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Sökning: L4X0:1402 1544

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41.
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42.
  • Tinnsten, Mats (författare)
  • Numerical and experimental study of acoustic and structural optimization
  • 1999
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The main objective with this thesis has been to create a procedure (method and program code) that enables automatic optimization of acoustic response from vibrating structures. Automatic means that the proposed method, on its own, should be able to find the desired acoustic quantities for a given problem formulation by altering given variables. The main parts of such an optimization process are: availability to perform structural dynamic analysis, acoustic analysis, and optimization analysis. The structural dynamic analysis comprises eigenmode and response analyses, tools necessary to calculate surface velocities for the actual structure. These calculations are performed using a modified version of the finite element (FE) code FEMP [31]. This FE code is implemented in the acoustic optimization code and used in Papers B, C, D, E, and F. The surface velocities are used as input in the acoustic analyses. The acoustic analyses in this thesis comprises calculation of sound pressure and/or sound intensity amplitudes in specified regions outside vibrating structures surrounded by air. Calculation of the acoustic quantities (pressure and intensity) is performed using a boundary element (BE) code. The BE code is developed and used in Papers C, D, E, and F. The numerical results in Paper C is compared with experimental results A slightly modified version of the optimization routine MMA (method of moving asymptotes) [21] is used for optimization analysis together with the above-mentioned FE and BE codes. The MMA is in Paper A used for a purely structural optimization problem. The acoustic optimization process, comprising FE, BE, and optimization analysis, is performed in Papers D, E, and F. A comparison between numerical and experimental results was also performed in Paper F.
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43.
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44.
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45.
  • Abdikalikova, Zamira (författare)
  • Some new results concerning boundedness and compactness for embeddings between spaces with multiweighted derivatives
  • 2009
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • This Doctoral Thesis consists of five chapters, which deal with a new Sobolev type function space called the space with multiweighted derivatives. This space is a generalization of the usual one dimensional Sobolev space. As basis for this space serves some differential operators containing weight functions.Chapter 1 is an introduction, where, in particular, the importance to study function spaces with weights is discussed and motivated. In Chapter 2 we prove some new estimates for each function in a Tchebychev system. In order to be able to study compactness of the embeddings from Chapter 3 such estimates are crucial.In Chapter 3 we rewrite and present some results of L. D. Kudryavtsev, where he investigated one dimensional Sobolev spaces. Moreover, in this chapter we rewrite and discuss some analogous results by B. L. Baidel'dinov for generalized Sobolev spaces. These results are not available in the Western literatures in this way and they are crucial for the proofs of the main results in Chapter 4. In Chapter 4 we prove some embedding theorems for these new generalized Sobolev spaces. The main results of Kudryavtsev and Baidel'dinov about characterization of the behavior of functions at a singularity take place in weak degeneration of the spaces. However, with the help of our new embedding theorems we can extend theseresults to the case of strong degeneration.The main aim of Chapter 5 is to establish boundedness and compactness of the embedding considered in Chapter 4.In Chapter 4 basically only sufficient conditions for boundedness of this embedding were obtained. In Chapter 5 we obtain necessary and sufficient conditions for boundedness and compactness of this embedding and the main results are proved in a different way.
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46.
  • Abid, Nosheen, 1993- (författare)
  • Unsupervised Curriculum Learning Case Study: Earth Observation UCL4EO
  • 2024
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Earth Observation (EO) data, collected via satellites and remote sensing technologies, is crucial for understanding, managing, and conserving the Earth. It enables humankind to monitor environmental changes, such as natural disasters, urban growth, and climate shifts, assisting informed decisions and proactive measures. Early Remote Sensing (RS) heavily relied on statistical methods and expert domain knowledge, but the advent of machine learning has revolutionized EO data processing, enhancing efficiency and accuracy. Conventional machine learning (ML) models require expensive and labor-intensive data labeling. In contrast, unsupervised ML techniques can learn features from data without the need for manual labeling, making the process more efficient and cost-effective.This thesis presents an innovative Unsupervised Curriculum Learning (UCL) approach utilizing advanced deep learning (DL) models to classify EO data, referred to as UCL4EO. This approach eliminates the need for manual data labeling in training the DL model. The UCL framework comprises i) a DL model, typically a Convolutional Neural Network (CNN) tailored for feature extraction from image data, ii) a clustering technique to cluster deep features, and iii) a selection operation to select representative samples from these clusters. The CNN extracts meaningful features from images, subjected to a clustering algorithm to create pseudo-labels. After identifying the initial clusters, representative samples from each cluster are chosen using the UCL selection operation to fine-tune the feature extractor. The stated process is repeated iteratively until convergence. The proposed UCL approach progressively learns and incorporates salient data features in an unsupervised manner by utilizing pseudo-labels.UCL serves as a proof of