The relationship between lower intelligence, crime and custodial outcomes : a brief literary review of a vulnerable group

The relationship between intellectual functioning and criminal offending has received considerable focus within the literature. While there remains debate regarding the existence (and strength) of this relationship, there is a wider consensus that individuals with below average functioning (in particular cognitive impairments) are disproportionately represented within the prison population. This paper focuses on research that has implications for the effective management of lower functioning individuals within correctional environments as well as the successful rehabilitation and release of such individuals back into the community. This includes a review of the literature regarding the link between lower intelligence and offending and the identification of possible factors that either facilitate (or confound) this relationship. The main themes to emerge from this review are that individuals with lower intellectual functioning continue to be disproportionately represented in custodial settings and that there is a need to increase the provision of specialised programs to cater for their needs. Further research is also needed into a range of areas including: (1) the reason for this over-representation in custodial settings, (2) the existence and effectiveness of rehabilitation and release programs that cater for lower IQ offenders, (3) the effectiveness of custodial alternatives for this group (e.g. intensive corrections orders) and (4) what post-custodial release services are needed to reduce the risk of recidivism.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

Physical and linkage maps for Drosophila serrata, a model species for studies of clinal adaptation and sexual selection

Drosophila serrata is a member of the montium group, which contains more than 98 species and until recently was considered a subgroup within the melanogaster group. This Drosophila species is an emerging model system for evolutionary quantitative genetics and has been used in studies of species borders, clinal variation and sexual selection. Despite the importance of D. serrata as a model for evolutionary research, our poor understanding of its genome remains a significant limitation. Here, we provide a first-generation gene-based linkage map and a physical map for this species. Consistent with previous studies of other drosophilids we observed strong conservation of genes within chromosome arms homologous with D. melanogaster but major differences in within-arm synteny. These resources will be a useful complement to ongoing genome sequencing efforts and QTL mapping studies in this species

Of castles and fairytales

1,000-word travel article describing a journey on the Moselle River in Germany. "Step back in time with Germany’s historical landmarks along the country’s beautiful Mosel River, writes Kari Gislason"--publisher website

Uninav : a context-aware mobile application for university campus maps

The smart phones we carry with us are becoming ubiquitous with everyday life and the sensing capabilities of these devices allow us to provide context-aware services. In this paper, we discuss the development of UniNav, a context-aware mobile application that delivers personalised campus maps for universities. The application utilises university students’ details to provide information and services that are relevant and important to them. It helps students to navigate within the campus and become familiar with their university environment quickly. A study was undertaken to evaluate the acceptability and usefulness of the campus map, as well as the impact on a users’ navigation efficiency by utilising the personal and environmental contexts. The result indicates the integration of personal and environmental contexts on digital maps can improve its usefulness and navigation efficiency.

Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

Use of concept maps in reforming teaching Family and Consumer Sciences in Kuwait

This paper addresses the professional development of Kuwaiti teachers in the use of concept maps to teach Family and Consumer Science. A key aim of the study was to evaluate the degree to which the use of concept maps would influence the way Kuwaiti teachers approach and teach Family and Consumer Studies (FCS) subjects and the degree to which concept maps empower students to critically identify and express their knowledge of the subject being taught. A case study methodology was adopted to follow the implementation of lessons using concept maps by four teachers of middle years. An analysis of the data revealed the positive impact that student-centred teaching tools can have on the reformation of traditional teaching environments. For all teachers, the primary strengths of using concept maps were the ability to generate student interest, to motivate student participation and to enhance student understanding of content. Although a case study design may limit the generalisation and comparative value of the study, the findings of this study remain important to the planning of future professional development programs and the use of concept maps within Kuwait’s FCS curriculum area.

Testing the accuracy of luminance maps acquired by smart phone cameras

This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.

Flexibility, Technology and Academics' Practices : Tantalising Tales and Muddy Maps

The project investigated the relationships between diversification in modes ofdelivery, use of information and communication technologies, academics’ teaching practices, and the context in which those practices are employed, in two of the three large universities in Brisbane—Griffith University and the Queensland University of Technology (QUT). The project’s initial plan involved the investigation of two sites: Queensland University of Technology’s Faculty of Education (Kelvin Grove campus) and Griffith University’s Faculty of Humanities(Nathan campus). Interviews associated with the Faculty of Education led to a decision to include a third site—the School of Law within Queensland University of Technology’s Faculty of Law, which is based on the Gardens Point Campus. Here the investigation focused on the use of computer-based flexible learning practices, as distinct from the more text-based practices identified within the original two sites.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

Career-path analysis using optimal matching and self-organizing maps

This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal.

Vision-only autonomous navigation using topometric maps

This paper presents a mapping and navigation system for a mobile robot, which uses vision as its sole sensor modality. The system enables the robot to navigate autonomously, plan paths and avoid obstacles using a vision based topometric map of its environment. The map consists of a globally-consistent pose-graph with a local 3D point cloud attached to each of its nodes. These point clouds are used for direction independent loop closure and to dynamically generate 2D metric maps for locally optimal path planning. Using this locally semi-continuous metric space, the robot performs shortest path planning instead of following the nodes of the graph --- as is done with most other vision-only navigation approaches. The system exploits the local accuracy of visual odometry in creating local metric maps, and uses pose graph SLAM, visual appearance-based place recognition and point clouds registration to create the topometric map. The ability of the framework to sustain vision-only navigation is validated experimentally, and the system is provided as open-source software.

Marking out the pitch : a historiography and taxonomy of football fiction

Football, or soccer as it is more commonly referred to in Australia and the US, is arguably the world’s most popular sport. It generates a proportionate volume of related writing. Within this landscape, works of novel-length fiction are seemingly rare. This paper establishes and maps a substantial body of football fiction works, explores elements and qualities exhibited individually and collectively. In bringing together current, limited surveys of the field, it presents the first rigorous definition of football fiction and captures the first historiography of the corpus. Drawing on distant reading methods developed in conjunction with closer textual analyses, the historiography and subsequent taxonomy represent the first articulation of relationships across the body of work, identify growth areas and establish a number of movements and trends. In advancing the understanding of football fiction as a collective body, the paper lays foundations for further research and consideration of the works in generic terms.