Development of fourth-grade students’ understanding of experimental and theoretical probability

Students explored variation and expectation in a probability activity at the end of the first year of a 3-year longitudinal study across grades 4-6. The activity involved experiments in tossing coins both manually and with simulation using the graphing software, TinkerPlots. Initial responses indicated that the students were aware of uncertainty, although an understanding of chance concepts appeared limited. Predicting outcomes of 10 tosses reflected an intuitive notion of equiprobability, with little awareness of variation. Understanding the relationship between experimental and theoretical probability did not emerge until multiple outcomes and representations were generated with the software.

Stability analysis of STATCOM in distribution networks

This chapter presents the stability analysis based on bifurcation theory of the distribution static compensator (DSTATCOM) operating both in current control mode as in voltage control mode. The bifurcation analysis allows delimiting the operating zones of nonlinear power systems and hence the computation of these boundaries is of interest for practical design and planning purposes. Suitable mathematical representations of the DSTATCOM are proposed to carry out the bifurcation analyses efficiently. The stability regions in the Thevenin equivalent plane are computed for different power factors at the Point of Common Coupling (PCC). In addition, the stability regions in the control gain space are computed, and the DC capacitor and AC capacitor impact on the stability are analyzed in detail. It is shown through bifurcation analysis that the loss of stability in the DSTATCOM is in general due to the emergence of oscillatory dynamics. The observations are verified through detailed simulation studies.

Functional MRI BOLD response to Tower of London performance of first-episode schizophrenia patients using cortical pattern matching

Due to its three-dimensional folding pattern, the human neocortex; poses a challenge for accurate co-registration of grouped functional; brain imaging data. The present study addressed this problem by; employing three-dimensional continuum-mechanical image-warping; techniques to derive average anatomical representations for coregistration; of functional magnetic resonance brain imaging data; obtained from 10 male first-episode schizophrenia patients and 10 age-matched; male healthy volunteers while they performed a version of the; Tower of London task. This novel technique produced an equivalent; representation of blood oxygenation level dependent (BOLD) response; across hemispheres, cortical regions, and groups, respectively, when; compared to intensity average co-registration, using a deformable; Brodmann area atlas as anatomical reference. Somewhat closer; association of Brodmann area boundaries with primary visual and; auditory areas was evident using the gyral pattern average model.; Statistically-thresholded BOLD cluster data confirmed predominantly; bilateral prefrontal and parietal, right frontal and dorsolateral; prefrontal, and left occipital activation in healthy subjects, while; patients’ hemispheric dominance pattern was diminished or reversed,; particularly decreasing cortical BOLD response with increasing task; difficulty in the right superior temporal gyrus. Reduced regional gray; matter thickness correlated with reduced left-hemispheric prefrontal/; frontal and bilateral parietal BOLD activation in patients. This is the; first study demonstrating that reduction of regional gray matter in; first-episode schizophrenia patients is associated with impaired brain; function when performing the Tower of London task, and supports; previous findings of impaired executive attention and working memory; in schizophrenia.

From true story to Morning Glory : fantasy and reality in journalism movies

Many movies have been made about journalists, including some of cinema’s all-time classics. Fewer have been made about the process of journalism, however, and fewer still have captured that process in a way which reflects the reality of a hyperactive, stressedout trade that at its best confronts power and risks everything to expose its abuse. Those deemed to come close to that gritty realism regularly feature in those polls of the films journalists themselves think are the best representations of their oft-maligned profession. These are the films in which journalists like to think they see themselves. They are part of the professional mythology of journalistic practice.

Green Cultural Criminology : Constructions of Environmental Harm, Consumerism, and Resistance to Ecocide

Over the last two decades, "green criminology" has emerged as a unique area of study, bringing together criminologists and sociologists from a wide range of research backgrounds and varying theoretical orientations. It spans the micro to the macro—from individual-level environmental crimes and victimization to business/corporate violations and state transgressions. There have been few attempts, however, to explicitly or implicitly integrate cultural criminology into green criminology (or vice versa). This book moves towards articulating a green cultural criminological perspective. Brisman and South examine existing overlapping research and offer a platform to support future excursions by green criminologists into cultural criminology’s concern with media images and representations, consumerism and consumption, and resistance. At the same time, they offer an invitation to cultural criminologists to adopt a green view of the consumption landscape and the growth (and depictions) of environmental harms.

Exploring variation in measurement as a foundation for statistical thinking in the elementary school

This study was based on the premise that variation is the foundation of statistics and statistical investigations. The study followed the development of fourth-grade students' understanding of variation through participation in a sequence of two lessons based on measurement. In the first lesson all students measured the arm span of one student, revealing pathways students follow in developing understanding of variation and linear measurement (related to research question 1). In the second lesson each student's arm span was measured once, introducing a different aspect of variation for students to observe and contrast. From this second lesson, students' development of the ability to compare their representations for the two scenarios and explain differences in terms of variation was explored (research question 2). Students' documentation, in both workbook and software formats, enabled us to monitor their engagement and identify their increasing appreciation of the need to observe, represent, and contrast the variation in the data. Following the lessons, a written student assessment was used for judging retention of understanding of variation developed through the lessons and the degree of transfer of understanding to a different scenario (research question 3).

