Scaffolding children’s robot building and programming activities

Since 2001 the School of Information Technology and Electrical Engineering (ITEE) at the University of Queensland has been involved in RoboCupJunior activities aimed at providing children with the Robot building and programming knowledge they need to succeed in RoboCupJunior competitions. These activities include robotics workshops, the organization of the State-wide RoboCupJunior competition, and consultation on all matters robotic with schools and government organizations. The activities initiated by ITEE have succeeded in providing children with the scaffolding necessary to become competent, independent robot builders and programmers. Results from state, national and international competitions suggest that many of the children who participate in the activities supported by ITEE are subsequently able to purpose- build robots to effectively compete in RoboCupJunior competitions. As a result of the scaffolding received within workshops children are able to think deeply and creatively about their designs, and to critique their designs in order to make the best possible creation in an effort to win.

Investigation into travel of transit oriented development : school students’ travel survey of Kelvin Grove Urban Village

Travel surveys were conducted for collecting data related to school students’ travel at Kelvin Grove Urban Village (KGUV). Currently, KGUV has school students studying at grade 10 to 12. As a part of data collection process, travel surveys were undertaken for school students studying. This document contains the questionnaire form used to collect the demographic and travel data related to school students at KGUV. The surveys forms were hand delivered to the school and the responses were collected back via reply paid envelop provided with the questionnaire form.

Coordinated road-junction traffic control by dynamic programming

This paper presents a novel approach to road-traffic control for interconnected junctions. With a local fuzzy-logic controller (FLC) installed at each junction, a dynamic-programming (DP) technique is proposed to derive the green time for each phase in a traffic-light cycle. Coordination parameters from the adjacent junctions are also taken into consideration so that organized control is extended beyond a single junction. Instead of pursuing the absolute optimization of traffic delay, this study examines a practical approach to enable the simple implementation of coordination among junctions, while attempting to reduce delays, if possible. The simulation results show that the delay per vehicle can be substantially reduced, particularly when the traffic demand reaches the junction capacity. The implementation of this controller does not require complicated or demanding hardware, and such simplicity makes it a useful tool for offline studies or realtime control purposes.

Group segmentation during object tracking using optical flow discontinuities

Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

User characteristics of transit oriented developments : the case of Kelvin Grove Urban Village

Transit oriented developments are high density mixed use developments located within short and easily walkable distance of a major transit centre. These developments are often hypothesised as a means of enticing a mode shift from the private car to sustainable transport modes such as, walking, cycling and public transport. However, it is important to gather evidence to test this hypothesis by determining the travel characteristics of transit oriented developments users. For this purpose, travel surveys were conducted for an urban transit oriented development currently under development. This chapter presents the findings from the preliminary data analysis of the travel surveys. Kelvin Grove Urban Village, a mixed use development located in Brisbane, Australia, has been selected as the case for the transit oriented developments study. Travel data for all groups of transit oriented development users ranging from students to shoppers, and residents to employees were collected. Different survey instruments were used for different transit oriented development users to optimise their response rates, and the performance of these survey instruments are stated herein. The travel characteristics of transit oriented development users are reported in this chapter by explaining mode share, trip length distribution, and time of day of trip. The results of the travel survey reveal that Kelvin Grove Urban Village users use more sustainable modes of transport as compared to other Brisbane residents.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Internal market orientation and market-oriented behaviours

Purpose: The purpose of this empirical paper is to investigate internal marketing from a behavioural perspective. The impact of internal marketing behaviours, operationalised as an internal market orientation (IMO), on employees’ marketing and other in-role behaviours (IRB) were examined. ---------- Design/methodology/approach: Survey data measuring IMO, market orientation and a range of constructs relevant to the nomological network in which they are embedded were collected from the UK retail managers. These were tested to establish their psychometric properties and the conceptual model was analysed using structural equations modelling, employing a partial least squares methodology. ---------- Findings: IMO has positive consequences for employees’ market-oriented and other IRB. These, in turn, influence marketing success. Research limitations/implications – The paper provides empirical support for the long-held assumption that internal and external marketing are related and that organisations should balance their external focus with some attention to employees. Future research could measure the attitudes and behaviours of managers, employees and customers directly and explore the relationships between them. ---------- Practical implications: Firm must ensure that they do not put the needs of their employees second to those of managers and shareholders; managers must develop their listening skills and organisations must become more responsive to the needs of their employees. ---------- Originality/value: The paper contributes to the scarce body of empirical support for the role of internal marketing in services organisations. For researchers, this paper legitimises the study of internal marketing as a route to external market success; for managers, the study provides quantifiable evidence that focusing on employees’ wants and needs impacts their behaviours towards the market.

The Spartan-3E Tutorial 1 : Introduction to FPGA Programming, Version 1.0

This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through the following: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; and downloading the program to the Spartan-3E board using the Project Navigator software.

Engaging operations management students by designing the unit with industry focus

Operations management is an area concerned with the production of goods and services ensuring that business operations are efficient in utilizing resource and effective to meet customer requirements. It deals with the design and management of products, processes, services and supply chains and considers the acquisition, development, and effective and efficient utilization of resources. Unlike other engineering subjects, content of these units could be very wide and vast. It is therefore necessary to cover the content that is most related to the contemporary industries. It is also necessary to understand what engineering management skills are critical for engineers working in the contemporary organisations. Most of the operations management books contain traditional Operations Management techniques. For example ‘inventory management’ is an important topic in operations management. All OM books deal with effective method of inventory management. However, new trend in OM is Just in time (JIT) delivery or minimization of inventory. It is therefore important to decide whether to emphasise on keeping inventory (as suggested by most books) or minimization of inventory. Similarly, for OM decisions like forecasting, optimization and linear programming most organisations now a day’s use software. Now it is important for us to determine whether some of these software need to be introduced in tutorial/ lab classes. If so, what software? It is established in the Teaching and Learning literature that there must be a strong alignment between unit objectives, assessment and learning activities to engage students in learning. Literature also established that engaging students is vital for learning. However, engineering units (more specifically Operations management) is quite different from other majors. Only alignment between objectives, assessment and learning activities cannot guarantee student engagement. Unit content must be practical oriented and skills to be developed should be those demanded by the industry. Present active learning research, using a multi-method research approach, redesigned the operations management content based on latest developments in Engineering Management area and the necessity of Australian industries. The redesigned unit has significantly helped better student engagement and better learning. It was found that students are engaged in the learning if they find the contents are helpful in developing skills that are necessary in their practical life.

QoS-oriented resource allocation and scheduling of multiple composite Web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

A Taxonomy of image matching techniques for stereo vision

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.