Play a role in the patent puzzle

Discusses the contentious issues surrounding computer software patents and patenting in connection with the Peer-to-Patent Australia project, a joint initiative of Queensland University of Technology (QUT) and New York Law School (NYLS) that operates with the support and endorsement of IP Australia, the government body housing Australia's patent office. Explains that the project is based on the successful Peer-to-Patent pilots run recently in the USA and Japan that are designed to improve the quality of issued patents and the patent examination process by facilitating community participation in that process. Describes how members of the public are allowed to put forward prior art references that will be considered by IP Australia's patent examiners when determining whether participating applications are novel and inventive, and therefore deserving of a patent. Concludes that, while Peer-to-Patent Australia is not a complete solution to the problems besetting patent law, the model has considerable advantages over the traditional model of patent examination

Measuring the success of ABC training in South Africa: A case study in the production of Western Liberal broadcast news values

In 1993 the Australian Broadcasting Corporation was contracted by the Australian Government to assist in the reshaping of the South African Broadcasting Corporation from a state-run broadcaster to a respected and trusted national broadcaster for all people in the newly democratic South Africa. Broadcast journalism training was identified by ABC consultant Bob Wurth as possibly the greatest need for SABC Radio. This thesis examines the ABC's role in South Africa and the effectiveness of its radio journalism training project considering the organisational, structural, cultural and political constraints of the SABC. This thesis will show through interviews and participant observation the difficulties in achieving the production of Western Liberal journalism values at the SABC within the time constraints set by the project funded by the Australian Government and the particular South African morays.

Analysis of alternative water sources for use in the manufacture of concrete

In Australia and many other countries worldwide, water used in the manufacture of concrete must be potable. At present, it is currently thought that concrete properties are highly influenced by the water type used and its proportion in the concrete mix, but actually there is little knowledge of the effects of different, alternative water sources used in concrete mix design. Therefore, the identification of the level and nature of contamination in available water sources and their subsequent influence on concrete properties is becoming increasingly important. Of most interest, is the recycled washout water currently used by batch plants as mixing water for concrete. Recycled washout water is the water used onsite for a variety of purposes, including washing of truck agitator bowls, wetting down of aggregate and run off. This report presents current information on the quality of concrete mixing water in terms of mandatory limits and guidelines on impurities as well as investigating the impact of recycled washout water on concrete performance. It also explores new sources of recycled water in terms of their quality and suitability for use in concrete production. The complete recycling of washout water has been considered for use in concrete mixing plants because of the great benefit in terms of reducing the cost of waste disposal cost and environmental conservation. The objective of this study was to investigate the effects of using washout water on the properties of fresh and hardened concrete. This was carried out by utilizing a 10 week sampling program from three representative sites across South East Queensland. The sample sites chosen represented a cross-section of plant recycling methods, from most effective to least effective. The washout water samples collected from each site were then analysed in accordance with Standards Association of Australia AS/NZS 5667.1 :1998. These tests revealed that, compared with tap water, the washout water was higher in alkalinity, pH, and total dissolved solids content. However, washout water with a total dissolved solids content of less than 6% could be used in the production of concrete with acceptable strength and durability. These results were then interpreted using chemometric techniques of Principal Component Analysis, SIMCA and the Multi-Criteria Decision Making methods PROMETHEE and GAIA were used to rank the samples from cleanest to unclean. It was found that even the simplest purifying processes provided water suitable for the manufacture of concrete form wash out water. These results were compared to a series of alternative water sources. The water sources included treated effluent, sea water and dam water and were subject to the same testing parameters as the reference set. Analysis of these results also found that despite having higher levels of both organic and inorganic properties, the waters complied with the parameter thresholds given in the American Standard Test Method (ASTM) C913-08. All of the alternative sources were found to be suitable sources of water for the manufacture of plain concrete.

Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

Researching with the Aboriginal Community, MPH2057- Aboriginal Health Course (Monash University), delivered by the Victorian Aboriginal Community Controlled Health Organisation (VACCHO) & The Burnet Institute at The Burnet Institute, Melbourne, Victoria, 29 September 2010

A copy of the slide presentation titled 'Researching with the Aboriginal Community'. It was presented by Bronwyn Fredericks for the Master of Public Health Program (MPH2057- Aboriginal Health Course) at Monash University. The Monash University Aboriginal Health Course (MPH2057) is delivered in partnership by the Victorian Aboriginal Community Controlled Health Organisation (VACCHO) & The Burnet Institute. The 2010 Aboriginal Health Course was run on Level 3 of The Burnet Institute, 89 Commercial Road, Prahan, Melbourne, Victoria, 29 September 2010.

A distributed denial of service testbed

The Denial of Service Testing Framework (dosTF) being developed as part of the joint India-Australia research project for ‘Protecting Critical Infrastructure from Denial of Service Attacks’ allows for the construction, monitoring and management of emulated Distributed Denial of Service attacks using modest hardware resources. The purpose of the testbed is to study the effectiveness of different DDoS mitigation strategies and to allow for the testing of defense appliances. Experiments are saved and edited in XML as abstract descriptions of an attack/defense strategy that is only mapped to real resources at run-time. It also provides a web-application portal interface that can start, stop and monitor an attack remotely. Rather than monitoring a service under attack indirectly, by observing traffic and general system parameters, monitoring of the target application is performed directly in real time via a customised SNMP agent.

Coast control for mass rapid transit railways with searching methods

With daily commercial and social activity in cities, regulation of train service in mass rapid transit railways is necessary to maintain service and passenger flow. Dwell-time adjustment at stations is one commonly used approach to regulation of train service, but its control space is very limited. Coasting control is a viable means of meeting the specific run-time in an inter-station run. The current practice is to start coasting at a fixed distance from the departed station. Hence, it is only optimal with respect to a nominal operational condition of the train schedule, but not the current service demand. The advantage of coasting can only be fully secured when coasting points are determined in real-time. However, identifying the necessary starting point(s) for coasting under the constraints of current service conditions is no simple task as train movement is governed by a large number of factors. The feasibility and performance of classical and heuristic searching measures in locating coasting point(s) is studied with the aid of a single train simulator, according to specified inter-station run times.

Interaction of natural survival instincts and internalized social norms exploring the Titanic and Lusitania disasters

To understand human behavior, it is important to know under what conditions people deviate from selfish rationality. This study explores the interaction of natural survival instincts and internalized social norms using data on the sinking of the Titanic and the Lusitania. We show that time pressure appears to be crucial when explaining behavior under extreme conditions of life and death. Even though the two vessels and the composition of their passengers were quite similar, the behavior of the individuals on board was dramatically different. On the Lusitania, selfish behavior dominated (which corresponds to the classical homo oeconomicus); on the Titanic, social norms and social status (class) dominated, which contradicts standard economics. This difference could be attributed to the fact that the Lusitania sank in 18 minutes, creating a situation in which the short-run flight impulse dominates behavior. On the slowly sinking Titanic (2 hours, 40 minutes), there was time for socially determined behavioral patterns to re-emerge. To our knowledge, this is the first time that these shipping disasters have been analyzed in a comparative manner with advanced statistical (econometric) techniques using individual data of the passengers and crew. Knowing human behavior under extreme conditions allows us to gain insights about how varied human behavior can be depending on differing external conditions.

Sodium removal from Maramarua CSG waters using Ngakuru zeolites

Coal seam gas (CSG) waters are a by-product of natural gas extraction from un derground coal seams. The main issue with these waters is their elevated sodium content, which in conjunction with their low calcium and magnesium concentrations can generate soil infiltration problems in the long run , as well as short term toxicity effects in plants due to the sodium ion itself. Zeolites are minerals having a porous structure, crystalline characteristics, and an alumino-silicate configuration resulting in an overall negative charge which is balanced by loosely held cations. In New Zealand, Ngakuru zeolites have been mined for commercial use in wastewater treatment applications, cosmetics, and pet litter. This research focuses on assessing the capacity of Ngakuru zeolites to reduce sodium concentrations of CSG waters from Maramarua. Batch and column test (flow through) experiments revealed that Ngakuru zeolites are capable of sorbing sodium cations from concentrated solutions of sodium. In b atch tests, the sodium adsorption capacity ranged from 5.0 to 34.3meq/100g depending on the solution concentration and on the number of times the zeolite had been regenerated. Regeneration with CaCl2 was foun d to be effective. The calculated sodium adsorption capacity of Ngakuru zeolites under flow-through conditions ranged from 11 to 42meq/100g depending on the strength of the solution being treated and on w hether the zeolites had been previously regenerated. The slow kinetics and low cost of the zeolities, coupled with potentially remote sites for gas extraction, could make semi-batch operational processes without regeneration more favourable than in more industrial ion exchange situations.