Rules and mechanics

So far in this book, we have seen a large number of methods for generating content for existing games. So, if you have a game already, you could now generate many things for it: maps, levels, terrain, vegetation, weapons, dungeons, racing tracks. But what if you don’t already have a game, and want to generate the game itself? What would you generate, and how? At the heart of any game are its rules. This chapter will discuss representations for game rules of different kinds, along with methods to generate them, and evaluation functions and constraints that help us judge complete games rather than just isolated content artefacts. Our main focus here will be on methods for generating interesting, fun, and/or balanced game rules. However, an important perspective that will permeate the chapter is that game rule encodings and evaluation functions can encode game design expertise and style, and thus help us understand game design. By formalising aspects of the game rules, we define a space of possible rules more precisely than could be done through writing about rules in qualitative terms; and by choosing which aspects of the rules to formalise, we define what aspects of the game are interesting to explore and introduce variation in. In this way, each game generator can be thought of an executable micro-theory of game design, though often a simplified, and sometimes even a caricatured one

Robust conservation decision-making

Decision-making for conservation is conducted within the margins of limited funding. Furthermore, to allocate these scarce resources we make assumptions about the relationship between management impact and expenditure. The structure of these relationships, however, is rarely known with certainty. We present a summary of work investigating the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that achieving robustness in conservation decisions can require a triage approach, and emphasize the need for managers to consider triage not as surrendering but as rational decision making to ensure species persistence in light of the urgency of the conservation problems, uncertainty, and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park, Indonesia. To conserve our environment, conservation managers must make decisions in the face of substantial uncertainty. Further, they must deal with the fact that limitations in budgets and temporal constraints have led to a lack of knowledge on the systems we are trying to preserve and on the benefits of the actions we have available (Balmford & Cowling 2006). Given this paucity of decision-informing data there is a considerable need to assess the impact of uncertainty on the benefit of management options (Regan et al. 2005). Although models of management impact can improve decision making (e.g.Tenhumberg et al. 2004), they typically rely on assumptions around which there is substantial uncertainty. Ignoring this 'model uncertainty', can lead to inferior decision-making (Regan et al. 2005), and potentially, the loss of the species we are trying to protect. Current methods used in ecology allow model uncertainty to be incorporated into the model selection process (Burnham & Anderson 2002; Link & Barker 2006), but do not enable decision-makers to assess how this uncertainty would change a decision. This is the basis of information-gap decision theory (info-gap); finding strategies most robust to model uncertainty (Ben-Haim 2006). Info-gap has permitted conservation biology to make the leap from recognizing uncertainty to explicitly incorporating severe uncertainty into decision-making. In this paper we present a summary of McDonald-Madden et al (2008a) who use an info-gap framework to address the impact of uncertainty in the functional representations of biological systems on conservation decision-making. Furthermore, we highlight the importance of two key elements limiting conservation decision-making - funding and knowledge - and how they interact to influence the best management strategy for a threatened species. Copyright © ASCE 2011.

The National Curriculum and history school textbooks in Australia and the Russian Federation

This chapter analyses recent policy reforms in the national history curriculum in both Australia and the Russian Federation. It analyses those emphases in the national curriculum in history that depict new representations and historiography and the ways in which this is foregrounded in History school textbooks. In doing so, it considers the debates about what version of the nation’s past are deemed significant, and what should be transmitted to future generations of citizens. In this discussion of national history curricula, consideration is made of the curriculum’s officially defined status as an instrument in the process of ideological transformation, and nation-building. The chapter also examines how history textbooks are implicit in this process, in terms of reproducing and representing what content is selected and emphasised in a national history curriculum.

Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

Edge-weighting of gene expression graphs

In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed. Keywords: Edge-weighting; weighted graphs; gene expression; bi-clustering

Empowering the disempowered through voice-inclusive practice: Children’s views on adult-centric educational provision

The United Nations Convention on the Rights of the Child provides a significant platform to include children’s views on issues that affect their lives, yet, in many contexts, particularly in educational practice, children’s perspectives continue to be irregularly sought and are rarely acted upon. By providing children’s perspectives on what they would like adults to know, this article explores a unique view of childhood and the interactions with family, community, educational experiences and well-being. The children’s insights about their worlds that they feel adults are missing potentiate the development and incorporation of voice-inclusive practice. While the sense that each child makes of their Lebenswelt – the ‘ingredients’ – is idiosyncratic and will be influenced by many factors, including peers, teachers, parents, other adults and the media, it is the nature of this personal understanding that is poorly understood, and consequently ignored by adults. By exploring the commentary of more than 1000 children across five countries – Australia, England, New Zealand, Italy and Sweden – this research reveals an overwhelming collection of what the authors describe as ‘comments that rhyme’ in terms of the identification of expressed sentiment and thematic representations of their perspectives.

Deriving word association networks from text corpora

This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.

Scaffolding understanding of tables and graphs

The literacy demands of tables and graphs are different from those of prose texts such as narrative. This paper draws from part of a qualitative case study which sought to investigate strategies that scaffold and enhance the teaching and learning of varied representations in text. As indicated in the paper, the method focused on the teaching and learning of tables and graphs with use of Freebody and Luke's (1990) four resources model from literacy education.