Global ETD Search

431	The Moral Economy of Swedish Labour Market Co-operation and Job Security in the Neoliberal Era Fleming, James January 2021 (has links) In the neoliberal era, there has been a global trend towards increased labour market insecurity and inequality, even in countries traditionally emblematic of union strength and socio-economic security such as Sweden. In this study, I present the first ethnographic research conducted in anthropology of negotiations between the central Swedish union and employer peak bodies (known as the ‘labour market partners’). These negotiations were conducted in 2020 against the background of a political crisis and political pressure to modernise and liberalise longstanding and fundamental job security protec- tions in the Employment Protection Act (LAS). Through the lens of these negotiations, I investigate the role of the labour market partners in moderating neoliberal trends and how the partners see their relationship and role in society. I investigate, for example, why Swedish employers support unions and a system that ostensibly curbs their own power. I employ the notions of moral economy and em- bedding to look beyond economic self-interest, to the moral and institutional norms that help explain the partners’ co-operation over time and the role they see themselves as playing as guardians of the social peace. I also incorporate interview material describing diverse workers’ experiences of the current job security protections under LAS. I argue that workers’ voices and experiences reveal a parallel moral economy, where current job security protections are revealed to be important but inadequate, and that job security is a highly nebulous, ambivalent and contextual phenomenon. I argue the moral economy of job security is one of entangled reciprocity between employer, worker and the state, and I consider the proposed reforms in this context. The study shows that even in the context of increasing market- isation of labour and society, reciprocity and cooperation both at the workplace and during the LAS negotiations serve to de-commodify labour and embed the economy in various moral norms. In this way, the research contributes to the anthropological literature on embeddedness and moral economy. It also contributes to both an ethnographic and theoretical understanding of job security. Moral economy embedding industrial relations Sweden corporatism co-operation job security ne- oliberalism labour market negotiations unions employer organisations anthropology political econ- omy de-commodification social peace Inbäddning Sverige samarbete arbetssäkerhet nyliberalism arbetsmarknadsparter arbetsmarknadsrelationer arbetsmarknad förhandlingar fackförbund facket arbetsgivarorganisation antropologi social fred kommodifiering Svenskt näringsliv LO anställningskydd Las Social Anthropology Socialantropologi Cultural Studies Kulturstudier Ethnology Etnologi Economic History Ekonomisk historia Law and Society Juridik och samhälle
432	Analysis of Bolted Connections in Creo Simulate - Theory, Software Functionality and Application Examples Jakel, Roland 25 June 2013 (has links) Die Präsentation stellt kurz die Grundlagen der Berechnung von Schraubenverbindungen in Anlehnung an die VDI-Richtlinie 2230 Teil 1 dar. Auch die vier FEM-Modellklassen, die die VDI 2230 Teil 2 (Entwurf) zur Berechnung von Mehrschraubenverbindungen vorschlägt, werden behandelt, und die in Creo Simulate vorhandenen Softwarefeatures zu deren Umsetzung vorgestellt. Es folgt eine Darstellung, was bei der Linearisierung von Schraubenverbindungen zur vereinfachten Berechnung zu beachten ist, und wieso bei der Berechnung im FEM-System dann nicht notwendigerweise eine Vorspannung benötigt wird. Ausführlich wird das neue Schraubenfeature in Creo Simulate betrachtet, das eine weitgehend automatisierte Modellierung und Berechnung von Standardverschraubungen erlaubt. Weitere Features, wie die neuen Vorspannelemente, werden erläutert, sowie auch die Grenzen der Software aufgezeigt. Abschließend werden zwei anspruchsvolle Anwendungsbeispiele vorgestellt: Eine zentrisch belastete Verschraubung mit Berücksichtigung von Elasto-Plastizität und einer komplexen Lasthistorie (Anziehen durch Anzugsmoment, Setzeffekte, Entfall des Torsionsmomentes durch das Anziehen, Betriebskraft) sowie eine exzentrisch belastete Verschraubung, die wegen eines relativ dünnen Flansches starke Biegezusatzbeanspruchungen erfährt. / The presentation shows the foundations of bolt analysis according to VDI-guideline 2230 part 1. In addition, the four FEM model classes proposed in VDI 2230 part 2 (draft) are described, as well as the features available in Creo Simulate to realize these model classes. Next, the presentation shows the requirements for linearizing bolted connections, and why in a FEM analysis with a linearized connection no preload is necessary. The new fastener feature introduced in Creo Simulate is explained in detail. This feature allows the automated modeling and analysis of bolted connections having standard geometry. Further software features, like pretension elements, as well as the current software limitations are shown. Finally, two advanced application examples are shown: A centrically loaded bolted connection taking into account elasto-plasticity and a complex load history (tightening torque, embedding, removal of tightening stress, operational load), and an eccentrically loaded flange connection, which is subjected to high additional bending loads because the flange is relatively thin. info:eu-repo/classification/ddc/629 ddc:629
