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Bakgrund: Damfotboll har vuxit kraftigt senaste åren. Spelares externa belastning monitoreras med utrustning bestående av global positioning system, accelerometer och pulsband. Variablerna total distans, höghastighetslöpning och accelerationer/decelerationer har beskrivits som relevanta mått för att monitorera den externa belastningen för fotbollsspelare. Syfte: Att undersöka den externa belastningen i samband med träning, samt dess fluktuationer över tre mesocykler, för ett fotbollslag i Damallsvenskan under försäsongsträning, med fokus på variablerna total distans, high speed running och accelerationer/decelerationer.Metod: 15 utespelare inkluderades och försäsongsträningen delades in i tre mesocykler med 14 pass vardera. Between- och within subject-analyser utfördes med fokus på total distans, höghastighetslöpning samt accelerationer/decelerationer.Resultat: Resultatet visade en ökning av respektive variabel mellan mesocykel ett och två, följt av en minskning mellan två och tre. En tydlig minskning av höghastighetslöpning under mesocykel tre noterades. Between subjects-analysen visade lägre absoluta värden och variation än within subjects-analysen. Stora variationer i spelares externa belastning förelåg. Slutsats: Damfotbollsspelares externa belastning varierade kraftigt vid undersökning av total distans, höghastighetslöpning och accelerationer/decelerationer i samband med försäongsträning. Enligt en blockperiodisering, misslyckades i upprätthållandet av intensitet i sista mesocykeln. / Background: Womens’ football has grown rapidly. An increased use of tracking devices in football research has been shown, where total distance, high speed running and accelerations/decelerations stand out as important variables to track.Aim: To investigate external load, and its fluctuations over three mesocycles, for a team of elite female footballers during pre-season training.Method: A between- and within subject-analysis of 15 players from a team in Damallsvenskan, looking at total distance, high speed running and accelerations/decelerations, was conducted. Training sessions were divided into three mesocycles where comparisons were made.Results: Results showed an increase of each variable between mesocycle one and two, followed by a decrease in all variables between mesocycle two and three in both analyses. A decrease in high speed running during mesocycle three was prevalent. Between-subjects analysis showed slightly lower absolute values and slightly less variation than the within- subject analysis. Both analyses showed a big between- and within-players variation. Conclusion: Female footballers’ external load during pre-season training sessions were shown to display big variation looking at total distance, high speed running and accelerations/decelerations. Following a block periodisation model, the final mesocycle before season start failed in adequately maintaining intensity during tapering.

Laboratory and feral lineages of mice were subjected to cephalad (+GZ) accelerations, for 1.8 seconds, aboard a solid fuel rocket. Spectrophotometric analysis of bronchoalveolar lavage retrieved post launch revealed significant (p < .001) elevations of protein in the lungs of experimental mice. Sudden transient imposition of a mean +GZ acceleration of 6.22 ± .47 (SD) G, at lift-off, may have induced hypervolemia of basilar pulmonary microvasculature with concomitant migration of fluid and protein from intravascular to juxta-alveolar perivascular compartments. Exudates may have entered bronchiolar airways subsequently gravitating toward alveoli.

Electrons accelerating in shock events occur oftenin outer space, for example in supernovas and the poles of blackholes, and are of high interest to physicists and other researchers.The technology to take a closer look at events that far awaydoes not exist yet, but luckily we can observe similar events inplaces where the Earth’s magnetic fields and particle streamsfrom the Sun meet. Using data from NASA’s MMS mission thispaper aims to gather information about what variables affect theacceleration, under what conditions the most energetic eventsoccur and create a ranked list of several hundreds of theseevents. It did this by calculating the expected value of the electrondistribution function at different times to create a dimensionlessranking. The study showed that these events are highly complexand that it is difficult to assign a few variables which would affectthe acceleration. However it also showed that most accelerationoccurs after the most abrupt shock crossing and not exactly atthe location where the expected value is maximal, and that thereare some correlations with angle relative to the solar magneticfield and electron number density. / Elektroner som accelereras i shockar skerofta i yttre rymden, till exmepel i supernovor och vid polernahos svarta hål, och är därför av högt intresse hos fysikeroch andra forskare. Teknologin för att titta närmre på dessafjärran fenomen existerar inte ännu, men som tur är så kan viobservera liknande händelser på platser där Jordens magnetfältmöter partikelvindar från Solen. Med hjälp av data från NASAsMMS uppdrag har detta projekt önskat att samla informationom vilka variabler som påverkar accelerationen, under vilkaomständigheter de mest energirika händelserna sker och skapa enrankad lista av flera hundra av dessa händelser. Det gjorde dettagenom att beräkna det förväntade värdet på elektronernas distributionsfunktionvid flera tillfällen för att skapa en dimensionslösrank. Studien visade att dessa händelser är mycket komplexaoch att det är svårt att tilldela ett fåtal variabler som skullepåverka accelerationen. Dock så visade projektet att den störstaaccelerationen sker efter den mest abrubta shockkorsningen ochinte exakt vid det tillfälle då det förväntansvärdet är som högst,och att det finns någon korrelation med vinkeln relativt solensmagnetfält och elektronernas nummerdensitet. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

