SVD Factorization for Tall-and-Fat Matrices on Map/Reduce Architectures

We demonstrate an implementation for an approximate rank-k SVD factorization, combining well-known randomized projection techniques with previously implemented map/reduce solutions in order to compute steps of the random projection based SVD procedure, such QR and SVD. We structure the problem in a way that it reduces to Cholesky and SVD factorizations on $k \times k$ matrices computed on a single machine, greatly easing the computability of the problem.Comment: There are mistakes in the approac

Pinning of a solid--liquid--vapour interface by stripes of obstacles

We use a macroscopic Hamiltonian approach to study the pinning of a solid--liquid--vapour contact line on an array of equidistant stripes of obstacles perpendicular to the liquid. We propose an estimate of the density of pinning stripes for which collective pinning of the contact line happens. This estimate is shown to be in good agreement with Langevin equation simulation of the macroscopic Hamiltonian. Finally we introduce a 2--dimensional mean field theory which for small strength of the pinning stripes and for small capillary length gives an excellent description of the averaged height of the contact line.Comment: Plain tex, 12 pages, 3 figures available upon reques

Temporal Continuity Based Unsupervised Learning for Person Re-Identification

Person re-identification (re-id) aims to match the same person from images taken across multiple cameras. Most existing person re-id methods generally require a large amount of identity labeled data to act as discriminative guideline for representation learning. Difficulty in manually collecting identity labeled data leads to poor adaptability in practical scenarios. To overcome this problem, we propose an unsupervised center-based clustering approach capable of progressively learning and exploiting the underlying re-id discriminative information from temporal continuity within a camera. We call our framework Temporal Continuity based Unsupervised Learning (TCUL). Specifically, TCUL simultaneously does center based clustering of unlabeled (target) dataset and fine-tunes a convolutional neural network (CNN) pre-trained on irrelevant labeled (source) dataset to enhance discriminative capability of the CNN for the target dataset. Furthermore, it exploits temporally continuous nature of images within-camera jointly with spatial similarity of feature maps across-cameras to generate reliable pseudo-labels for training a re-identification model. As the training progresses, number of reliable samples keep on growing adaptively which in turn boosts representation ability of the CNN. Extensive experiments on three large-scale person re-id benchmark datasets are conducted to compare our framework with state-of-the-art techniques, which demonstrate superiority of TCUL over existing methods

Theoretical and Experimental Analysis of the Equilibrium Contours of Liquid Bridges of Arbitrary Shape

The equilibrium shape of the liquid bridge interface is analyzed theoretically and experimentally.Both axisymmetric and nonaxisymmetric perturbations are considered. The axisymmetric deviationsare those related to volume effects, the difference between the radii of the disks, and the axial forcesacting on the liquid bridge. The nonaxisymmetric deviations are those due to the eccentricity of thedisk and the action of lateral forces. The theoretical study is performed using three differenttechniques: ~i! an analytical expansion around the cylindrical solution, ~ii! a finite differencescheme, and ~iii! an approximate numerical approach valid only for slight nonaxisymmetricdeviations. The results of the three methods are compared systematically. There is a very goodagreement between the analytical and the numerical approaches for contours which are close tocylindrical, and the agreement extends to configurations with only moderate deviations fromcylindrical. Experiments are performed using the so-called neutral buoyancy or plateau technique.Theoretical and experimental contours are compared considering a wide range of values for theparameters characterizing the perturbations. In general, the finite difference method providesreasonably accurate predictions even for large deviations of the liquid bridge contour fromcylindrical

Global players, local changes: The European Union's impact on vocational education reforms in Azerbaijan

This dissertation uses Azerbaijan as a case study to investigate how international organizations, particularly the European Union, shape and guide VET policies in developing nations. Through an in-depth case study of Azerbaijan, a non-EU member country that underwent VET reform with EU assistance, this research illuminates the complex interplay of political, economic, and cultural factors shaping the adoption of EU-endorsed VET mechanisms. Employing a qualitative approach grounded in the Cultural Political Economy (CPE) framework and a historical institutionalist perspective, the study unravels motivations driving policy choices and expands the theoretical understanding of EU-Azerbaijan policy transfer in the VET sphere. Findings reveal a dynamic process where both global and national forces interact. While the EU-inspired VET model initially gained legitimacy as a solution to domestic challenges, local actors strategically adapted mechanisms to suit their political and economic interests. Key factors influencing the reform process include human capital deficiencies, skills shortages, centralised governance structures, and a negative perception of the Soviet legacy. The EU's role was significant in problematizing VET underdevelopment, proposing solutions, and catalysing the implementation process. This dissertation enriches the scholarly discourse on VET policy adoption by demonstrating the intertwined nature of global and national forces in reforms. It addresses a gap in the literature by elucidating the historical context shaping post-Soviet VET transformations outside the EU. The findings contribute to theoretical debates on policy transfer within the VET sector, offering insights into policymakers' motivations, contextual influences, and the complexities of translating global models to localised settings

Detachment force of particles from fluid droplets

We calculate the deformation of a spherical droplet, resulting from the application of a pair of opposite forces to particles located diametrically opposite at the two ends of the droplet. The free-energy analysis is used to calculate the force–distance curves for the generated restoring forces, arising from the displacement of the particles relative to each other. While the logarithmic dependence of the “de Gennes–Hooke” constant on the particle to droplet size ratio, ν, is rather well known in the limit of very small ν, we find that for more realistic particle to droplet size ratios, i.e. ν = 0.001 to 0.01, the additional constant terms of O(1) constitute a significant correction to previously reported results. We derive the restoring force constant to be 2πγ[0.5 − ln(ν/2)]−1, in perfect agreement with the exact semi-numerical analysis of the same problem. The deviation from the linear force–displacement behaviour, occurring close to the point of detachment, is also investigated. A study of the energy dissipated shows it to be an increasingly dominant component of the work done during the detachment of the particles, as ν decreases. This indicates the existence of a significantly higher energy barrier to desorption of very small particles, compared to the one suggested by their adsorption energy alone. The influence of the line tension on the detachment force is also considered. It is shown that where line tension is important, the contact angle is no longer a constant but instead alters with the displacement of the particles from their equilibrium positions