Post-WTO China : competition and technology transfer laws in the 'new' socialist market economy

China has been the focus of much academic and business scrutiny of late. Its economic climate is changing and its huge new market opportunities seem quite tantalizing to the would-be 'technology entrepreneur'. But China's market is a relatively immature one; it is still in the process of being opened up to real competition. The corollary of this is that, at this stage of the transitional process, there is still significant State control of market function. This article discusses Chinese competition law, the technology transfer system, how the laws are being reformed and how the technology entrepreneur fares under them. The bottom line is that while opportunities beckon, the wise entrepreneur will nevertheless continue to exercise caution.

Market access of Papua New Guinea bananas (Musa spp.) with particular respect to banana fly (Bactrocera musae (Tryon)) (Diptera: Tephritidae)

International market access for fresh commodities is regulated by international accepted phytosanitary guidelines, the objectives of which are to reduce the biosecurity risk of plant pest and disease movement. Papua New Guinea (PNG) has identified banana as a potential export crop and to help meet international market access requirements, this thesis provides information for the development of a pest risk analysis (PRA) for PNG banana fruit. The PRA is a three step process which first identifies the pests associated with a particular commodity or pathway, then assesses the risk associated with those pests, and finally identifies risk management options for those pests if required. As the first step of the PRA process, I collated a definitive list on the organisms associated with the banana plant in PNG using formal literature, structured interviews with local experts, grey literature and unpublished file material held in PNG field research stations. I identified 112 organisms (invertebrates, vertebrate, pathogens and weeds) associated with banana in PNG, but only 14 of these were reported as commonly requiring management. For these 14 I present detailed information summaries on their known biology and pest impact. A major finding of the review was that of the 14 identified key pests, some research information occurs for 13. The single exception for which information was found to be lacking was Bactrocera musae (Tryon), the banana fly. The lack of information for this widely reported ‘major pest on PNG bananas’ would hinder the development of a PNG banana fruit PRA. For this reason the remainder of the thesis focused on this organism, particularly with respect to generation of information required by the PRA process. Utilising an existing, but previously unanalysed fruit fly trapping database for PNG, I carried out a Geographic Information System analysis of the distribution and abundance of banana in four major regions of PNG. This information is required for a PRA to determine if banana fruit grown in different parts of the country are at different risks from the fly. Results showed that the fly was widespread in all cropping regions and that temperature and rainfall were not significantly correlated with banana fly abundance. Abundance of the fly was significantly correlated (albeit weakly) with host availability. The same analysis was done with four other PNG pest fruit flies and their responses to the environmental factors differed to banana fly and each other. This implies that subsequent PRA analyses for other PNG fresh commodities will need to investigate the risk of each of these flies independently. To quantify the damage to banana fruit caused by banana fly in PNG, local surveys and one national survey of banana fruit infestation were carried out. Contrary to expectations, infestation was found to be very low, particularly in the widely grown commercial cultivar, Cavendish. Infestation of Cavendish fingers was only 0.41% in a structured, national survey of over 2 700 banana fingers. Follow up laboratory studies showed that fingers of Cavendish, and another commercial variety Lady-finger, are very poor hosts for B. musae, with very low host selection rates by female flies and very poor immature survival. An analysis of a recent (within last decade) incursion of B. musae into the Gazelle Peninsula of East New Britain Province, PNG, provided the final set of B. musae data. Surveys of the fly on the peninsular showed that establishment and spread of the fly in the novel environment was very rapid and thus the fly should be regarded as being of high biosecurity concern, at least in tropical areas. Supporting the earlier impact studies, however, banana fly has not become a significant banana fruit problem on the Gazelle, despite bananas being the primary starch staple of the region. The results of the research chapters are combined in the final Discussion in the form of a B. musae focused PRA for PNG banana fruit. Putting the thesis in a broader context, the Discussion also deals with the apparent discrepancy between high local abundance of banana fly and very low infestation rates. This discussion focuses on host utilisation patterns of specialist herbivores and suggests that local pest abundance, as determined by trapping or monitoring, need not be good surrogate for crop damage, despite this linkage being implicit in a number of international phytosanitary protocols.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Socially responsible investment in market downturns : implications for the fiduciary responsibilities of investment fund trustees

This paper investigates whether Socially Responsible Investment (SRI) is more or less sensitive to market downturns than conventional investment, and examines the legal implications for fund managers and trustees. Using a market model methodology, we find that over the past 15 years, the beta risk of SRI, both in Australia and internationally, increased more than that of conventional investment during economic downturns. This implies that companies acting as fund trustees, managed investment schemes and traditional institutional fund managers risk breaching their fiduciary or statutory duties if they go long - or remain long - in SRI funds during market downturns, unless perhaps relevant legislation is reformed. If reform is viewed as desirable, possible reforms could include explicitly overriding the common law to allow all traditional funds to invest in SRI; granting immunity to directors of trustee companies from potential personal liability under sections 197 or 588G et seq of the Corporations Act; allowing companies acting as trustees, managed investment schemes and traditional institutional fund managers and trustees to invest in SRI without triggering a substantial capital gains tax liability through trust resettlement; tax concessions for SRI (eg. introducing a 150% tax deduction or investment allowance for SRI); and allowing SRI sub-funds to obtain “deductible gift recipient” status or the equivalent from relevant taxation authorities. The research is important and original insofar as the assessment of risk in SRIs during market downturns is an area which has hitherto not been subjected to rigorous empirical investigation, despite its serious legal implications.

Optimal track access rights allocation for agent negotiation in an open railway market

In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multi-agent system (MAS) in which the IP and TSP are represented by separate software agents. One task of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between timetables attained from the proposed methods and those derived by the scheduling principles adopted in practice.

Service bid comparisons by fuzzy ranking in open railway market timetabling

In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market.