This thesis aims at developing efficient algorithms for solving some fundamental engineering problems in data science and machine learning. We investigate a variety of acceleration techniques for improving the convergence times of optimization algorithms.  First, we investigate how problem structure can be exploited to accelerate the solution of highly structured problems such as generalized eigenvalue and elastic net regression. We then consider Anderson acceleration, a generic and parameter-free extrapolation scheme, and show how it can be adapted to accelerate practical convergence of proximal gradient methods for a broad class of non-smooth problems. For all the methods developed in this thesis, we design novel algorithms, perform mathematical analysis of convergence rates, and conduct practical experiments on real-world data sets. / <p>QC 20191105</p>

<p>As the number of transistors that are integrated onto a silicon die continues to in- crease, the compute power is becoming a commodity. This has enabled a whole host of new applications that rely on high-throughput computations. Recently, the need for faster and cost-effective applications in form-factor constrained environments has driven an interest in on-chip acceleration of algorithms based on Monte Carlo simula- tions. Though Field Programmable Gate Arrays (FPGAs), with hundreds of on-chip arithmetic units, show significant promise for accelerating these embarrassingly paral- lel simulations, a challenge exists in sharing access to simulation data amongst many concurrent experiments. This thesis presents a compute architecture for accelerating Monte Carlo simulations based on the Network-on-Chip (NoC) paradigm for on-chip communication. We demonstrate through the complete implementation of a Monte Carlo-based image reconstruction algorithm for Single-Photon Emission Computed Tomography (SPECT) imaging that this complex problem can be accelerated by two orders of magnitude on even a modestly-sized FPGA over a 2GHz Intel Core 2 Duo Processor. Futhermore, we have created a framework for further increasing paral- lelism by scaling our architecture across multiple compute devices and by extending our original design to a multi-FPGA system nearly linear increase in acceleration with logic resources was achieved.</p> / Master of Applied Science (MASc)

This research provides the real-time computational resource for three dimensional tomographic chemical threat mapping using mobile hyperspectral sensors from sparse input data. The crucial calculation limiting real-time execution of the algorithm is the determination of the projection matrix using the algebraic reconstruction technique (ART). The computation utilizes the inherent parallel nature of ART with an implementation of the algorithm on a field programmable gate array. The MATLAB Fixed-Point Toolbox is used to determine the optimal fixed-point data types in the conversion from the original floating-point algorithm. The computation is then implemented using the Xilinx System Generator, which generates a hardware description language representation from a block diagram design. / Electrical and Computer Engineering

Computational modeling of light-matter interactions is a valuable approach for simulating photon paths in highly scattering media such as biological tissues. Monte Carlo (MC) models are considered to be the gold standard of implementation and can offer insights into light flux, absorption, and emission through tissues. Monte Carlo modeling is a computationally intensive approach, but this burden has been alleviated in recent years due to the parallelizable nature of the algorithm and the recent implementation of graphics processing unit (GPU) acceleration. Despite impressive translational applications, the relatively recent emergence of GPU-based acceleration of MC models can still be utilized to address some pressing challenges in biomedical optics beyond DOT and PDT. The overarching goal of the current dissertation is to advance the applications and abilities of GPU accelerated MC models to include low-cost devices and model Raman scattering phenomena as they relate to clinical diagnoses. The massive increase in computational capacity afforded by GPU acceleration dramatically reduces the time necessary to model and optimize optical detection systems over a wide range of real-world scenarios. Specifically, the development of simplified optical devices to meet diagnostic challenges in low-resource settings is an emerging area of interest in which the use of MC modeling to better inform device design has not yet been widely reported. In this dissertation, GPU accelerated MC modeling is utilized to guide the development of a mobile phone-based approach for diagnosing neonatal jaundice. Increased computational capacity makes the incorporation of less common optical phenomena such as Raman scattering feasible in realistic time frames. Previous Raman scattering MC models were simplistic by necessity. As a result, it was either challenging or impractical to adequately include model parameters relevant to guiding clinical translation. This dissertation develops a Raman scattering MC model and validates it in biological tissues. The high computational capacity of a GPU-accelerated model can be used to dramatically decrease the model’s grid size and potentially provide an understanding of measured signals in Raman spectroscopy that span multiple orders of magnitude in spatial scale. In this dissertation, a GPU-accelerated Raman scattering MC model is used to inform clinical measurements of millimeter-scale bulk tissue specimens based on Raman microscopy images. The current study further develops the MC model as a tool for designing diffuse detection systems and expands the ability to use the MC model in Raman scattering in biological tissues. / Bioengineering