433	A Multilinear (Tensor) Algebraic Framework for Computer Graphics, Computer Vision and Machine Learning Vasilescu, M. Alex O. 09 June 2014 (has links) This thesis introduces a multilinear algebraic framework for computer graphics, computer vision, and machine learning, particularly for the fundamental purposes of image synthesis, analysis, and recognition. Natural images result from the multifactor interaction between the imaging process, the scene illumination, and the scene geometry. We assert that a principled mathematical approach to disentangling and explicitly representing these causal factors, which are essential to image formation, is through numerical multilinear algebra, the algebra of higher-order tensors. Our new image modeling framework is based on(i) a multilinear generalization of principal components analysis (PCA), (ii) a novel multilinear generalization of independent components analysis (ICA), and (iii) a multilinear projection for use in recognition that maps images to the multiple causal factor spaces associated with their formation. Multilinear PCA employs a tensor extension of the conventional matrix singular value decomposition (SVD), known as the M-mode SVD, while our multilinear ICA method involves an analogous M-mode ICA algorithm. As applications of our tensor framework, we tackle important problems in computer graphics, computer vision, and pattern recognition; in particular, (i) image-based rendering, specifically introducing the multilinear synthesis of images of textured surfaces under varying view and illumination conditions, a new technique that we call ``TensorTextures'', as well as (ii) the multilinear analysis and recognition of facial images under variable face shape, view, and illumination conditions, a new technique that we call ``TensorFaces''. In developing these applications, we introduce a multilinear image-based rendering algorithm and a multilinear appearance-based recognition algorithm. As a final, non-image-based application of our framework, we consider the analysis, synthesis and recognition of human motion data using multilinear methods, introducing a new technique that we call ``Human Motion Signatures''. multilinear algebra tensor algebra computer vision computer graphics machine learning principal component analysis (PCA) independent component analysis (ICA/BSS) kernel component analysis (KPCA/KICA) local linear embedding multifactor LLE M-mode SVD M-mode PCA M-mode ICA multilinear projection m-mode pseudo-inverse tensor m-mode identity tensor m-mode product genearlization texture synthesis face recognition human motion signatures 0984 0800 0805 0463
434	A Multilinear (Tensor) Algebraic Framework for Computer Graphics, Computer Vision and Machine Learning Vasilescu, M. Alex O. 09 June 2014 (has links) This thesis introduces a multilinear algebraic framework for computer graphics, computer vision, and machine learning, particularly for the fundamental purposes of image synthesis, analysis, and recognition. Natural images result from the multifactor interaction between the imaging process, the scene illumination, and the scene geometry. We assert that a principled mathematical approach to disentangling and explicitly representing these causal factors, which are essential to image formation, is through numerical multilinear algebra, the algebra of higher-order tensors. Our new image modeling framework is based on(i) a multilinear generalization of principal components analysis (PCA), (ii) a novel multilinear generalization of independent components analysis (ICA), and (iii) a multilinear projection for use in recognition that maps images to the multiple causal factor spaces associated with their formation. Multilinear PCA employs a tensor extension of the conventional matrix singular value decomposition (SVD), known as the M-mode SVD, while our multilinear ICA method involves an analogous M-mode ICA algorithm. As applications of our tensor framework, we tackle important problems in computer graphics, computer vision, and pattern recognition; in particular, (i) image-based rendering, specifically introducing the multilinear synthesis of images of textured surfaces under varying view and illumination conditions, a new technique that we call ``TensorTextures'', as well as (ii) the multilinear analysis and recognition of facial images under variable face shape, view, and illumination conditions, a new technique that we call ``TensorFaces''. In developing these applications, we introduce a multilinear image-based rendering algorithm and a multilinear appearance-based recognition algorithm. As a final, non-image-based application of our framework, we consider the analysis, synthesis and recognition of human motion data using multilinear methods, introducing a new technique that we call ``Human Motion Signatures''. multilinear algebra tensor algebra computer vision computer graphics machine learning principal component analysis (PCA) independent component analysis (ICA/BSS) kernel component analysis (KPCA/KICA) local linear embedding multifactor LLE M-mode SVD M-mode PCA M-mode ICA multilinear projection m-mode pseudo-inverse tensor m-mode identity tensor m-mode product genearlization texture synthesis face recognition human motion signatures 0984 0800 0805 0463
435	Getting it right operationalizing civilian capacity for conflict and post-conflict environments. McNaught, James A. January 1900 (has links) "A paper submitted to the faculty of the NWC in partial satisfaction of the requirements of the JMO Department." / Title from title screen (viewed June 10, 2008). "February 14, 2005." Faculty advisor: Douglas Hime. "ADA464898"--URL. Includes bibliographical references (p. 24-27).