concept in a simpler setting of detection tasks on RS and aerial imagery. Specifically, the UCL framework is employed to identify water bodies using three RGB datasets, encompassing both low and high-resolution RS and aerial imagery. While UCL has been extensively examined with RGB imagery, it has been adapted to benefit from the enhanced capabilities of multi-spectral satellite imagery. This adaptation enables UCL to generalize to multi-spectral imagery from Sentinel-2 to detect forest fires in Australia. UCL undergoes subsequent improvements and is further investigated to identify utility poles in high-resolution UAV images. These gray-scale images of utility poles pose computer vision challenges, including issues like occlusion and cropping, where a significant portion of the image contains the background and only a slight appearance of the utility pole. Extensive experimentation on the mentioned tasks effectively showcases UCL's adaptive learning capabilities, producing promising results. The achieved accuracy surpassed those of supervised methods in cross-domain adaptation on similar tasks, underscoring the effectiveness of the proposed algorithm.In these investigations, two datasets are generated using Sentinel-2: one for water bodies - PakSAT and the other for Australian forest fire. Cloud cover significantly hinders the acquisition of satellite imagery depicting the Earth's surface. In preparing these datasets, this work employs available cloud masking solutions to avoid the images with cloud cover. Later, this thesis examines cloud detection and Cloud Optical Thickness (COT) estimation from Sentinel-2 imagery. We employed advanced machine-learning techniques, achieving state-of-the-art performance for cloud cover tasks.The scope of UCL has been extended to encompass multi-class classification tasks in the domain of RS data, referred to as Multi-class UCL. Multi-class UCL progressively acquires knowledge about various categories on multi-scale resolution. To investigate Multi-class UCL, we have used three publicly available datasets of Sentinel-2 and aerial imagery: EuroSAT, SAT-6, and RSSCN7. The evaluation of Multi-class UCL’s performance incorporates the concept of a confusion matrix to compare the predicted labels with the actual labels. Comprehensive experiments conducted on the specified datasets revealed better cross-domain adaptation capabilities compared to supervised methods, thereby demonstrating the effectiveness of Multi-class UCL.In addition to the application in RS data, UCL has been investigated in other domains of EO, such as undersea imagery. Furthermore, UCL has also been used for tasks like natural scene classification, medical imaging, and document analysis, demonstrating its versatility and broad applicability. Further exploration of UCL could involve improving the process of generating pseudo-labels through deep learning techniques.
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47.
  • Abiri, Olufunminiyi (författare)
  • Non-local models in manufacturing simulations
  • 2016
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Ductile fracture presents challenges with respect to material modelling andnumerical simulations of localization. The strain and damage localization maybe unwanted as it indicates a failure in the process or, as in the case ofmachining and cutting, a wanted phenomenon to be controlled. The latterrequires a higher accuracy regarding the modelling of the underlying coupledplastic and fracturing/damage behaviour of the material, metal in the currentcontext as well as the stability and robustness of the simulation procedure.This aim of this work is to develop, evaluate and implement formulations thatcan efficiently and reliably handle localization problems in machiningsimulations. The focus is on non-local models. The non-local models extendthe standard continuum mechanics theory by using non-local continuumtheory in order to achieve mesh independent results when simulating fractureor shear localization.The non-local damage model is implemented and various formulations areevaluated in a Matlab™ based finite element code. The chosen algorithm wasthen implemented in commercial software. The implementations remedy themesh sensitivity problem and gives convergent solution for metal cuttingsimulations with reasonable cost. The length scale associated with the nonlocalmodels are in the current context considered as a numericalregularization parameter. The model has been applied in machiningsimulations and compared with measurements from industry.Keywords: Finite element simulation; Non-local damage; Plasticity; Machining
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48.
  • Abrahamsson, Lena (författare)
  • Att återställa ordningen : könsmönster och förändring i arbetsorganisationer
  • 1999
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Avhandlingen är en könsteoretisk studie av organisationsförändringar i industrin - med fokus på kvinnor som arbetar med produktionsarbete. Avhandlingen beskriver vad som händer med organisationsstrukturen och med genusordningen i organisationen när företaget försöker införa en platt integrerad arbetsorganisation. Empirin omfattar åtta svenska industriföretag: fem massa- och papper, ett tvätteri, ett charkuteri och ett elektronikföretag. Resultaten visar att återställare och dämpande krafter ute i lokala arbetsorganisationer drar organisationen tillbaka till sitt ursprungliga utseende. Många av återställarna har koppling till "kön" och genusordningen. De lokala organisationernas utgångsläge inför organisationsförändringarna bygger ofta på en struktur som ger olika villkor för kvinnor och för män. Denna könsordning är en förklaring till många återställare och det är dessutom ofta just den som återställs. Genusordningens segregerande och hierakiserande krafter gör att människor lätt återskapar gamla könsmönster i nya organisationer. Detta innebär att de nya organisationsmodellernas strävan efter integrering, tillplattning, kompetensutveckling och flexibilitet riskerar att motarbetas. En stark och omfattande könsmärkning och könsuppdelning i utgångsläget inför organisationsförändringen innebär många återställare och därmed svårare att införa den platta integrerade arbetsorganisationen.
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49.
