlddue to rapidly expanding use in different areas, such as Machine Learning. In orderfor the data-related organizational operations to be efficient, the topic of data shar-ing has to be explored. This thesis focuses on understanding inter-organizationaldata sharing by exploring practices and challenges that are present w

Computation of radome reference cases using a rotationally symmetric full wave solver

We demonstrate how to compute radome reference cases for benchmarkingradome codes. Radomes are electrically large structures, and to facilitate thecomputations a rotationally symmetric structure is assumed. We show howto implement this in the commercial software Comsol Multiphysics, and howto extract the relevant data for comparison. Two example geometries areanalyzed: a spherical shell radome, an

Deterministic annealing with Potts neurons for multi-robot routing

A deterministic annealing (DA) method is presented for solving the multi-robot routing problem with min–max objective. This is an NP-hard problem belonging to the multi-robot task allocation set of problems where robots are assigned to a group of sequentially ordered tasks such that the cost of the slowest robot is minimized. The problem is first formulated in a matrix form where the optimal solut

A review of explainable AI in the satellite data, deep machine learning, and human poverty domain

Recent advances in artificial intelligence and deep machine learning have created a step change in how to measure human development indicators, in particular asset-based poverty. The combination of satellite imagery and deep machine learning now has the capability to estimate some types of poverty at a level close to what is achieved with traditional household surveys. An increasingly important is

Successive Cancellation Decoding of Single Parity-Check Product Codes : Analysis and Improved Decoding

A product code with single parity-check component codes can be described via the tools of a multi-kernel polar code, where the rows of the generator matrix are chosen according to the constraints imposed by the product code construction. Following this observation, successive cancellation decoding of such codes is introduced. In particular, the error probability of single parity-check product code

Characteristic Mode Decomposition of Scattering Dyadic

This abstract describes the decomposition of a matrix representing a scattering dyadic into characteristic modes. Scattering dyadic, as compared to conventionally used impedance matrices, are independent of numerical method used to compute them and the same characteristic mode formulation can be used for decomposition of composite and inhomogeneous materials. The utilization of scattering dyadic m

Folding lattice proteins with quantum annealing

Quantum annealing is a promising approach for obtaining good approximate solutions to difficult optimization problems. Folding a protein sequence into its minimum-energy structure represents such a problem. For testing new algorithms and technologies for this task, the minimal lattice-based [hydrophobic (H) or polar (P) beads] HP model is well suited, as it represents a considerable challenge desp

Guest Editorial : Recent and Future Evolution of Wi-Fi

The IEEE 802.11 standard, often referred to as Wi-Fi, underpins wireless networking applications around the world that impact our daily lives, such as wireless access to the Internet from offices, homes, airports, hotels, restaurants, trains, and aircraft. Today's laptops, tablets, and smartphones are typically equipped with at least one IEEE 802.11 radio. IEEE 802.11 standards have enabled a whol

Robust Performance Over Changing Intersymbol Interference Channels by Spatial Coupling

We show that spatially coupled low-density parity-check (LDPC) codes yield robust performance over changing intersymbol interfere (ISI) channels with optimal and suboptimal detectors. We compare the performance with classical LDPC code design which involves optimizing the degree distribution for a given (known) channel. We demonstrate that these classical schemes, despite working very good when de

Towards a Complete Safety Framework for Longitudinal Driving

Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework allows calculating minimum safe inter-vehicular distances for arbitrary ego vehicle control policies. We use this framework to enhance the Responsibility-Sensitive Safety (RSS) model and models based on it,

Can RE Help Better Prepare Industrial AI for Commercial Scale?

This issue marks the start of my term as department editor for the “Requirements” column. I very much look forward to exploring contemporary aspects of requirements and requirements engineering (RE) in the coming years! As an institute researcher with RISE, I primarily work in strictly regulated domains, in which requirements are cornerstones in the development activities. Please check my introduc

Remembering the past during new learning: the temporal dynamics of integrative encoding

Memories may integrate elements experienced in different events. For instance, meeting a woman leaving her house, and later meeting another woman entering the same house, may allow us to infer that the two women live together. Such memory representations are thought to rely on integrative encoding mechanisms, allowing us to make inferences about the world and generalize knowledge to entirely new s