358 resultados para Minimal

em Queensland University of Technology - ePrints Archive


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In the filed of semantic grid, QoS-based Web service scheduling for workflow optimization is an important problem.However, in semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the scheduling consider not only quality properties of Web services, but also inter service dependencies which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address scheduling optimization problems in workflow applications in the presence of domain constraints and inter service dependencies. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

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In the field of semantic grid, QoS-based Web service composition is an important problem. In semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the composition consider not only QoS properties of Web services, but also inter service dependencies and conflicts which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address the Web service composition optimization problem in the presence of domain constraints and inter service dependencies and conflicts. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

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This paper is directed towards providing an answer to the question, ”Can you control the trajectory of a Lagrangian float?” Being a float that has minimal actuation (only buoyancy control), their horizontal trajectory is dictated through drifting with ocean currents. However, with the appropriate vertical actuation and utilising spatio-temporal variations in water speed and direction, we show here that broad controllabilty results can be met such as waypoint following to keep a float inside of a bay or out of a designated region. This paper extends theory experimen- tally evaluted on horizontally actuated Autonomous Underwater Vehicles (AUVs) for trajectory control utilising ocean forecast models and presents an initial investi- gation into the controllability of these minimally actuated drifting AUVs. Simulated results for offshore coastal and within highly dynamic tidal bays illustrate two tech- niques with the promise for an affirmative answer to the posed question above.

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Kinematic models are commonly used to quantify foot and ankle kinematics, yet no marker sets or models have been proven reliable or accurate when wearing shoes. Further, the minimal detectable difference of a developed model is often not reported. We present a kinematic model that is reliable, accurate and sensitive to describe the kinematics of the foot–shoe complex and lower leg during walking gait. In order to achieve this, a new marker set was established, consisting of 25 markers applied on the shoe and skin surface, which informed a four segment kinematic model of the foot–shoe complex and lower leg. Three independent experiments were conducted to determine the reliability, accuracy and minimal detectable difference of the marker set and model. Inter-rater reliability of marker placement on the shoe was proven to be good to excellent (ICC = 0.75–0.98) indicating that markers could be applied reliably between raters. Intra-rater reliability was better for the experienced rater (ICC = 0.68–0.99) than the inexperienced rater (ICC = 0.38–0.97). The accuracy of marker placement along each axis was <6.7 mm for all markers studied. Minimal detectable difference (MDD90) thresholds were defined for each joint; tibiocalcaneal joint – MDD90 = 2.17–9.36°, tarsometatarsal joint – MDD90 = 1.03–9.29° and the metatarsophalangeal joint – MDD90 = 1.75–9.12°. These thresholds proposed are specific for the description of shod motion, and can be used in future research designed at comparing between different footwear.

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Metalloproteinases have been implicated in the pathogenesis of equine laminitis and other inflammatory conditions, through their role in the degradation and remodelling of the extracellular matrix environment. Matrix metalloproteinases (MMPs) and their inhibitors are present in normal equine lamellae, with increased secretion and activation of some metalloproteinases reported in horses with laminitis associated with systemic inflammation. It is unknown whether these enzymes are involved in insulin-induced laminitis, which occurs without overt systemic inflammation. In this study, gene expression of MMP-2, MMP-9, MT1-MMP, ADAMTS-4 and TIMP-3 was determined in the lamellar tissue of normal control horses (n = 4) and horses that developed laminitis after 48 h of induced hyperinsulinaemia (n = 4), using quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Protein concentrations of MMP-2 and MMP-9 were also examined using gelatin zymography in horses subject to prolonged hyperinsulinaemia for 6 h (n = 4), 12 h (n = 4), 24 h (n = 4) and 48 h (n = 4), and in normal control horses (n = 4). The only change in gene expression observed was an upregulation of MMP-9 (p < 0.05) in horses that developed insulin-induced laminitis (48 h). Zymographical analysis showed an increase (p < 0.05) in pro MMP-9 during the acute phase of laminitis (48 h), whereas pro MMP-2 was present in similar concentration in the tissue of all horses. Thus, MMP-2, MT1-MMP, TIMP-3 and ADAMTS-4 do not appear to play a significant role in the pathogenesis of insulin-induced laminitis. The increased expression of MMP-9 may be associated with the infiltration of inflammatory leukocytes, or may be a direct result of hyperinsulinaemia. The exact role of MMP-9 in basement membrane degradation in laminitis is uncertain as it appears to be present largely in the inactive form.

