The importance of ecological scale for wildlife conservation in naturally fragmented environments: A case study of the Brush-Tailed Rock-Wallaby (Petrogale Penicillata)

Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.

Medienvermittelte transnationale Öffentlichkeiten im Zeitalter praktischer Hybridisierung (English title: Mediated transnational publics in environments of practical hybridisation)

This article is concerned with the repercussions of societal change on transnational media. It offers a new understanding of multilingual programming strategies by examining “Radio MultiKulti” (RM), a public service radio station discontinued from 1/1/2009 by Rundfunk Berlin-Brandenburg. In its fourteen years of existence, “RM” had to implement a well-intended and politically-motivated logic of ‘multiethnic, intercultural service station’. However, as we demonstrate, such a direction, despite some achievements, has resulted in the constraints to RM’s journalistic activities and language policy, drawing criticism for the station’s economic viability. This paper proposes that multilingual media services are to be framed by the concept of practical hybridity that allows a necessary responsiveness towards an ever-changing media environment, at the moment within digital culture. Our approach draws on Mikhail Bakhtin’s and Yuri Lotman’s theoretical approaches to hybridity, as well as in-depth interviews conducted with “RM” staff from 2005 onwards, further interviews with key agents outside RM and a continuous monitoring of the public debate which culminated at the end of 2008 in the controversial decision to close the radio station. Against this background, the concluding remarks are meant to contribute to the scholarly debate on hybridization as well as to inform multilingual media policy in the 21st century.

Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.

Wireless channel modelling for indoor populated environments : statistical characterization of narrowband channels at 2.45 Ghz and 5.2 Ghz

The recent development of indoor wireless local area network (WLAN) standards at 2.45 GHz and 5 GHz has led to increased interest in propagation studies at these frequency bands. Within the indoor environment, human body effects can strongly reduce the quality of wireless communication systems. Human body effects can cause temporal variations and shadowing due to pedestrian movement and antenna- body interaction with portable terminals. This book presents a statistical characterisation, based on measurements, of human body effects on indoor narrowband channels at 2.45 GHz and at 5.2 GHz. A novel cumulative distribution function (CDF) that models the 5 GHz narrowband channel in populated indoor environments is proposed. This novel CDF describes the received envelope in terms of pedestrian traffic. In addition, a novel channel model for the populated indoor environment is proposed for the Multiple-Input Multiple-Output (MIMO) narrowband channel in presence of pedestrians at 2.45 GHz. Results suggest that practical MIMO systems must be sufficiently adaptive if they are to benefit from the capacity enhancement caused by pedestrian movement.

Towards an intelligent learning system for the natural born cyborg

We propose to design a Custom Learning System that responds to the unique needs and potentials of individual students, regardless of their location, abilities, attitudes, and circumstances. This project is intentionally provocative and future-looking but it is not unrealistic or unfeasible. We propose that by combining complex learning databases with a learner’s personal data, we could provide all students with a personal, customizable, and flexible education. This paper presents the initial research undertaken for this project of which the main challenges were to broadly map the complex web of data available, to identify what logic models are required to make the data meaningful for learning, and to translate this knowledge into simple and easy-to-use interfaces. The ultimate outcome of this research will be a series of candidate user interfaces and a broad system logic model for a new smart system for personalized learning. This project is student-centered, not techno-centric, aiming to deliver innovative solutions for learners and schools. It is deliberately future-looking, allowing us to ask questions that take us beyond the limitations of today to motivate new demands on technology.

Location-based games : transforming everyday environments into dynamic learning spaces

Location based games (LBGs) provide an opportunity to look at how new technologies can support a reciprocal relationship between formal classroom learning and learning that can potentially occur in other everyday environments. Fundamentally many games are intensely engaging due to the resulting social interactions and technical challenges they provide to individual and group players. By introducing the use of mobile devices we can transport these characteristics of games into everyday spaces. LBGs are understood as a broad genre incorporating ideas and tools that provide many unique opportunities for us to to reveal, create and even subvert various social, cultural, technical, and scientific interpretations of place, in particular places where learning is sometimes problematic.--------- A team of Queensland game developers have learnt a great deal through designing a range of LBGs such as SCOOT for various user groups and places. While these LBGs were primarily designed as social events, we found that the players recognised and valued the game as an opportunity to learn about their environment, it's history, cultural significance, inhabitants, services etc. Since identifying the strong pedagogical outcomes of LBGs, the team has created a set of authoring tools for people to design and host their own LBGs. A particular version of this is known as MiLK the mobile learning kit for schools.---------- This presentation will include examples of how LBGs have been used to improve the teaching and learning outcomes in various contexts. Participants will be introduced to MiLK and invited to trial it in their own classrooms with students.

Collaborative business process modeling using 3D virtual environments

Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists involved in the process modeling. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. Some systems have been developed to support collaborative process modeling, all of which use traditional 2D interfaces. We present an environment for collaborative process modeling, using 3D virtual environment technology. We make use of avatar instantiations of user ego centres, to allow for the spatial embodiment of the user with reference to the process model. We describe an innovative prototype collaborative process modeling approach, implemented as a modeling environment in Second Life. This approach leverages the use of virtual environments to provide user context for editing and collaborative exercises. We present a positive preliminary report on a case study, in which a test group modelled a business process using the system in Second Life.

Autonomous excavation using a rope shovel

This paper describes automation of the digging cycle of a mining rope shovel which considers autonomous dipper (bucket) filling and determining methods to detect when to disengage the dipper from the bank. Novel techniques to overcome dipper stall and the online estimation of dipper "fullness" are described with in-field experimental results of laser DTM generation, machine automation and digging using a 1/7th scale model rope shovel presented. © 2006 Wiley Periodicals, Inc.

Robust outdoor visual localization using a three-dimensional-edge map

Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3D)-edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long-term robust operation. Previous 3D-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions.

Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

Hippocampal models for simultaneous localisation and mapping on an autonomous robot

To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in one dimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.