258 resultados para Torso Segment Masses


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Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

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Traditional recommendation methods provide recommendations equally to all users. In this paper, a segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs in order to offer a specific recommendation strategy to each segment. Experiment is conducted using a live online dating network data.

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Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

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Introduction. Endoscopic anterior scoliosis correction has been employed recently as a less invasive and level-sparing approach compared with open surgical techniques. We have previously demonstrated that during the two-year post-operative period, there was a mean loss of rib hump correction by 1.4 degrees. The purpose of this study was to determine whether intra- or inter-vertebral rotational deformity during the post-operative period could account for the loss of rib hump correction. Materials and Methods. Ten consecutive patients diagnosed with adolescent idiopathic scoliosis were treated with an endoscopic anterior scoliosis correction. Low-dose computed tomography scans of the instrumented segment were obtained post-operatively at 6 and 24 months following institutional ethical approval and patient consent. Three-dimensional multi-planar reconstruction software (Osirix Imaging Software, Pixmeo, Switzerland) was used to create axial slices of each vertebral level, corrected in both coronal and sagittal planes. Vertebral rotation was measured using Ho’s method for every available superior and inferior endplate at 6 and 24 months. Positive changes in rotation indicate a reduction and improvement in vertebral rotation. Intra-observer variability analysis was performed on a subgroup of images. Results. Mean change in rotation for vertebral endplates between 6 and 24 months post-operatively was -0.26˚ (range -3.5 to 4.9˚) within the fused segment and +1.26˚ (range -7.2 to 15.1˚) for the un-instrumented vertebrae above and below the fusion. Mean change in clinically measured rib hump for the 10 patients was -1.6˚ (range -3 to 0˚). The small change in rotation within the fused segment accounts for only 16.5% of the change in rib hump measured clinically whereas the change in rotation between the un-instrumented vertebrae above and below the construct accounts for 78.8%. There was no clear association between rib hump recurrence and intra- or inter-vertebral rotation in individual patients. Intra-rater variability was ± 3˚. Conclusions. Intra- and inter-vertebral rotation continues post-operatively both within the instrumented and un-instrumented segments of the immature spine. Rotation between the un-instrumented vertebrae above and below the fusion was +1.26˚, suggesting that the un-instrumented vertebrae improved and de-rotated slightly after surgery. This may play a role in rib hump recurrence, however this remains clinically insignificant.

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Background and purpose: The purpose of the work presented in this paper was to determine whether patient positioning and delivery errors could be detected using electronic portal images of intensity modulated radiotherapy (IMRT). Patients and methods: We carried out a series of controlled experiments delivering an IMRT beam to a humanoid phantom using both the dynamic and multiple static field method of delivery. The beams were imaged, the images calibrated to remove the IMRT fluence variation and then compared with calibrated images of the reference beams without any delivery or position errors. The first set of experiments involved translating the position of the phantom both laterally and in a superior/inferior direction a distance of 1, 2, 5 and 10 mm. The phantom was also rotated 1 and 28. For the second set of measurements the phantom position was kept fixed and delivery errors were introduced to the beam. The delivery errors took the form of leaf position and segment intensity errors. Results: The method was able to detect shifts in the phantom position of 1 mm, leaf position errors of 2 mm, and dosimetry errors of 10% on a single segment of a 15 segment IMRT step and shoot delivery (significantly less than 1% of the total dose). Conclusions: The results of this work have shown that the method of imaging the IMRT beam and calibrating the images to remove the intensity modulations could be a useful tool in verifying both the patient position and the delivery of the beam.

