952 resultados para evaluation algorithm
Resumo:
Executive Summary: Completion of the Veloway 1 (V1) will provide a dedicated and safe route for cyclists between the Brisbane CBD and the Gateway Motorway off-ramp at Eight Mile Plains alongside the South East Motorway. The V1 is being delivered in stages and when completed will provide a dedicated 3m wide cycleway 17km in length. Two stages (D and E) remain to be constructed to complete the V1. Major trip attractors along the V1 include the Mater, Princes Alexandra and Greenslopes Hospitals, two campuses of Griffith University, Garden City shopping centre and the Australian Tax Office. This report assesses the available evidence on the impacts on cycling behaviour of the recently completed V1 Stage C. The data sources informing this review include three intercept surveys, motion activated traffic cameras and travel time surveys on the V1 and adjoining South East Freeway Bikeway (SEFB), Strava app data, and cyclist crash data along Logan Road. The key findings from the evidence are that the completed V1 Stage C has: a Attracted cyclists from Holland Park, Holland Park West, Mt Gravatt and southern parts of Tarragindi onto the V1 Stage C. b Reduced the crash exposure of pedestrians to cyclists by attracting higher speed cyclists off the adjoining SEFB onto the cycling dedicated V1 Stage C. c Reduced the potential crash exposure of cyclists to motor vehicles by attracting cyclists off Logan Road on to the V1. d Provided travel time benefits to cyclists and reduced road crossings (eight down to two). e Predominantly attracted adults commuting alone to and from work and university. The evidence shows that the two traffic crossings across Birdwood Road (required as a temporary measure until the V1 is completed) negate much of the travel time gains of the V1 Stage C compared to the adjoining SEFB for southbound cyclists. Many cyclists accessing the V1 Stage C from the south are cycling in high-volume vehicular traffic lanes to reduce their travel time along Birdwood Road, but in the process are increasing their exposure to crashes with motor vehicles. Based on these findings this report recommends that TMR: a. Continue with plans to complete the V1 Veloway b. Undertake an engineering feasibility assessment to determine the viability of constructing a section of the V1 Stage E from the intersection Weller and Birdwood Roads over Marshall Road and along Bapaume Road on the western side of the Motorway to the intersection of Bapaume and Sterculia Roads. c. In the interim, improve signage and Birdwood Road crossing points for cyclists accessing and egressing the southern end of the V1 Stage C. d. Work with Brisbane City Council to identify the safest and most practical bicycle facilities to facilitate cycle travel between Logan Road and the V1 south of Birdwood Road. e. Improve the awareness of the V1 Stage C through signage for cyclists approaching from the north with the aim of providing a better understanding of the route of the V1 to the south. f. Refine the use of motion activated traffic cameras to improve the capture rate of useable images and obtain an ongoing collection over time of V1 usage data. g. Undertake discussions with Strava, Inc. to refine the presentation of Strava data to improve visual understanding of maps showing before and after cycle route volumes along and on roads leading to the V1.
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This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.
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Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice. We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning. The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language.
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In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.
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In this chapter we introduce and explore the notion of “intentionally enriched awareness”. Intentional enrichment refers to the process of actively engaging users in the awareness process by enabling them to express intentions. We initially look at the phenomenon if sharing intentional information in related collaborative systems. We then explore the concept of intentional enrichment through designing and evaluating the AnyBiff system which allows users to freely create, share and use a variety of biff applications. Biffs are simple representation of pre-defined activities. Users can select biffs to indicate that they are engaged in an activity. We summarise the results of a trial which allowed us to gain insights into the potential of the AnyBiff prototype and the underlying biff concept to implement intentionally enriched awareness. Our findings show that intentional disclosure mechanisms in the form of biffs were successfully used in a variety of contexts. Users actively engaged in the design of a large variety of biffs and explored many different uses of the concept. The study revealed a whole host of issues with regard to intentionally enriched awareness which give valuable insight into the conception and design of future applications in this area.
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The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.
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The Air Pollution Model and Chemical Transport Model (TAPM-CTM) framework has been tested and applied originally in Sydney to quantify particle and gaseous concentration (Cope et al, 2014). However, the model performance had not been tested in the south-eastern Queensland region (SEQR), Australia.
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Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.
