983 resultados para human expert cognition, real-time trajectory planning, autonomous UAS


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Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

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Combining human-computer interaction and urban informatics, this design research developed and tested novel interfaces offering users real-time feedback on their paper and energy consumption. Findings from deploying these interfaces in both domestic and office environments in Australia, the UK, and Ireland, will innovate future generations of resource monitoring technologies. The study draws conclusions with implications for government policy, the energy industry, and sustainability researchers.

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This paper provides a three-layered framework to monitor the positioning performance requirements of Real-time Relative Positioning (RRP) systems of the Cooperative Intelligent Transport Systems (C-ITS) that support Cooperative Collision Warning (CCW) applications. These applications exploit state data of surrounding vehicles obtained solely from the Global Positioning System (GPS) and Dedicated Short-Range Communications (DSRC) units without using other sensors. To this end, the paper argues the need for the GPS/DSRC-based RRP systems to have an autonomous monitoring mechanism, since the operation of CCW applications is meant to augment safety on roads. The advantages of autonomous integrity monitoring are essential and integral to any safety-of-life system. The autonomous integrity monitoring framework proposed necessitates the RRP systems to detect/predict the unavailability of their sub-systems and of the integrity monitoring module itself, and, if available, to account for effects of data link delays and breakages of DSRC links, as well as of faulty measurement sources of GPS and/or integrated augmentation positioning systems, before the information used for safety warnings/alarms becomes unavailable, unreliable, inaccurate or misleading. Hence, a monitoring framework using a tight integration and correlation approach is proposed for instantaneous reliability assessment of the RRP systems. Ultimately, using the proposed framework, the RRP systems will provide timely alerts to users when the RRP solutions cannot be trusted or used for the intended operation.

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This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

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Polymorphisms of glutathione transferases (GST) are important genetic determinants of susceptibility to environmental carcinogens (Rebbeck, 1997). The GSTs are a multigene family of dimeric enzymes involved in detoxification, and, in a few cases, the bioactivation of a variety of xenobiotics (Hayes et al., 1995). The cytosolic GST enzyme family consists of four major classes of enzymes, referred to as alpha, mu, pi and theta. Several members of this family (for example, GSTM1, GSTT1 and GSTP1) are polymorphic in human populations (Wormhoudt et al., 1999). Molecular epidemiology studies have examined the role of GST polymorphisms as susceptibility factors for environmentally and/or occupationally induced cancers (Wormhoudt et al., 1999). In particular, case-control studies showed a relationship between the GSTM1 null genotype and the development of cancer in association with smoking habits, which has been shown for cancers of the respiratory and gastrointestinal tracts as well as other cancer types (Miller et al., 1997). Only a few molecular epidemiological studies addressed the role of GSTT1 and GSTP1 polymorphisms in cancer susceptibility. Since GSTP1 is a key player in biotransformation/bioactivation of benzo(a)pyrene, GSTP1 may be even more important than GSTM1 in the prevention of tobacco-induced cancers (Harries et al., 1997; Harris et al., 1998). To date, this relationship has not been sufficiently addressed in humans. Comprehensive molecular epidemiological studies may add to the current knowledge of the role of GST polymorphisms in cancer susceptibility and extent of the knowledge gained from approaches that used phenotyping, such as GSTM1 activity as it relates to trans-stilbene oxide, or polymerase chain reaction (PCR) based genotyping of polymorphic isoenzymes (Bell et al., 1993; Pemble et al., 1994; Harries et al., 1997).

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Observing the working procedure of construction workers is an effective means of maintaining the safety performance of a construction project. It is also difficult to achieve due to a high worker-to-safety-officer ratio. There is an imminent need for the development of a tool to assist in the real-time monitoring of workers, in order to reduce the number of construction accidents. The development and application of a real time locating system (RTLS) based on the Chirp Spread Spectrum (CSS) technique is described in this paper for tracking the real-time position of workers on construction sites. Experiments and tests were carried out both on- and off-site to verify the accuracy of static and dynamic targets by the system, indicating an average error of within one metre. Experiments were also carried out to verify the ability of the system to identify workers’ unsafe behaviours. Wireless data transfer was used to simplify the deployment of the system. The system was deployed in a public residential construction project and proved to be quick and simple to use. The cost of the developed system is also reported to be reasonable (around 1800USD) in this study and is much cheaper than the cost of other RTLS. In addition, the CCS technique is shown to provide an economical solution with reasonable accuracy compared with other positioning systems, such as ultra wideband. The study verifies the potential of the CCS technique to provide an effective and economical aid in the improvement of safety management in the construction industry.