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We have taken a new method of calibrating portal images of IMRT beams and used this to measure patient set-up accuracy and delivery errors, such as leaf errors and segment intensity errors during treatment. A calibration technique was used to remove the intensity modulations from the images leaving equivalent open field images that show patient anatomy that can be used for verification of the patient position. The images of the treatment beam can also be used to verify the delivery of the beam in terms of multileaf collimator leaf position and dosimetric errors. A series of controlled experiments delivering an IMRT anterior beam to the head and neck of a humanoid phantom were undertaken. A 2mm translation in the position of the phantom could be detected. With intentional introduction of delivery errors into the beam this method allowed us to detect leaf positioning errors of 2mm and variation in monitor units of 1%. The method was then applied to the case of a patient who received IMRT treatment to the larynx and cervical nodes. The anterior IMRT beam was imaged during four fractions and the images calibrated and investigated for the characteristic signs of patient position error and delivery error that were shown in the control experiments. No significant errors were seen. The method of imaging the IMRT beam and calibrating the images to remove the intensity modulations can be a useful tool in verifying both the patient position and the delivery of the beam.

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Bermanite Mn2þMn3þ2 ðPO4Þ2ðOHÞ2 � 4ðH2OÞ is a mixed valent hydrated hydroxy phosphate mineral. The mineral is reddish-brown and occurs in crystal aggregates and as lamellar masses. Bermanite is a common mineral in granitic pegmatites. The chemical composition of bermanite was obtained using EDS techniques. We have studied the molecular structure of bermanite using vibrational spectroscopy. The mineral is characterized by a Raman doublet at 991 and 999 cm-1 attributed to the phosphate stretching mode of two non-equivalent phosphate units. Raman bands at 1071, 1117 and 1142 cm-1 are assigned to the phosphate antisymmetric stretching modes. The hydroxyl stretching spectral region is complex with overlapping bands attributed to water and hydroxyl stretching vibrations. Vibrational spectroscopy proves most useful for the study of the mineral bermanite.

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In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.

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Cardiovascular diseases are a leading cause of death throughout the developed world. With the demand for donor hearts far exceeding the supply, a bridge-to-transplant or permanent solution is required. This is currently achieved with ventricular assist devices (VADs), which can be used to assist the left ventricle (LVAD), right ventricle (RVAD), or both ventricles simultaneously (BiVAD). Earlier generation VADs were large, volume-displacement devices designed for temporary support until a donor heart was found. The latest generation of VADs use rotary blood pump technology which improves device lifetime and the quality of life for end stage heart failure patients. VADs are connected to the heart and greater vessels of the patient through specially designed tubes called cannulae. The inflow cannulae, which supply blood to the VAD, are usually attached to the left atrium or ventricle for LVAD support, and the right atrium or ventricle for RVAD support. Few studies have characterized the haemodynamic difference between the two cannulation sites, particularly with respect to rotary RVAD support. Inflow cannulae are usually made of metal or a semi-rigid polymer to prevent collapse with negative pressures. However suction, and subsequent collapse, of the cannulated heart chamber can be a frequent occurrence, particularly with the relatively preload insensitive rotary blood pumps. Suction events may be associated with endocardial damage, pump flow stoppages and ventricular arrhythmias. While several VAD control strategies are under development, these usually rely on potentially inaccurate sensors or somewhat unreliable inferred data to estimate preload. Fixation of the inflow cannula is usually achieved through suturing the cannula, often via a felt sewing ring, to the cannulated chamber. This technique extends the time on cardiopulmonary bypass which is associated with several postoperative complications. The overall objective of this thesis was to improve the placement and design of rotary LVAD and RVAD inflow cannulae to achieve enhanced haemodynamic performance, reduced incidence of suction events, reduced levels of postoperative bleeding and a faster implantation procedure. Specific objectives were: * in-vitro evaluation of LVAD and RVAD inflow cannula placement, * design and in-vitro evaluation of a passive mechanism to reduce the potential for heart chamber suction, * design and in-vitro evaluation of a novel suture-less cannula fixation device. In order to complete in-vitro evaluation of VAD inflow cannulae, a mock circulation loop (MCL) was developed to accurately replicate the haemodynamics in the human systemic and pulmonary circulations. Validation of the MCL’s haemodynamic performance, including the form and magnitude of pressure, flow and volume traces was completed through comparisons of patient data and the literature. The MCL was capable of reproducing almost any healthy or pathological condition, and provided a useful tool to evaluate VAD cannulation and other cardiovascular devices. The MCL was used to evaluate inflow cannula placement for rotary VAD support. Left and right atrial and ventricular cannulation sites were evaluated under conditions of mild and severe heart failure. With a view to long term LVAD support in the severe left heart failure condition, left ventricular inflow cannulation was preferred due to improved LVAD efficiency and reduced potential for thrombus formation. In the mild left heart failure condition, left atrial cannulation was preferred to provide an improved platform for myocardial recovery. Similar trends were observed with RVAD support, however to a lesser degree due to a smaller difference in right atrial and ventricular pressures. A compliant inflow cannula to prevent suction events was then developed and evaluated in the MCL. As rotary LVAD or RVAD preload was reduced, suction events occurred in all instances with a rigid inflow cannula. Addition of the compliant segment eliminated suction events in all instances. This was due to passive restriction of the compliant segment as preload dropped, thus increasing the VAD circuit resistance and decreasing the VAD flow rate. Therefore, the compliant inflow cannula acted as a passive flow control / anti-suction system in LVAD and RVAD support. A novel suture-less inflow cannula fixation device was then developed to reduce implantation time and postoperative bleeding. The fixation device was evaluated for LVAD and RVAD support in cadaveric animal and human hearts attached to a MCL. LVAD inflow cannulation was achieved in under two minutes with the suture-less fixation device. No leakage through the suture-less fixation device – myocardial interface was noted. Continued development and in-vivo evaluation of this device may result in an improved inflow cannulation technique with the potential for off-bypass insertion. Continued development of this research, in particular the compliant inflow cannula and suture-less inflow cannulation device, will result in improved postoperative outcomes, life span and quality of life for end-stage heart failure patients.

