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Reinforcement Learning (RL) is a powerful mathematical framework that allows robots to learn complex skills by trial-and-error. Despite numerous successes in many applications, RL algorithms still require thousands of trials to converge to high-performing policies, can produce dangerous behaviors while learning, and the optimized policies (usually modeled as neural networks) give almost zero expla
A convex optimization framework over contrast current density is developed to calculate fundamental bounds on the performance of linear passive cloaks. The formulation uses the method of moments applied to the electric field integral equation while using extincted power as the optimized metric. The presented results show that high cloaking efficiency requires cloaks made of low-loss and high-contr
An honest communication of uncertainty about quantities of interest enhances transparency in scientific assessments. To support this communication, risk assessors should choose appropriate ways to evaluate and characterize epistemic uncertainty. A full treatment of uncertainty requires methods that distinguish aleatory from epistemic uncertainty. Quantitative expressions for epistemic uncertainty
A non-von Neumann Near-Memory Computing architecture, optimized for CNN inference in edge computing, is integrated in the cache memory sub-system of a microcontroller unit. The NMC co-processor is evaluated using an 8-bit fixed-point quantized CNN model, and achieves an accuracy of 98% on the MNIST dataset. A full inference of the CNN model executed on the NMC processor, demonstrates an improvemen
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
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
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
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
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
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
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
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
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,
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
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
ObjectivesThe formation of episodic memories is critically determined by how we visually sample the world over time via sequences of eye movements. Nonetheless, in the neuroscience of human memory, memory encoding has almost exclusively been studied in experimental paradigms where the study material is presented in a single fixed location on the screen, and where eye movements are treated as artif
Episodic memory enables mental time travel, allowing us to relive specific, personally experienced events tied in time and place. This feat of human memory is considered to be dependent on the reinstatement of the cortical patterns that were active at the time of encoding. A growing body of recent literature has provided support for this idea by showing that retrieval success co-varies with the ne
In this paper, we examine variable node (VN) doping to mitigate the error propagation problem in sliding window decoding (SWD) of spatially coupled LDPC (SC-LDPC) codes from the point of view of the encoding process. More specifically, in order to simplify the process of generating an encoded sequence with some number of doped code bits, we propose to employ systematic encoding and to limit doping
The commercial availability of low-cost millimeterwave (mmWave) communication and radar devices is starting to improve the adoption of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifthgeneration (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedent
Cell-free massive multiple-input multiple-output (MIMO) consists of a large set of distributed access points (APs) serving a number of users. The APs can be far from each other, and they can also have a big number of antennas. Thus, decentralized architectures have to be considered so as to reduce the interconnection bandwidth to a central processing unit (CPU) and make the system scalable. On the
