College Students‘ GIS Spatial Concept Knowledge Assessed by Concept Maps

The development of spatial thinking proficiency has been increasingly demanded in Geographic Information System (GIS) education. Despite this educational trend, there is little empirical research on college students' spatial concept knowledge, which critically affects the quality of spatial thinking. This study addressed the following three research questions: 1) What differences exist between students' understandings of spatial concepts at the beginning, middle, and end of an introductory-level GIS course?, 2) What spatial misconceptions students may possess while taking an introductory-level GIS course?, and 3) Which spatial concepts are easy or hard for undergraduate students to understand? The researcher asked twelve participants who were taking an introductory-level GIS course to create concept maps about space and revised their concept maps in three experiment sessions. For the first question, the researcher scored the sixty obtained concept maps and statistically analyzed those scores to examine if there is any significant difference among the scores of the three experiment sessions. For the second question, the researcher examined participants' misconceptions by analyzing the incorrect statements of distortion, map projection, and scale. For the third question, the researcher statistically analyzed concept-based scores to examine if there is any significant difference among the scores of three different complexity levels. A main finding for the first question was that there was a significant difference among the scores of the concept maps created in the first session and the scores of the concept maps revised in the second and third sessions. This implied that participants could successfully revise their own original concept maps in the middle of a semester. The result of the study of the second question indicated that a half of participants misunderstood the concepts of map projections and scale. This result suggested that some undergraduate students may have difficulty shifting from scientifically inappropriate spatial concept knowledge to appropriate knowledge. Analysis of the third question resulted that the concept-based scores of simple spatial concepts are significantly higher than the scores of complicated spatial concepts. This result inferred that participants' scores decreased as the complexity of the concepts increased

Problèmes de graphes motivés par des modèles basse et haute résolution de grands assemblages de protéines

To explain the biological function of a molecular assembly (MA), one has to know its structural description. It may be ascribed to two levels of resolution: low resolution (i.e. molecular interactions) and high resolution (i.e. relative position and orientation of each molecular subunit, called conformation). Our thesis aims to address the two problems from graph aspects.The first part focuses on low resolution problem. Assume that the composition (complexes) of a MA is known, we want to determine all interactions ofsubunits in the MA which satisfies some property. It can be modeled as a graph problem by representing a subunit as a vertex, then a subunit interaction is an edge, and a complex is an induced subgraph. In our work, we use the fact that a subunit has a bounded number of interactions. It leads to overlaying graph with bounded maximum degree. For a graph family F and a fixed integer k, given a hypergraph H = (V (H), E(H)) (whose edges are subsets of vertices) and an integer s, M AX (∆ ≤ k)-F -O VERLAY consists in deciding whether there exists a graph with degree at most k such that there are at least s hyperedges in which the subgraph induced by each hyperedge (complex) contains an element of F. When s = |E(H)|, it is called (∆ ≤ k)-F -O VERLAY . We present complexity dichotomy results (P vs. NP-complete) for MAX (∆ ≤ k)-F-OVERLAY and (∆ ≤ k)-F-OVERLAY depending on pairs (F, k).The second part presents our works motivated by high resolution problem. Assume that we are given a graph representing the interactions of subunits, a finite set of conformations for each subunit and a weight function assessing the quality of the contact between two subunits positioned in the assembly. Discrete Optimization of Multiple INteracting Objects (D OMINO ) aims to find conformations for the subunits maximizing a global utility function. We propose a new approach based on this problem in which the weight function is relaxed, CONFLICT COLORING . We present studies from both theoretical and experimental points of view. Regarding the theory, we provide a complexity dichotomy result and also algorithmic methods (approximation and fixed paramater tracktability). Regarding the experiments, we build instances of CONFLICT COLORING associated with Voronoi diagrams in the plane. The obtained statistics provide information on the dependencies of the existences of a solution, to parameters used in ourexperimental setup.Pour comprendre les fonctions biologiques d’un assemblage moléculaire (AM), il est utile d’en avoir une représentation structurale. Celle-ci peut avoir deux niveaux de résolution : basse résolution (i.e. interactions moléculaires) et haute résolution (i.e. position relative et orientation de chaque sous-unité, appelée conformation). Cette thèse s’intéresse à trouver de telles représentations à l’aide de graphes.Dans la première partie, nous cherchons des représentations basse résolution. Etant donné la composition des complexes d’un AM, notre but est de déterminer les interactions entre ses différentes sous-unités. Nous modélisons l’AM à l’aide d’un graphe : les sous-unités sont les sommets, les interactions entre elles sont les arêtes et un complexe est un sous-graphe induit. Utilisant le fait qu’une sous-unité n’a qu’un nombre limité d’interactions, nous arrivons au problème suivant. Pour un graphe F et un entier k fixés, étant donné un hypergraphe H et un entier s, MAX (∆ ≤ k)-F-OVERLAY consiste à décider s’il existe un graphe de degré au plus k tel qu’au moins s hyperarêtes de H induisent un sous-graphe contenant F (en tant que sous-graphe). La restriction au cas s = |E(H)| est appelée (∆ ≤ k)-F-OVERLAY . Nous donnons une dichotomie de complexité (P vs. NP-complet) pour MAX (∆ ≤ k)-F-OVERLAY et (∆ ≤ k)-F-OVERLAY en fonction du couple (F, k).Dans la seconde partie, nous nous attaquons à la haute résolution. Nous sont donnés un graphe représentant les interactions entre sous-unités, un ensemble de conformations possibles pour chaque sous-unité et une fonction de poids représentant la qualité de contact entre les conformations de deux sous-unités interagissant dans l’assemblage. Le problème Discrete Optimization of Multiple INteracting Objects (D OMINO ) consiste alors à trouver les conformations pour les sous-unités qui maximise une fonction d’utilité globale. Nous proposons une nouvelle approche à ce problème en relâchant la fonction de poids, ce qui mène au problème de graphe CONFLICT COLORING . Nous donnons tout d’abord des résultats de complexité et des algorithmes (d’approximation et à paramètre fixé). Nous menons ensuite des expérimentations sur des instances de CONFLICT COLORING associées à des diagrammes de Voronoi dans le plan. Les statistiques obtenues nous informent sur comment les parmètres de notre montage expérimental influe sur l’existence d’une solution