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This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

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Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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This research segments male and female food shoppers based on store and product attribute evaluations, enjoyment, planning, and shopping responsibility. A rich profile for each segment is developed from a sample of 580 primary food shoppers. Gender comparisons are operationalized and these developed food shopper typologies are contrasted against earlier works. Factor analysis, cluster analysis, and ANOVA were employed to develop specific segments of shoppers. This is the first study to identify specific groups of male food shoppers and contrast these to traditional female shoppers and earlier typographical works. The research provides the basis for further cross-cultural, cross-contextual comparative studies.

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Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

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Queensland University of Technology (QUT) Library offers a range of resources and services to researchers as part of their research support portfolio. This poster will present key features of two of the data management services offered by research support staff at QUT Library. The first service is QUT Research Data Finder (RDF), a product of the Australian National Data Service (ANDS) funded Metadata Stores project. RDF is a data registry (metadata repository) that aims to publicise datasets that are research outputs arising from completed QUT research projects. The second is a software and code registry, which is currently under development with the sole purpose of improving discovery of source code and software as QUT research outputs. RESEARCH DATA FINDER As an integrated metadata repository, Research Data Finder aligns with institutional sources of truth, such as QUT’s research administration system, ResearchMaster, as well as QUT’s Academic Profiles system to provide high quality data descriptions that increase awareness of, and access to, shareable research data. The repository and its workflows are designed to foster better data management practices, enhance opportunities for collaboration and research, promote cross-disciplinary research and maximise the impact of existing research data sets. SOFTWARE AND CODE REGISTRY The QUT Library software and code registry project stems from concerns amongst researchers with regards to development activities, storage, accessibility, discoverability and impact, sharing, copyright and IP ownership of software and code. As a result, the Library is developing a registry for code and software research outputs, which will use existing Research Data Finder architecture. The underpinning software for both registries is VIVO, open source software developed by Cornell University. The registry will use the Research Data Finder service instance of VIVO and will include a searchable interface, links to code/software locations and metadata feeds to Research Data Australia. Key benefits of the project include:improving the discoverability and reuse of QUT researchers’ code and software amongst QUT and the QUT research community; increasing the profile of QUT research outputs on a national level by providing a metadata feed to Research Data Australia, and; improving the metrics for access and reuse of code and software in the repository.