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Visual sea-floor mapping is a rapidly growing application for Autonomous Underwater Vehicles (AUVs). AUVs are well-suited to the task as they remove humans from a potentially dangerous environment, can reach depths human divers cannot, and are capable of long-term operation in adverse conditions. The output of sea-floor maps generated by AUVs has a number of applications in scientific monitoring: from classifying coral in high biological value sites to surveying sea sponges to evaluate marine environment health.

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This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

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Current IEEE 802.11 wireless networks are vulnerable to session hijacking attacks as the existing standards fail to address the lack of authentication of management frames and network card addresses, and rely on loosely coupled state machines. Even the new WLAN security standard - IEEE 802.11i does not address these issues. In our previous work, we proposed two new techniques for improving detection of session hijacking attacks that are passive, computationally inexpensive, reliable, and have minimal impact on network performance. These techniques utilise unspoofable characteristics from the MAC protocol and the physical layer to enhance confidence in the intrusion detection process. This paper extends our earlier work and explores usability, robustness and accuracy of these intrusion detection techniques by applying them to eight distinct test scenarios. A correlation engine has also been introduced to maintain the false positives and false negatives at a manageable level. We also explore the process of selecting optimum thresholds for both detection techniques. For the purposes of our experiments, Snort-Wireless open source wireless intrusion detection system was extended to implement these new techniques and the correlation engine. Absence of any false negatives and low number of false positives in all eight test scenarios successfully demonstrated the effectiveness of the correlation engine and the accuracy of the detection techniques.

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The soda process was the first chemical pulping method and was patented in 1845. Soda pulping led to kraft pulping, which involves the combined use of sodium hydroxide and sodium sulfide. Today, kraft pulping dominates the chemical pulping industry. However, about 10% of the total chemical pulp produced in the world is made using non-wood material, such as bagasse and wheat straw. The soda process is the preferred method of chemical pulping of non-wood materials, because it is considered to be economically viable on a small scale and for bagasse is compatible with sugarcane processing. With recent developments, the soda process can be designed to produce minimal effluent discharge and the fouling of evaporators by silica precipitation. The aim of this work is to produce bagasse fibres suitable for papermaking and allied applications and to produce sulfur-free lignin for use in specialty applications. A preliminary economic analysis of the soda process for producing commodity silica, lignin and pulp for papermaking is presented.

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The picturesque aesthetic in the work of Sir John Soane, architect and collector, resonates in the major work of his very personal practice – the development of his house museum, now the Soane Museum in Lincoln’s Inn Fields in London. Soane was actively involved with the debates, practices and proponents of picturesque and classical practices in architecture and landscape and his lectures reveal these influences in the making of The Soane, which was built to contain and present diverse collections of classical and contemporary art and architecture alongside scavenged curiosities. The Soane Museum has been described as a picturesque landscape, where a pictorial style, together with a carefully defined itinerary, has resulted in the ‘apotheosis of the Picturesque interior’. Soane also experimented with making mock ruinscapes within gardens, which led him to construct faux architectures alluding to archaeological practices based upon the ruin and the fragment. These ideas framed the making of interior landscapes expressed through spatial juxtapositions of room and corridor furnished with the collected object that characterise The Soane Museum. This paper is a personal journey through the Museum which describes and then reviews aspects of Soane’s work in the context of contemporary theories on ‘new’ museology. It describes the underpinning picturesque practices that Soane employed to exceed the boundaries between interior and exterior landscapes and the collection. It then applies particular picturesque principles drawn from visiting The Soane to a speculative project for a house/landscape museum for the Oratunga historic property in outback South Australia, where the often, normalising effects of conservation practices are reviewed using minimal architectural intervention through a celebration of ruinous states.

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Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating non-critical in-car systems. Likelihood-maximising (LIMA) frameworks optimise speech enhancement algorithms based on recognised state sequences rather than traditional signal-level criteria such as maximising signal-to-noise ratio. Previously presented LIMA frameworks require calibration utterances to generate optimised enhancement parameters which are used for all subsequent utterances. Sub-optimal recognition performance occurs in noise conditions which are significantly different from that present during the calibration session - a serious problem in rapidly changing noise environments. We propose a dialog-based design which allows regular optimisation iterations in order to track the changing noise conditions. Experiments using Mel-filterbank spectral subtraction are performed to determine the optimisation requirements for vehicular environments and show that minimal optimisation assists real-time operation with improved speech recognition accuracy. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session.