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LPED 2022 3

Centre for Economic Demography Lund University School of Economics and Management P.O. Box 7083 SE-220 07 Lund, Sweden www.ed.lu/publications/Lund-Papers-in-Economic-Demography/ Documenting Determinants of the Divorce Transition. Micro-Level Evidence from Sweden 1905–1967 MARTIN BERGVALL, MARIA STANFORS LUND PAPERS IN ECONOMIC DEMOGRAPHY 2022:3 Documenting Determinants of the Divorce Transition. M

https://www.lusem.lu.se/sites/lusem.lu.se/files/2024-01/LPED%202022%203.pdf - 2026-05-18

Rapport vecka9 CoSS

Rapport vecka 9 (publicerad 2021-03-10) COVID Symptom Study Innehåll Bakgrund 2 Metod 2 Etiskt godkännande 4 Aktuell status 4 10 postnummerområden med högst uppskattad förekomst av symtomatisk covid-19 10 mars . . . . 6 10 postnummerområden med lägst uppskattad förekomst av symtomatisk covid-19 10 mars . . . . 8 Störst ökning senaste 7 dagarna . . . . . . . . . . . . . . . . . . . . . . . . . . .

https://www.covid19app.lu.se/sites/covid19app.lu.se/files/2021-03/rapport_vecka9_CoSS.pdf - 2026-05-18

VR teleoperation to support a GPS-free positioning system in a marine environment

Small autonomous surface vehicles (ASV) will need both teleoperation support and redundant positioning technology to comply with expected future regulations. When at sea, they are limited by a satellite communication link with low throughput. We have designed and implemented a graphical user interface (GUI) for teleoperation using a communication link with low throughput, and one positioning syste

Continuous close-range 3D object pose estimation

In the context of future manufacturing lines, removing fixtures will be a fundamental step to increase the flexibility of autonomous systems in assembly and logistic operations. Vision-based 3D pose estimation is a necessity to accurately handle objects that might not be placed at fixed positions during the robot task execution. Industrial tasks bring multiple challenges for the robust pose estima

Assembling a toolkit for computational dissection of dense protein systems

The cellular interior is a dense environment. Understanding how such an environment impacts the properties of proteins and other macromolecules, as well as how weak, non-specific interactions drive processes such as protein droplet formation through liquid-liquid phase separation, is a major challenge in biological physics. The complexity of this environment often makes experimental studies extrem

IR and Metasurface based mm-Wave Camera

We have developed a technique to measure low-power electromagnetic fields from mm-wave devices non-intrusively by combining a metasurface, designed to absorb power and focus the radiated power in a thermally isolated region, with an infrared camera. The metasurface consists of thermally isolated elements of low mass and highly emissive material for maximal IR conversion of the incident wave. The I

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of

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

A suggestion for the quantification of precise and bounded probability to quantify epistemic uncertainty in scientific assessments

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

An Energy-Efficient Near-Memory Computing Architecture for CNN Inference at Cache Level

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

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

Early Identification of Invalid Bug Reports in Industrial Settings – A Case Study

Software development companies spend considerable time resolving bug reports. However, bug reports might be invalid, i.e., not point to a valid flaw. Expensive resources and time might be expended on invalid bug reports before discovering that they are invalid. In this case study, we explore the impact of invalid bug reports and develop and assess the use of machine learning (ML) to indicate wheth

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,