436	Elektrische Charakterisierung PLD-gewachsener Zinkoxid-Nanodrähte Zimmermann, Gregor 17 August 2010 (has links) Die vorliegende Arbeit beschäftigt sich mit der elektrischen Charakterisierung von Zinkoxid-Nanodrähten, die mittels gepulster Laserablation (PLD) hergestellt wurden. Ausgehend von den so generierten ZnO-Nanodraht-Ensembles werden Methoden zu deren elektrischer Untersuchung diskutiert und auf praktische Anwendbarkeit hin verglichen. Die entwickelten Methoden werden auf Ensembles von auf n-leitenden ZnO- und ZnO:Ga-Dünnschichten aufgewachsenen Phosphor-dotierten ZnO-Nanodrähten angewendet. Deren reproduzierbares, in Strom–Spannungs- (I–U-) Kennlinien beobachtetes diodenartiges Verhalten wird genauer beleuchtet. Im Zusammenhang mit der elektrischen Charakterisierung einzelner ZnO-Nano-drähte werden experimentelle Methoden zur Vereinzelung und zur Kontaktierung der vereinzelten ZnO-Nanodrähte diskutiert. Dabei werden sowohl etablierte Methoden wie Elektronenstrahllithographie (EBL) als auch neue Techniken wie elektronen- und ionenstrahlinduzierte Deposition (EBID/IBID) und Strom–Spannungs-Rastersondenmikroskopie (I-AFM) behandelt und ihre Eignung für eingehende elektrische Untersuchungen und reproduzierbare Messungen analysiert. Die geeignetsten Methoden werden schließlich eingesetzt, um spezifischen Widerstand sowie Ladungsträgermobilität und -dichte sowohl in nominell undotierten als auch in Aluminium-dotierten ZnO-Nanodrähten zu untersuchen und zu vergleichen. In der Ableitung der physikalischen Materialparameter aus den Messdaten wird dabei besonderes Augenmerk auf die Einbeziehung der geometrischen Besonderheiten der Nanodrähte gegenüber Volumenmaterial- und Dünnschichtproben gelegt. Im Zuge dessen wird unter anderem ein Modell für den elektrischen Widerstand in Nanodrähten mit ihrer Länge nach veränderlichem Querschnitt abgeleitet. info:eu-repo/classification/ddc/537 ddc:537 info:eu-repo/classification/ddc/539 ddc:539
437	Machine Learning for Speech Forensics and Hypersonic Vehicle Applications Emily R Bartusiak (6630773) 06 December 2022 (has links) <p>Synthesized speech may be used for nefarious purposes, such as fraud, spoofing, and misinformation campaigns. We present several speech forensics methods based on deep learning to protect against such attacks. First, we use a convolutional neural network (CNN) and transformers to detect synthesized speech. Then, we investigate closed set and open set speech synthesizer attribution. We use a transformer to attribute a speech signal to its source (i.e., to identify the speech synthesizer that created it). Additionally, we show that our approach separates different known and unknown speech synthesizers in its latent space, even though it has not seen any of the unknown speech synthesizers during training. Next, we explore machine learning for an objective in the aerospace domain.</p> <p><br></p> <p>Compared to conventional ballistic vehicles and cruise vehicles, hypersonic glide vehicles (HGVs) exhibit unprecedented abilities. They travel faster than Mach 5 and maneuver to evade defense systems and hinder prediction of their final destinations. We investigate machine learning for identifying different HGVs and a conic reentry vehicle (CRV) based on their aerodynamic state estimates. We also propose a HGV flight phase prediction method. Inspired by natural language processing (NLP), we model flight phases as “words” and HGV trajectories as “sentences.” Next, we learn a “grammar” from the HGV trajectories that describes their flight phase transition patterns. Given “words” from the initial part of a HGV trajectory and the “grammar”, we predict future “words” in the “sentence” (i.e., future HGV flight phases in the trajectory). We demonstrate that this approach successfully predicts future flight phases for HGV trajectories, especially in scenarios with limited training data. We also show that it can be used in a transfer learning scenario to predict flight phases of HGV trajectories that exhibit new maneuvers and behaviors never seen before during training.</p> Audio processing Computer vision Digital forensics Deep learning machine learning deep learning speech forensics media forensics convolutional neural network transformer convolutional transformer ensemble spectrogram analysis mel spectrogram analysis synthesized speech detection synthesized speech attribution closed set open set t-stochastic neighbor embedding latent space analysis hypersonics hypersonic glide vehicles vehicle classification flight phase prediction stochastic grammar k-nearest neighbors support vector machine probabilistic context-free grammar automatic distillation of structure generalized earley parser transfer learning

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