CAUSES OF EARLY SCHOOL LEAVING AND PREVENTION MEASURES: SCHOOL DIRECTORS’ INSIGHTS

The following study explores the phenomenon of early school leaving and related prevention strategies, focusing on the region of Crete, an island in Greece which has high early school leaving rates. This is a qualitative research focused on the opinions and attitudes of the elementary and secondary school units’ directors. Thirteen semi-structured interviews were conducted, showing the interviewees’ opinions about the reasons students leave school in this specific district, the applied prevention measures, and their evaluation. It is noted that the frequency of early school leaving in the local high schools and lyceums is high, while in the elementary schools it is low, which is mainly caused by the students’ decision to enter the job market, help their family agricultural business, and create a family of their own or get married -especially the female students. Furthermore, participants state that they apply certain prevention measures, which include regular communication with the close family circle and with students at risk. Finally, they state that the effectiveness of the measures implemented depends - to a large extent - on the funding provided to schools, mainly as recruitment of specialized staff.  Article visualizations

Towards segmentation into surfaces

Image segmentation is a fundamental problem of low level computer vision and is also used as a preprocessing step for a number of higher level tasks (e.g. object detection and recognition, action classification, optical flow and stereo computation etc). In this dissertation we study the image segmentation problem focusing on the task of segmentation into surfaces. First we present our unifying framework through which mean shift, bilateral filtering and anisotropic diffusion can be described. Three new methods are also described and implemented and the most prominent of them, called Color Mean Shift (CMS), is extensively tested and compared against the existing methods. We experimentally show that CMS outperforms the other methods i.e., creates more uniform regions and retains equally well the edges between segments. Next we argue that color based segmentation should be a two stage process; edge preserving filtering, followed by pixel clustering. We create novel segmentation algorithms by coupling the previously described filtering methods with standard grouping techniques. We compare all the segmentation methods with current state of the art grouping methods and show that they produce better results on the Berkeley and Weizmann segmentation datasets. A number of other interesting conclusions are also drawn from the comparison. Then we focus on surface normal estimation techniques. We present two novel methods to estimate the parameters of a planar surface viewed by a moving robot when the odometry is known. We also present a way of combining them and integrate the measurements over time using an extended Kalman filter. We test the estimation accuracy by demonstrating the ability of the system to navigate in an indoor environment using exclusively vision. We conclude this dissertation with a discussion on how color based segmentation can be integrated into a structure from motion framework that computes planar surfaces using homographies

Bilateral symmetry of object silhouettes under perspective projection

Symmetry is an important property of objects and is exhibited in different forms e.g., bilateral, rotational, etc. This paper presents an algorithm for computing the bilateral symmetry of silhouettes of shallow objects under perspective distortion, exploiting the invariance of the cross ratio to projective transformations. The basic idea is to use the cross ratio to compute a number of midpoints of cross sections and then fit a straight line through them. The goodness-of-fit determines the likelihood of the line to be the axis of symmetry. We analytically estimate the midpoint’s location as a function of the vanishing point for a given object silhouette. Hence finding the symmetry axis amounts to a 2D search in the space of vanishing points. We present experiments on two datasets as well as internet images of symmetric objects that validate our approach. under perspectivities, we analytically compute a set of midpoints of the object as a function of the vanishing point. Then, we fit a straight line passing through the midpoints. The goodness-of-fit defines the likelihood of this line to be a symmetry axis. Using the proposed method, searching for the symmetry axis is reduced to searching for a vanishing point. Our approach is global in the sense that we consider the whole silhouette of the object rather than small parts of it. The results show that the method presented here is capable of finding axes of symmetry of considerably distorted perspective images. 2 Related Work

Εισαγωγή στους κβαντικούς υπολογιστές, στους κβαντικούς αλγορίθμους για μηχανική μάθηση, σχεδιασμός και υλοποίηση ενός κβαντικού Kmeans

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) "Επιστήμη Δεδομένων και Μηχανική Μάθηση

A Distributed Algorithm for Constructing a Generalization of de Bruijn Graphs

De Bruijn graphs possess many characteristics that make them a suitable choice for the topology of an overlay network. These include constant degree at each node, logarithmic diameter and a highly-regular topology that permits nodes to make strong assumptions about the global structure of the network. We propose a distributed protocol that constructs an approximation of a de Bruijn graph in the presence of an arbitrary number of nodes. We show that the degree of each node is constant and that the diameter of the network is no worse than 2logN, where N is the number of nodes. The cost of the join and the departure procedures are O(logN) in the worst case. To the best of our knowledge, this is the first distributed protocol that provides such deterministic guarantees

Mesh management methods in finite element simulations of orthodontic tooth movement

In finite element simulations of orthodontic tooth movement, one of the challenges is to represent long term tooth movement. Large deformation of the periodontal ligament and large tooth displacement due to bone remodelling lead to large distortions of the finite element mesh when a Lagrangian formalism is used. We propose in this work to use an Arbitrary Lagrangian Eulerian (ALE) formalism to delay remeshing operations. A large tooth displacement is obtained including effect of remodelling without the need of remeshing steps but keeping a good-quality mesh. Very large deformations in soft tissues such as the periodontal ligament is obtained using a combination of the ALE formalism used continuously and a remeshing algorithm used when needed. This work demonstrates that the ALE formalism is a very efficient way to delay remeshing operations

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results

Computer simulation of periprosthetic bone remodelling after total hip arthroplasty

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