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Scaled reassigned spectrograms applied to linear transducer signals

This study evaluates the applicability of scaled reassigned spectrograms (ReSTS) on ultrasound radio frequency data obtained with a clinical linear array ultrasound transducer. The ReSTS's ability to resolve axially closely spaced objects in a phantom is compared to the classical cross-correlation method with respect to the ability to resolve closely spaced objects as individual reflectors using u

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) super

Object Detector Differences when Using Synthetic and Real Training Data

To train well-performing generalizing neural networks, sufficiently large and diverse datasets are needed. Collecting data while adhering to privacy legislation becomes increasingly difficult and annotating these large datasets is both a resource-heavy and time-consuming task. An approach to overcome these difficulties is to use synthetic data since it is inherently scalable and can be automatical

Grain-128AEADv2: Strengthening the Initialization Against Key Reconstruction

Properties of the Grain-128AEAD key re-introduction, as part of the cipher initialization, are analyzed and discussed. We consider and analyze several possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seems favorable to separate the state initialization, the key re-introduction, and the A/R register initialization into

Grain-128AEAD, Round 3 Tweak and Motivation

Weaknesses in the Grain-128AEAD key re-introduction, as part of thecipher initialization, are analyzed and discussed. We consider and analyzeseveral possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seemsfavorable to separate the state initialization, the key re-introduction, andthe A/R register initialization into thr

Utarmning och utdöende – tillståndet för rödlistade dagfjärilar och bastardsvärmare

Under de senaste 150 åren har det svenska landskapet genomgått mycket stora förändringar. Det har lett till förlust av livsmiljöer för många arter och har haft långtgående konsekvenser för vår inhemska fauna och flora. Många arter har minskat dramatiskt och i vissa fall helt försvunnit.När en art väl har börjat minska finns det många faktorer som kan förstärka den negativa trenden. En individrik p

Dynamic Federations for 6G Cell-Free Networking: Concepts and Terminology

Cell-Free networking is one of the prime candidatesfor 6G networks. Despite being capable of providing the 6Gneeds, practical limitations and considerations are often neglectedin current research. In this work, we introduce the conceptof federations to dynamically scale and select the best set ofresources, e.g., antennas, computing and data resources, to servea given application. Next to communica

Assessing the Impact of Atmospheric CO2 and NO2 Measurements From Space on Estimating City-Scale Fossil Fuel CO2 Emissions in a Data Assimilation System

The European Copernicus programme plans to install a constellation of multiple polar orbiting satellites (Copernicus Anthropogenic CO2 Monitoring Mission, CO2M mission) for observing atmospheric CO2 content with the aim to estimate fossil fuel CO2 emissions. We explore the impact of potential CO2M observations of column-averaged CO2 (XCO2), nitrogen dioxide (NO2), and aerosols in a 200 × 200 km2 d

Security Issue Classification for Vulnerability Management with Semi-supervised Learning

Open-Source Software (OSS) is increasingly common in industry software and enables developers to build better applications, at a higher pace, and with better security. These advantages also come with the cost of including vulnerabilities through these third-party libraries. The largest publicly available database of easily machine-readable vulnerabilities is the National Vulnerability Database (NV

Bias Versus Non-Convexity in Compressed Sensing

Cardinality and rank functions are ideal ways of regularizing under-determined linear systems, but optimization of the resulting formulations is made difficult since both these penalties are non-convex and discontinuous. The most common remedy is to instead use the ℓ1- and nuclear norms. While these are convex and can therefore be reliably optimized, they suffer from a shrinking bias that degrades

Performance Measurement Systems, Middle Managers, and the Fight over Control

Title: Performance Measurement Systems, Middle Managers, and the Fight over Control Seminar Date: June 2nd, 2023 Course: Business Administration: Bachelor’s degree project in organization. Undergraduate level, 15 credits. Authors: Nicole Kronkvist, Fritjof Jansson and Maja Muscat Scerri Supervisor: Johan Jönsson Five Keywords: Performance Measurement Systems, Expectancy Theory, Middle Manage

Spatial Modeling of Urban Pluvial Flood Risk on Sewer Networks: A Bayesian Approach for Climate Adaptation in Swedish Municipalities

Climate change is intensifying short-duration rainfall extremes, increasing urban pluvial flood risk across Swedish municipalities. This study develops a novel spatial statistical framework for basement flood risk assessment using Log-Gaussian Cox Process (LGCP) models on metric graphs, applied to 17 years of flood records from Trelleborg, southern Sweden.Unlike conventional approaches that treat

From observed impacts to rainfall thresholds: compound risks of urban pluvial flooding

Urban pluvial flooding is a growing climate-related risk in Nordic cities, where short-duration rainfall extremes interact with aging drainage infrastructure and urban form. This study analyses 17 years (2006–2023) of property-level basement flooding reports from Trelleborg, a coastal municipality in southern Sweden, to identify empirical rainfall thresholds and infrastructural conditions associat

On the Asymptotics of Solving the LWE Problem Using Coded-BKW with Sieving

The Learning with Errors problem (LWE) has become a central topic in recent cryptographic research. In this paper, we present a new solving algorithm combining important ideas from previous work on improving the Blum-Kalai-Wasserman (BKW) algorithm and ideas from sieving in lattices. The new algorithm is analyzed and demonstrates an improved asymptotic performance. For the Regev parameters $q=n^2$

Comparing LSTM and FOFE-based Architectures for Named Entity Recognition

LSTM architectures (Hochreiter and Schmidhuber, 1997) have become standard to recognize named entities (NER) in text (Lample et al., 2016; Chiu and Nichols, 2016). Nonetheless, Zhang et al. (2015) recently proposed an approach based on fixed-size ordinally forgetting encoding (FOFE) to translate variable-length contexts into fixed-length features. This encoding method can be used with feed-forward

Vectorized linear approximations for attacks on SNOW 3G

SNOW 3G is a stream cipher designed in 2006 by ETSI/SAGE, serving in 3GPP as one of the standard algorithms for data confidentiality and integrity protection. It is also included in the 4G LTE standard. In this paper we derive vectorized linear approximations of the finite state machine in SNOW3G. In particular,we show one 24-bit approximation with a bias around 2−37 and one byte-oriented approxim

Flexible DRX Optimization for LTE and 5G

With the advancement of the next generation of cellular systems, flexible mechanisms for Discontinuous Reception (DRX) are needed in order to save energy. 5G will bring heterogeneous packet sizes and traffic types, as well as an increasing need for energy efficiency. The current static DRX mechanism is inadequate to meet these needs. In this paper we exploit channel prediction to develop integer p