456 resultados para temporal visualization techniques


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Grading is basic to the work of Landscape Architects concerned with design on the land. Gradients conducive to easy use, rainwater drained away, and land slope contributing to functional and aesthetic use are all essential to the amenity and pleasure of external environments. This workbook has been prepared specifically to support the program of landscape construction for students in Landscape Architecture. It is concerned primarily with the technical design of grading rather than with its aesthetic design. It must be stressed that the two aspects are rarely separate; what is designed should be technically correct and aesthetically pleasing - it needs to look good as well as to function effectively. This revised edition contains amended and new content which has evolved out of student classes and discussion with colleagues. I am pleased to have on record that every delivery of this workbook material has resulted in my own better understanding of grading and the techniques for its calculation and communication.

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This is the third TAProViz workshop being run at BPM. The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. We note this year the continuing interest in the visualisation of process mining data and resultant process models. More info at: http://wst.univie.ac.at/topics/taproviz14/

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After attending this presentation, attendees will gain awareness of the ontogeny of cranial maturation, specifically: (1) the fusion timings of primary ossification centers in the basicranium; and (2) the temporal pattern of closure of the anterior fontanelle, to develop new population-specific age standards for medicolegal death investigation of Australian subadults. This presentation will impact the forensic science community by demonstrating the potential of a contemporary forensic subadult Computed Tomography (CT) database of cranial scans and population data, to recalibrate existing standards for age estimation and quantify growth and development of Australian children. This research welcomes a study design applicable to all countries faced with paucity in skeletal repositories. Accurate assessment of age-at-death of skeletal remains represents a key element in forensic anthropology methodology. In Australian casework, age standards derived from American reference samples are applied in light of scarcity in documented Australian skeletal collections. Currently practitioners rely on antiquated standards, such as the Scheuer and Black1 compilation for age estimation, despite implications of secular trends and population variation. Skeletal maturation standards are population specific and should not be extrapolated from one population to another, while secular changes in skeletal dimensions and accelerated maturation underscore the importance of establishing modern standards to estimate age in modern subadults. Despite CT imaging becoming the gold standard for skeletal analysis in Australia, practitioners caution the application of forensic age standards derived from macroscopic inspection to a CT medium, suggesting a need for revised methodologies. Multi-slice CT scans of subadult crania and cervical vertebrae 1 and 2 were acquired from 350 Australian individuals (males: n=193, females: n=157) aged birth to 12 years. The CT database, projected at 920 individuals upon completion (January 2014), comprises thin-slice DICOM data (resolution: 0.5/0.3mm) of patients scanned since 2010 at major Brisbane Childrens Hospitals. DICOM datasets were subject to manual segmentation, followed by the construction of multi-planar and volume rendering cranial models, for subsequent scoring. The union of primary ossification centers of the occipital bone were scored as open, partially closed or completely closed; while the fontanelles, and vertebrae were scored in accordance with two stages. Transition analysis was applied to elucidate age at transition between union states for each center, and robust age parameters established using Bayesian statistics. In comparison to reported literature, closure of the fontanelles and contiguous sutures in Australian infants occur earlier than reported, with the anterior fontanelle transitioning from open to closed at 16.7±1.1 months. The metopic suture is closed prior to 10 weeks post-partum and completely obliterated by 6 months of age, independent of sex. Utilizing reverse engineering capabilities, an alternate method for infant age estimation based on quantification of fontanelle area and non-linear regression with variance component modeling will be presented. Closure models indicate that the greatest rate of change in anterior fontanelle area occurs prior to 5 months of age. This study complements the work of Scheuer and Black1, providing more specific age intervals for union and temporal maturity of each primary ossification center of the occipital bone. For example, dominant fusion of the sutura intra-occipitalis posterior occurs before 9 months of age, followed by persistence of a hyaline cartilage tongue posterior to the foramen magnum until 2.5 years; with obliteration at 2.9±0.1 years. Recalibrated age parameters for the atlas and axis are presented, with the anterior arch of the atlas appearing at 2.9 months in females and 6.3 months in males; while dentoneural, dentocentral and neurocentral junctions of the axis transitioned from non-union to union at 2.1±0.1 years in females and 3.7±0.1 years in males. These results are an exemplar of significant sexual dimorphism in maturation (p<0.05), with girls exhibiting union earlier than boys, justifying the need for segregated sex standards for age estimation. Studies such as this are imperative for providing updated standards for Australian forensic and pediatric practice and provide an insight into skeletal development of this population. During this presentation, the utility of novel regression models for age estimation of infants will be discussed, with emphasis on three-dimensional modeling capabilities of complex structures such as fontanelles, for the development of new age estimation methods.

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The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.

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Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

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Overarching Research Questions Are ACT motorists aware of roadside saliva based drug testing operations? What is the perceived deterrent impact of the operations? What factors are predictive of future intentions to drug drive? What are the differences between key subgroups

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Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

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The palette of fluorescent proteins (FPs) has grown exponentially over the past decade, and as a result, live imaging of cells expressing fluorescently tagged proteins is becoming more and more mainstream. Spinning disk confocal (SDC) microscopy is a high-speed optical sectioning technique and a method of choice to observe and analyze intracellular FP dynamics at high spatial and temporal resolution. In an SDC system, a rapidly rotating pinhole disk generates thousands of points of light that scan the specimen simultaneously, which allows direct capture of the confocal image with low-noise scientific grade-cooled charge-coupled device cameras, and can achieve frame rates of up to 1000 frames per second. In this chapter, we describe important components of a state-of-the-art spinning disk system optimized for live cell microscopy and provide a rationale for specific design choices. We also give guidelines of how other imaging techniques such as total internal reflection microscopy or spatially controlled photoactivation can be coupled with SDC imaging and provide a short protocol on how to generate cell lines stably expressing fluorescently tagged proteins by lentivirus-mediated transduction.

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Thirteen sites in Deception Bay, Queensland, Australia were sampled three times over a period of 7 months and assessed for contamination by a range of heavy metals, primarily As, Cd, Cr, Cu, Pb and Hg. Fraction analysis, enrichment factors and Principal Components Analysis-Absolute Principal Component Scores (PCA-APCS) analysis were conducted in order to identify the potential bioavailability of these elements of concern and their sources. Hg and Te were identified as the elements of highest enrichment in Deception Bay while marine sediments, shipping and antifouling agents were identified as the sources of the Weak acid Extractable Metals (WE-M), with antifouling agents showing long residence time for mercury contamination. This has significant implications for the future of monitoring and regulation of heavy metal contamination within Deception Bay.

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Two ultrasound survey methods were used to determine the presence and activity patterns of New Zealand long-tailed bats (Chalinolobus tuberculatus) in the city of Hamilton. First, 13 monthly surveys conducted at 18 green spaces found C. tuberculatus in only one urban forest reserve, Hammond Bush, where they were found consistently throughout the year. Bat activity was strongly related to temperature. Second, twice-yearly citywide surveys conducted over 2 years determined the distribution and habitat associations of C. tuberculatus. Bats were found only in the southern part of the city and were strongly associated with the Waikato River. Bat activity was negatively correlated with housing and street light density and positively correlated with topographical complexity. In Hamilton, topographical complexity indicates the presence of gullies. Gullies probably provide foraging and roosting opportunities and connect the river to distant forest patches. These results suggest that urban habitats can be useful for bats if gullies can link these to distant habitat fragments.