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Trichinella nematodes are the causative agent of trichinellosis, a meat-borne zoonosis acquired by consuming undercooked, infected meat. Although most human infections are sourced from the domestic environment, the majority of Trichinella parasites circulate in the natural environment in carnivorous and scavenging wildlife. Surveillance using reliable and accurate diagnostic tools to detect Trichinella parasites in wildlife hosts is necessary to evaluate the prevalence and risk of transmission from wildlife to humans. Real-time PCR assays have previously been developed for the detection of European Trichinella species in commercial pork and wild fox muscle samples. We have expanded on the use of real-time PCR in Trichinella detection by developing an improved extraction method and SYBR green assay that detects all known Trichinella species in muscle samples from a greater variety of wildlife. We simulated low-level Trichinella infections in wild pig, fox, saltwater crocodile, wild cat and a native Australian marsupial using Trichinella pseudospiralis or Trichinella papuae ethanol-fixed larvae. Trichinella-specific primers targeted a conserved region of the small subunit of the ribosomal RNA and were tested for specificity against host and other parasite genomic DNAs. The analytical sensitivity of the assay was at least 100 fg using pure genomic T. pseudospiralis DNA serially diluted in water. The diagnostic sensitivity of the assay was evaluated by spiking log of each host muscle with T. pseudospiralis or T. papuae larvae at representative infections of 1.0, 0.5 and 0.1 larvae per gram, and shown to detect larvae at the lowest infection rate. A field sample evaluation on naturally infected muscle samples of wild pigs and Tasmanian devils showed complete agreement with the EU reference artificial digestion method (k-value = 1.00). Positive amplification of mouse tissue experimentally infected with T. spiralis indicated the assay could also be used on encapsulated species in situ. This real-time PCR assay offers an alternative highly specific and sensitive diagnostic method for use in Trichinella wildlife surveillance and could be adapted to wildlife hosts of any region. (C) 2012 Elsevier B.V. All rights reserved.

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Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.

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Irritable bowel syndrome (IBS) is a common multifactorial functional intestinal disorder, the pathogenesis of which is not completely understood. Increasing scientific evidence suggests that microbes are involved in the onset and maintenance of IBS symptoms. The microbiota of the human gastrointestinal (GI) tract constitutes a massive and complex ecosystem consisting mainly of obligate anaerobic microorganisms making the use of culture-based methods demanding and prone to misinterpretation. To overcome these drawbacks, an extensive panel of species- and group-specific assays for an accurate quantification of bacteria from fecal samples with real-time PCR was developed, optimized, and validated. As a result, the target bacteria were detectable at a minimum concentration range of approximately 10 000 bacterial genomes per gram of fecal sample, which corresponds to the sensitivity to detect 0.000001% subpopulations of the total fecal microbiota. The real-time PCR panel covering both commensal and pathogenic microorganisms was assessed to compare the intestinal microbiota of patients suffering from IBS with a healthy control group devoid of GI symptoms. Both the IBS and control groups showed considerable individual variation in gut microbiota composition. Sorting of the IBS patients according to the symptom subtypes (diarrhea, constipation, and alternating predominant type) revealed that lower amounts of Lactobacillus spp. were present in the samples of diarrhea predominant IBS patients, whereas constipation predominant IBS patients carried increased amounts of Veillonella spp. In the screening of intestinal pathogens, 17% of IBS samples tested positive for Staphylococcus aureus, whereas no positive cases were discovered among healthy controls. Furthermore, the methodology was applied to monitor the effects of a multispecies probiotic supplementation on GI microbiota of IBS sufferers. In the placebo-controlled double-blind probiotic intervention trial of IBS patients, each supplemented probiotic strain was detected in fecal samples. Intestinal microbiota remained stable during the trial, except for Bifidobacterium spp., which increased in the placebo group and decreased in the probiotic group. The combination of assays developed and applied in this thesis has an overall coverage of 300-400 known bacterial species, along with the number of yet unknown phylotypes. Hence, it provides good means for studying the intestinal microbiota, irrespective of the intestinal condition and health status. In particular, it allows screening and identification of microbes putatively associated with IBS. The alterations in the gut microbiota discovered here support the hypothesis that microbes are likely to contribute to the pathophysiology of IBS. The central question is whether the microbiota changes described represent the cause for, rather than the effect of, disturbed gut physiology. Therefore, more studies are needed to determine the role and importance of individual microbial species or groups in IBS. In addition, it is essential that the microbial alterations observed in this study will be confirmed using a larger set of IBS samples of different subtypes, preferably from various geographical locations.

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To realistically simulate the motion of flexible objects such as ropes, strings, snakes, or human hair,one strategy is to discretise the object into a large number of small rigid links connected by rotary or spherical joints. The discretised system is highly redundant and the rotations at the joints (or the motion of the other links) for a desired Cartesian motion of the end of a link cannot be solved uniquely. In this paper, we propose a novel strategy to resolve the redundancy in such hyper-redundant systems.We make use of the classical tractrix curve and its attractive features. For a desired Cartesian motion of the `head'of a link, the `tail' of the link is moved according to a tractrix,and recursively all links of the discretised objects are moved along different tractrix curves. We show that the use of a tractrix curve leads to a more `natural' motion of the entire object since the motion is distributed uniformly along the entire object with the displacements tending to diminish from the `head' to the `tail'. We also show that the computation of the motion of the links can be done in real time since it involves evaluation of simple algebraic, trigonometric and hyperbolic functions. The strategy is illustrated by simulations of a snake, tying of knots with a rope and a solution of the inverse kinematics of a planar hyper-redundant manipulator.

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Magnetic Resonance Imaging (MRI) has been widely used in cancer treatment planning, which takes the advantage of high-resolution and high-contrast provided by it. The raw data collected in the MRI can also be used to obtain the temperature maps and has been explored for performing MR thermometry. This review article describes the methods that are used in performing MR thermometry, with an emphasis on reconstruction methods that are useful to obtain these temperature maps in real-time for large region of interest. This article also proposes a prior-image constrained reconstruction method for temperature reconstruction in MR thermometry, and a systematic comparison using ex-vivo tissue experiments with state of the art reconstruction method is presented.

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A sliding mode position control for high-performance real-time applications of induction motors in developed in this work. The design also incorporates a simple flux estimator in order to avoid the flux sensors. Then, the proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost DSP-processor. The stability analysis of the controller under parameter uncertainties and load disturbances in provided using Lyapunov stability theory. Finally, simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.