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Mechanisms of the aerosol indirect effects (AIEs) from ice nucleating particles (INPs) are investigated with the cloud-resolving “aerosol–cloud” (AC) model with a hybrid bin–bulk microphysics scheme coupled with a radiation scheme in 1) continental deep convection observed during the Midlatitude Continental Convective Clouds Experiment (MC3E) over Oklahoma and 2) supercooled stratiform clouds obse
In this paper, we revisit the question of key recovery using side-channel analysis for unrolled, single-cycle block ciphers. In particular, we study the Princev2 cipher. While it has been shown vulnerable in multiple previous studies, those studies were performed on side-channel friendly ASICs or older FPGAs (e.g., Xilinx Virtex II on the SASEBO-G board), and using mostly expensive equipment. We s
Tropical cyclones (TCs) pose significant threats to life and property across global ocean basins, and forecasting their structural evolution, track, and intensity remains a major scientific challenge. This review synthesizes the current understanding of TCs across major basins, that is, the Pacific, Atlantic, and North Indian Oceans, with a focus on the key environmental factors influencing TC beh
Road traffic pollution is one of the most important factors among other environmental factors that influence the roadside vegetation. The present research examines the impact of motorway flyovers and at-grade roads on air pollution (PM10, SOx, NOx, and air quality index (AQI)) and roadside vegetation in Dehradun by considering the important biochemical parameters such as chlorophyll, ascorbic acid
Surface water pollution consists of various pollutants like heavy metals (Cu, Cr, Pb, and Ni), metalloids (Se, As, and Ag), and organic pollutants (dyes, antibiotics, pharmaceuticals, pesticides, and phenolic compounds). The escalating issue of water pollution requires innovative solutions for mitigation and climate resilience. Although various advanced techniques are being developed for removing
Against the backdrop of Gaza and Europe’s muted response, this essay reflects on Elad Lapidot’s challenge to recognize the violence hidden in the language of peace.
SJUKHUSFYSIKERPROGRAMMET 2020-08-02 LITTERATURLISTA MSFM21 Medicinsk strålningsfysik – SJUKHUSFYSIK (60 hp) HT20/VT21 Hoskins, P. R., Thrush, A., Martin, K. (eds.). Diagnostic Ultrasound – Physics and Equipment. Cambridge University Press 2010. ISBN 9780521757102. OBS! Boken finns som fri e-bok på LUB efter inloggning med din STiL-ID Används på delkursen Bild- och funktionsdiagnostik, tema: Ultral
https://www.msf.lu.se/sites/msf.lu.se/files/litteraturlista_msfm21_-_h20.pdf - 2026-05-30
Discontinuous Galerkin (DG) methods are promising high order discretizations for unsteady compressible flows. Here, we focus on Numerical Weather Prediction (NWP). These flows are characterized by a fine resolution in z-direction and low Mach numbers, making the system stiff. Thus, implicit time integration is required and for this a fast, highly parallel, low-memory iterative solver for the resul
Uppsatsmall Lunds universitet STV102 Statsvetenskapliga institutionen VT04 Handledare: NN Depoliticizing feminism? The transformation of an ideology-charged concept in a nation branding context ISABELLE KARLSSON Lund University Department of strategic communication Master’s thesis Course: SKOM12 Term: Spring 2018 Supervisor: Cecilia Cassinger Examiner: Åsa Thelander 2 Abstract Depoliticizing femin
https://www.isk.lu.se/sites/isk.lu.se/files/thesis-isabelle-karlsson_depoliticizing-feminism.pdf - 2026-05-30
In the dawning age of autonomous driving, accurate and robust tracking of vehicles is a quintessential part. This is inextricably linked with the problem of Simultaneous Localisation and Mapping (SLAM), in which one tries to determine the position of a vehicle relative to its surroundings without prior knowledge of them. The more you know about the object you wish to track—through sensors or mecha
We present a model for generating 3d articulated pedestrian locomotion in urban scenarios, with synthesis capabilities informed by the 3d scene semantics and geometry. We reformulate pedestrian trajectory forecasting as a structured reinforcement learning (RL) problem. This allows us to naturally combine prior knowledge on collision avoidance, 3d human motion capture and the motion of pedestrians
Precipitation over the Tibetan Plateau (TP) has major societal impacts in South and East Asia, but its spatiotemporal variations are not well understood, mainly because of the sparsely distributed in situ observation sites. With the help of the Global Precipitation Measurement satellite product IMERG and the ERA5 dataset, distinct precipitation seasonality features over the TP were objectively cla
Software-Defined Networking (SDN) is a novel architectural model for cloud network infrastructure, improving resource utilization, scalability and administration. SDN deployments increasingly rely on virtual switches executing on commodity operating systems with large code bases, which are prime targets for adversaries attacking the network infrastructure. We describe and implement TruSDN, a frame
There are several different approaches used to treat prostate cancer, depending on age and general health conditions of the patient but also how severe the cancer is. To determine the latter, Gleason grading is used. The grade is determined by a pathologist, based on structures in histology samples from prostate biopsies. To determine the diagnosis, both the most common Gleason grade but also the
We derive an expression for the error introduced by the second-order accurate temporal finitedifference (FD) operator, as present in the FD, pseudospectral and spectral element methods for seismic wave modeling applied to time-invariant media. The 'time-dispersion' error speeds up the signal as a function of frequency and time step only. Time dispersion is thus independent of the propagation path,
This thesis explores methods for estimating 3D models using depth sensors andfinding low-rank approximations of matrices. In the first part we focus on how toestimate the movement of a depth camera and creating a 3D model of the scene.Given an accurate estimation of the camera position, we can produce dense 3Dmodels using the images obtained from the camera. We present algorithms thatare both accu
Traditional matrix factorization methods approximate high dimensional data with a low dimensional subspace. This imposes constraints on the matrix elements which allow for estimation of missing entries. A lower rank provides stronger constraints and makes estimation of the missing entries less ambiguous at the cost of measurement fit. In this paper we propose a new factorization model that further
Are we using the right potential functions in the Conditional Random Field models that are popular in the Vision community? Semantic segmentation and other pixel-level labelling tasks have made significant progress recently due to the deep learning paradigm. However, most state-of-the-art structured prediction methods also include a random field model with a hand-crafted Gaussian potential to mode