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Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. However, such systems could overwhelm drivers, generate different types of driver errors and have negative effects on safety at level crossing. The literature shows an increasing interest for new ITS for increasing driver situational awareness at level crossings, as well as evaluations of such new systems on compliance. To our knowledge, the potential negative effects of such technologies have not been comprehensively evaluated yet. This study aimed at assessing the effect of different ITS interventions, designed to enhance driver behaviour at railway crossings, on driver’s cognitive loads. Fifty eight participants took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver cognitive load was objectively and subjectively assessed for each ITS intervention. Objective data were collected from a heart rate monitor and an eye tracker, while subjective data was collected with the NASA-TLX questionnaire. Overall, results indicated that the three trialled technologies did not result in significant changes in cognitive load while approaching crossings.
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This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.
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The project investigated the molecular response of Tra catfish (Pangasianodon hypophthalmus) to elevated salinity conditions. We employed Next generation sequencing platform to evaluate differential gene expression profiles of key genes under two salinity conditions. Results of the current project can form the basis for further studies to confirm the functional roles of specific genes that influence salinity tolerance in the target species and more broadly in other freshwater teleost fishes. Ultimately, the approach can contribute to developing superior culture stocks of the target species.
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Partial evaluation of infrastructure investments have resulted in expensive mistakes, unsatisfactory outcomes and increased uncertainties for too many stakeholders, communities and economies in both developing and developed nations. "Complex Stakeholder Perception Mapping" (CSPM), is a novel approach that can address existing limitations by inclusively framing, capturing and mapping the spectrum of insights and perceptions using extended Geographic Information Systems. Maps generated in CSPM offer presentations of flexibly combined, complex perceptions of stakeholders on multiple aspects of development. CSPM extends the applications of GIS software in non-spatial mapping and of Multi-Criteria Analysis with a multidimensional evaluation platform and augments decision science capabilities in addressing complexities. Application of CSPM can improve local and regional economic gains from infrastructure projects and aid any multi-objective and multi-stakeholder decision situations.
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Embedded many-core architectures contain dozens to hundreds of CPU cores that are connected via a highly scalable NoC interconnect. Our Multiprocessor-System-on-Chip CoreVAMPSoC combines the advantages of tightly coupled bus-based communication with the scalability of NoC approaches by adding a CPU cluster as an additional level of hierarchy. In this work, we analyze different cluster interconnect implementations with 8 to 32 CPUs and compare them in terms of resource requirements and performance to hierarchical NoCs approaches. Using 28nm FD-SOI technology the area requirement for 32 CPUs and AXI crossbar is 5.59mm2 including 23.61% for the interconnect at a clock frequency of 830 MHz. In comparison, a hierarchical MPSoC with 4 CPU cluster and 8 CPUs in each cluster requires only 4.83mm2 including 11.61% for the interconnect. To evaluate the performance, we use a compiler for streaming applications to map programs to the different MPSoC configurations. We use this approach for a design-space exploration to find the most efficient architecture and partitioning for an application.
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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.
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In this paper, a novel 2×2 multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) testbed based on an Analog Devices AD9361 highly integrated radio frequency (RF) agile transceiver was specifically implemented for the purpose of estimating and analyzing MIMO-OFDM channel capacity in vehicle-to-infrastructure (V2I) environments using the 920 MHz industrial, scientific, and medical (ISM) band. We implemented two-dimensional discrete cosine transform-based filtering to reduce the channel estimation errors and show its effectiveness on our measurement results. We have also analyzed the effects of channel estimation error on the MIMO channel capacity by simulation. Three different scenarios of subcarrier spacing were investigated which correspond to IEEE 802.11p, Long-Term Evolution (LTE), and Digital Video Broadcasting Terrestrial (DVB-T)(2k) standards. An extensive MIMO-OFDM V2I channel measurement campaign was performed in a suburban environment. Analysis of the measured MIMO channel capacity results as a function of the transmitter-to-receiver (TX-RX) separation distance up to 250 m shows that the variance of the MIMO channel capacity is larger for the near-range line-of-sight (LOS) scenarios than for the long-range non-LOS cases, using a fixed receiver signal-to-noise ratio (SNR) criterion. We observed that the largest capacity values were achieved at LOS propagation despite the common assumption of a degenerated MIMO channel in LOS. We consider that this is due to the large angular spacing between MIMO subchannels which occurs when the receiver vehicle rooftop antennas pass by the fixed transmitter antennas at close range, causing MIMO subchannels to be orthogonal. In addition, analysis on the effects of different subcarrier spacings on MIMO-OFDM channel capacity showed negligible differences in mean channel capacity for the subcarrier spacing range investigated. Measured channels described in this paper are available on request.