  • Abylayeva, Akbota (författare)
  • Inequalities for some classes of Hardy type operators and compactness in weighted Lebesgue spaces
  • 2016
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • This PhD thesis is devoted to investigate weighted differential Hardy inequalities and Hardy-type inequalities with the kernel when the kernel has an integrable singularity, and also the additivity of the estimate of a Hardy type operator with a kernel.The thesis consists of seven papers (Papers 1, 2, 3, 4, 5, 6, 7) and an introduction where a review on the subject of the thesis is given. In Paper 1 weighted differential Hardy type inequalities are investigated on the set of compactly supported smooth functions, where necessary and sufficient conditions on the weight functions are established for which this inequality and two-sided estimates for the best constant hold. In Papers 2, 3, 4 a more general class of -order fractional integrationoperators are considered including the well-known classical Weyl, Riemann-Liouville, Erdelyi-Kober and Hadamard operators. Here 0 <  < 1. In Papers 2 and 3 the boundedness and compactness of two classes of such operators are investigated namely of Weyl and Riemann-Liouville type, respectively, in weighted Lebesgue spaces for 1 < p ≤ q < 1 and 0 < q < p < ∞. As applications some new results for the fractional integration operators of Weyl, Riemann-Liouville, Erdelyi-Kober and Hadamard are given and discussed.In Paper 4 the Riemann-Liouville type operator with variable upper limit is considered. The main results are proved by using a localization method equipped with the upper limit function and the kernel of the operator. In Papers 5 and 6 the Hardy operator with kernel is considered, where the kernel has a logarithmic singularity. The criteria of the boundedness and compactness of the operator in weighted Lebesgue spaces are given for 1 < p ≤ q < ∞ and 0 < q < p < ∞, respectively. In Paper 7 we investigated the weighted additive estimates for integral operators K+ and K¯ defined byK+ ƒ(x) := ∫ k(x,s) ƒ(s)ds,  K¯ ƒ(x) := ∫ k(x,s)ƒ(s)ds.It is assumed that the kernel k of the operators K+and K- belongs to the general Oinarov class. We derived the criteria for the validity of these addittive estimates when 1 ≤ p≤ q < ∞
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50.
  • Adewumi, Oluwatosin, 1978- (författare)
  • Vector Representations of Idioms in Data-Driven Chatbots for Robust Assistance
  • 2022
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • This thesis presents resources capable of enhancing solutions of some Natural Language Processing (NLP) tasks, demonstrates the learning of abstractions by deep models through cross-lingual transferability, and shows how deep learning models trained on idioms can enhance open-domain conversational systems. The challenges of open-domain conversational systems are many and include bland repetitive utterances, lack of utterance diversity, lack of training data for low-resource languages, shallow world-knowledge and non-empathetic responses, among others. These challenges contribute to the non-human-like utterances that open-domain conversational systems suffer from. They, hence,have motivated the active research in Natural Language Understanding (NLU) and Natural Language Generation (NLG), considering the very important role conversations (or dialogues) play in human lives. The methodology employed in this thesis involves an iterative set of scientific methods. First, it conducts a systematic literature review to identify the state-of-the-art (SoTA) and gaps, such as the challenges mentioned earlier, in current research. Subsequently, it follows the seven stages of the Machine Learning (ML) life-cycle, which are data gathering (or acquisition), data preparation, model selection, training, evaluation with hyperparameter tuning, prediction and model deployment. For data acquisition, relevant datasets are acquired or created, using benchmark datasets as references, and their data statements are included. Specific contributions of this thesis are the creation of the Swedish analogy test set for evaluating word embeddings and the Potential Idiomatic Expression (PIE)-English idioms corpus for training models in idiom identification and classification. In order to create a benchmark, this thesis performs human evaluation on the generated predictions of some SoTA ML models, including DialoGPT. As different individuals may not agree on all the predictions, the Inter-Annotator Agreement (IAA) is measured. A typical method for measuring IAA is Fleiss Kappa, however, it has a number of shortcomings, including high sensitivity to the number of categories being evaluated. Therefore, this thesis introduces the credibility unanimous score (CUS), which is more intuitive, easier to calculate and seemingly less sensitive to changes in the number of categories being evaluated. The results of human evaluation and comments from evaluators provide valuable feedback on the existing challenges within the models. These create the opportunity for addressing such challenges in future work. The experiments in this thesis test two hypothesis; 1) an open-domain conversational system that is idiom-aware generates more fitting responses to prompts containing idioms, and 2) deep monolingual models learn some abstractions that generalise across languages. To investigate the first hypothesis, this thesis trains English models on the PIE-English idioms corpus for classification and generation. For the second hypothesis, it explores cross-lingual transferability from English models to Swedish, Yorùbá, Swahili, Wolof, Hausa, Nigerian Pidgin English and Kinyarwanda. From the results, the thesis’ additional contributions mainly lie in 1) confirmation of the hypothesis that an open-domain conversational system that is idiom-aware generates more fitting responses to prompts containing idioms, 2) confirmation of the hypothesis that deep monolingual models learn some abstractions that generalise across languages, 3) introduction of CUS and its benefits, 4) insight into the energy-saving and time-saving benefits of more optimal embeddings from relatively smaller corpora, and 5) provision of public access to the model checkpoints that were developed from this work. We further discuss the ethical issues involved in developing robust, open-domain conversational systems. Parts of this thesis are already published in the form of peer-reviewed journal and conference articles.
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