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Computer Simulations of Novel Annihilating Random WalkProblemsBrune, Ryan Tanner 27 October 2022 (has links)
No description available.
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ALGEBRAIC METHODS FOR LINK PREDICTIONIN VERY LARGE NETWORKSCoskun, Mustafa, Coskun 06 September 2017 (has links)
No description available.
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Spanning k-Trees and Loop-Erased Random SurfacesParsons, Kyle 27 October 2017 (has links)
No description available.
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Efficient and Effective Local Algorithms for Analyzing Massive GraphsWu, Yubao 31 May 2016 (has links)
No description available.
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A probabilistic model of virus transport through packed bedsShah, Jayesh R. January 1989 (has links)
No description available.
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A comparative analysis on the predictive performance of LSTM and SVR on Bitcoin closing prices.Rayyan, Hakim January 2022 (has links)
Bitcoin has since its inception in 2009 seen its market capitalisation rise to a staggering 846 billion US Dollars making it the world’s leading cryptocurrency. This has attracted financial analysts as well as researchers to experiment with different models with the aim of developing one capable of predicting Bitcoin closing prices. The aim of this thesis was to examine how well the LSTM and the SVR models performed in predicting Bitcoin closing prices. As a measure of performance, the RMSE, NRMSE and MAPE were used as well as the Random walk without drift as a benchmark to further contextualise the performance of both models. The empirical results show that the Random walk without drift yielded the best results for both the RMSE and NRMSE scoring 1624.638 and 0.02525, respectively while the LSTM outperformed both the Random Walk without drift and the SVR model in terms of the MAPE scoring 0.0272 against 0.0274 for both the Random walk without drift and SVR, respectively. Given the performance of the Random Walk against both models, it cannot be inferred that the LSTM and SVR models yielded statistically significant predictions. / <p>Aaron Green</p>
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Heat Transfer Issues in Thin-Film Thermal Radiation DetectorsBarry, Mamadou Yaya 22 December 1999 (has links)
The Thermal Radiation Group at Virginia Polytechnic Institute and State University has been working closely with scientists and engineers at NASA's Langley Research Center to develop accurate analytical and numerical models suitable for designing next-generation thin-film thermal radiation detectors for earth radiation budget measurement applications. The current study provides an analytical model of the notional thermal radiation detector that takes into account thermal transport phenomena, such as the contact resistance between the layers of the detector, and is suitable for use in parameter estimation. It was found that the responsivity of the detector can increase significantly due to the presence of contact resistance between the layers of the detector. Also presented is the effect of doping the thermal impedance layer of the detector with conducting particles in order to electrically link the two junctions of the detector. It was found that the responsivity and the time response of the doped detector decrease significantly in this case. The corresponding decrease of the electrical resistance of the doped thermal impedance layer is not sufficient to significantly improve the electrical performance of the detector. Finally, the "roughness effect" is shown to be unable to explain the decrease in the thermal conductivity often reported for thin-film layers / Master of Science
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On the Convergence to Uniformity of a Random Walk on SU(N)Hoti, Rilind, Lundqvist, Viktor January 2024 (has links)
We study a random walk on the special unitary group SU(N) consisting of a product of matrices chosen Haar uniformly from a fixed conjugacy class. In particular, we make use of the representation theory of matrix Lie groups to show two results about the rate of convergence of the random walk's distribution to the Haar measure in total variation distance. We derive a lower bound in total variation distance before a threshold number of steps, which appears to be an example of a cut-off phenomenon, and for dimension N=2 we prove exponentially fast convergence.
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Étude de la marche aléatoire biaisée en milieu aléatoireLaliberté, Nicolas 11 1900 (has links)
No description available.
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Superdiffusion in Scale-Free Inhomogeneous Environments / Superdiffusion in Skalenfreien Inhomogenen MedienBrockmann, Dirk 04 July 2003 (has links)
No description available.
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