Table of Contents

Abstract: Graph search algorithms have exploited graph extremities, such as the leaves of a tree and the simplicial vertices of a chordal graph. Recently, several well-known graph search algorithms have been collectively expressed as two generic algorithms called MLS and MLSM. In this paper, we investigate the properties of the vertex that is numbered 1 by MLS on a chordal graph and by MLSM on an arbitrary graph. We explain how this vertex is an extremity of the graph. Moreover, we show the remarkable property that the minimal separators included in the neighborhood of this vertex are totally ordered by inclusion.

Abstract: The present paper describes a novel recognition method of pulmonary nodules (i.e., cancer candidates) in thoracic computed tomography scans by use of three-dimensional spherical and cylindrical models that represent nodules and blood vessels, respectively. The anatomical validity of these object models and their fidelity to computed tomography scans are evaluated based on the Bayes theorem. The nodule recognition is employed by the maximum a posteriori estimation. The proposed method is applied to 26 actual computed tomography scans, and experimental results are shown.

Abstract: Given a sequence T = t₀t₁ . . . t_n-1 of size n = |T|, with symbols from a fixed alphabet Σ, (|Σ| ≤ n), the suffix array provides a listing of all the suffixes of T in a lexicographic order. Given T, the suffix sorting problem is to construct its suffix array. The direct suffix sorting problem is to construct the suffix array of T directly without using the suffix tree data structure. While algorithims for linear time, linear space direct suffix sorting have been proposed, the actual constant in the linear space is still a major concern, given that the applications of suffix trees and suffix arrays (such as in whole-genome analysis) often involve huge data sets. In this work, we reduce the gap between current results and the minimal space requirement. We introduce an algorithm for the direct suffix sorting problem with worst case time complexity in O(n), requiring only (1 2/3 n log n ¡ n log |Σ| + O(1)) bits in memory space. This implies 5 2/3 n+O(1) bytes for total space requirment, (including space for both the output suffix array and the input sequence T) assuming n ≤ 2³², |Σ| ≤ 256, and 4 bytes per integer. The basis of our algorithm is an extension of Shannon-Fano-Elias codes used in source coding and information theory. This is the first time information-theoretic methods have been used as the basis for solving the suffix sorting problem.

Abstract: Both learning how to program and understanding algorithms or data structures are often difficult. This paper presents three complementary approaches that we employ to help our students in learning to program, especially during the first term of their study. We use a web-based programming task database as an easy and risk-free environment for taking the first steps in programming Java. The Animal algorithm visualization system is used to visualize the dynamic behavior of algorithms and data structures. We complement both approaches with tutorial videos on using the Eclipse IDE. We also report on the experiences with this combined approach.

Abstract: In recent years, many tools have been proposed to reduce programming learning difficulties felt by many students. Our group has contributed to this effort through the development of several tools, such as VIP, SICAS, OOP-Anim, SICAS-COL and H-SICAS. Even though we had some positive results, the utilization of these tools doesn’t seem to significantly reduce weaker student’s difficulties. These students need stronger support to motivate them to get engaged in learning activities, inside and outside classroom. Nowadays, many technologies are available to create contexts that may help to accomplish this goal. We consider that a promising path goes through the integration of solutions. In this paper we analyze the features, strengths and weaknesses of the tools developed by our group. Based on these considerations we present a new environment, integrating different types of pedagogical approaches, resources, tools and technologies for programming learning support. With this environment, currently under development, it will be possible to review contents and lessons, based on video and screen captures. The support for collaborative tasks is another key point to improve and stimulate different models of teamwork. The platform will also allow the creation of various alternative models (learning objects) for the same subject, enabling personalized learning paths adapted to each student knowledge level, needs and preferential learning styles. The learning sequences will work as a study organizer, following a suitable taxonomy, according to student’s cognitive skills. Although the main goal of this environment is to support students with more difficulties, it will provide a set of resources supporting the learning of more advanced topics. Software engineering techniques and representations, object orientation and event programming are features that will be available in order to promote the learning progress of students.

Abstract: This paper is a review which presents and explains the decomposition of graphs by clique minimal separators. The pace is leisurely, we give many examples and figures. Easy algorithms are provided to implement this decomposition. The historical and theoretical background is given, as well as sketches of proofs of the structural results involved.