Dynamic coast control of train movement with genetic algorithm

The railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. Train service usually varies with the population activities throughout a day and train coordination and service regulation are then expected to meet the daily passengers' demand. Dwell time control at stations and fixed coasting point in an inter-station run are the current practices to regulate train service in most metro railway systems. However, a flexible and efficient train control and operation is not always possible. To minimize energy consumption of train operation and make certain compromises on the train schedule, coast control is an economical approach to balance run-time and energy consumption in railway operation if time is not an important issue, particularly at off-peak hours. The capability to identify the starting point for coasting according to the current traffic conditions provides the necessary flexibility for train operation. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigates the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. Further, a hierarchical genetic algorithm (HGA) is introduced here to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.

Regulation of train service by coasting control in metro railway system

To maximise the capacity of the rail lineand provide a reliable service for pas-sengers throughout the day, regulation of train service to maintain steady service headway is es-sential. In most current metro systems, train usually starts coasting at a fixed distance from the departed station to achieve service regulation. However, this approach is only effective with re-spect to a nominal operational condition of train schedule but not necessarily the current service demand. Moreover, it is not simply to identify the necessary starting point for coasting under the run time constraints of current service conditions since train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an ap-plication of classical measures to search for the appropriate coasting point to meet a specified inter-station run time and they can be integrated in the on-board Automatic Train Operation (ATO) system and have the potential for on-line implementation in making a set of coasting command decisions.

Coasting control of train operation by genetic algorithm

Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

A review of simulation models for railway systems

With the advances in computer hardware and software development techniques in the past 25 years, digital computer simulation of train movement and traction systems has been widely adopted as a standard computer-aided engineering tool [1] during the design and development stages of existing and new railway systems. Simulators of different approaches and scales are used extensively to investigate various kinds of system studies. Simulation is now proven to be the cheapest means to carry out performance predication and system behaviour characterisation. When computers were first used to study railway systems, they were mainly employed to perform repetitive but time-consuming computational tasks, such as matrix manipulations for power network solution and exhaustive searches for optimal braking trajectories. With only simple high-level programming languages available at the time, full advantage of the computing hardware could not be taken. Hence, structured simulations of the whole railway system were not very common. Most applications focused on isolated parts of the railway system. It is more appropriate to regard those applications as primarily mechanised calculations rather than simulations. However, a railway system consists of a number of subsystems, such as train movement, power supply and traction drives, which inevitably contains many complexities and diversities. These subsystems interact frequently with each other while the trains are moving; and they have their special features in different railway systems. To further complicate the simulation requirements, constraints like track geometry, speed restrictions and friction have to be considered, not to mention possible non-linearities and uncertainties in the system. In order to provide a comprehensive and accurate account of system behaviour through simulation, a large amount of data has to be organised systematically to ensure easy access and efficient representation; the interactions and relationships among the subsystems should be defined explicitly. These requirements call for sophisticated and effective simulation models for each component of the system. The software development techniques available nowadays allow the evolution of such simulation models. Not only can the applicability of the simulators be largely enhanced by advanced software design, maintainability and modularity for easy understanding and further development, and portability for various hardware platforms are also encouraged. The objective of this paper is to review the development of a number of approaches to simulation models. Attention is, in particular, given to models for train movement, power supply systems and traction drives. These models have been successfully used to enable various ‘what-if’ issues to be resolved effectively in a wide range of applications, such as speed profiles, energy consumption, run times etc.

An event-based traffic flow model for traffic control at railway junctions

This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.