Electronic tools for designing charts and graphs

Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1983.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCHIncludes bibliographical references (leaves 94-99).This thesis explores the issues involved in designing an interactive chart and graph making system, especially tailored to the needs of the graphic designer. It defines a set of user interface requirements and describe the implementation of the prototype software system.by Mary Jones.M.S.V.S

Investigation of land use of northern megalopolis using ERTS-1 imagery

Primary objective was to produce a color-coded land use map and digital data base for the northern third of Megalopolis. Secondary objective was to investigate possible applications of ERTS products to land use planning. Many of the materials in this report already have received national, dissemination as a result of unexpected interest in land use surveys from ERTS. Of special historical interest is the first comprehensive urban-type land use map from space imagery, which covered the entire state of Rhode Island and was made from a single image taken on 28 July 1972

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)

Randomization does not help much, comparability does

Following Fisher, it is widely believed that randomization "relieves the experimenter from the anxiety of considering innumerable causes by which the data may be disturbed." In particular, it is said to control for known and unknown nuisance factors that may considerably challenge the validity of a result. Looking for quantitative advice, we study a number of straightforward, mathematically simple models. However, they all demonstrate that the optimism with respect to randomization is wishful thinking rather than based on fact. In small to medium-sized samples, random allocation of units to treatments typically yields a considerable imbalance between the groups, i.e., confounding due to randomization is the rule rather than the exception. In the second part of this contribution, we extend the reasoning to a number of traditional arguments for and against randomization. This discussion is rather non-technical, and at times even "foundational" (Frequentist vs. Bayesian). However, its result turns out to be quite similar. While randomization's contribution remains questionable, comparability contributes much to a compelling conclusion. Summing up, classical experimentation based on sound background theory and the systematic construction of exchangeable groups seems to be advisable

A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms

This work was partly supported by the MINECO Under the TEC2015-64718-R Project, the Salvador de Madariaga Mobility Grants 2017 and the Consejería de Economía, Innovación, Ciencia y Empleo (Junta de Andalucía, Spain) under the Excellence Project P11-TIC-7103. The study was conducted in association with the National Institute for Health Research Collaborations for Leadership in Applied Health Research and Care (NIHR CLAHRC) East of England (EoE). The Project was supported by the UK Medical Research Council (Grant No. GO 400061) and European Autism Interventions — a Multicentre Study for Developing New Medications (EU-AIMS); EU-AIMS has received support from the Innovative Medicines Initiative Joint Undertaking Under Grant Agreement No. 115300, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in-kind contribution. During the period of this work, M-CL was supported by the OBrien Scholars Program in the Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health (CAMH) and The Hospital for Sick Children, Toronto, the Academic Scholar Award from the Department of Psychiatry, University of Toronto, the Slaight Family Child and Youth Mental Health Innovation Fund, CAMH Foundation, and the Ontario Brain Institute via the Province of Ontario Neurodevelopmental Disorders (POND) Network; MVL was supported by the British Academy, Jesus College Cambridge, Wellcome Trust, and an ERC Starting Grant (ERC-2017-STG; 755816); SB-C was supported by the Autism Research Trust. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health, UK.Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One of the difficulties in investigating differences between the sexes in autism is the small sample sizes of available imaging datasets with mixed sex. Thus, the majority of the investigations have involved male samples, with females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal differences in regional brain structure between individuals with autism and typically developing participants. A four-class classification problem (sex and condition) is specified, with theoretical restrictions based on the evaluation of a novel upper bound in the resubstitution estimate. These conditions were imposed on the classifier complexity and feature space dimension to assure generalizable results from the training set to test samples. Accuracies above 80% on gray and white matter tissues estimated from voxel-based morphometry (VBM) features are obtained in a sample of equal-sized high-functioning male and female adults with and without autism (N=120, n=30/group). The proposed learning machine revealed how autism is modulated by biological sex using a low-dimensional feature space extracted from VBM. In addition, a spatial overlap analysis on reference maps partially corroborated predictions of the “extreme male brain” theory of autism, in sexual dimorphic areas.This work was partly supported by the MINECO Under the TEC2015-64718-R Project, the Salvador de Madariaga Mobility Grants 2017 and the Consejería de Economía, Innovación, Ciencia y Empleo (Junta de Andalucía, Spain) under the Excellence Project P11-TIC-7103The Project was supported by the UK Medical Research Council (Grant No. GO 400061) and European Autism Interventions — a Multicentre Study for Developing New Medications (EU-AIMS)EU-AIMS has received support from the Innovative Medicines Initiative Joint Undertaking Under Grant Agreement No. 115300MVL was supported by the British Academy, Jesus College Cambridge, Wellcome Trust, and an ERC Starting Grant (ERC-2017-STG; 755816