830 resultados para Object based video
Resumo:
This thesis positions practitioner research within the emerging discipline of fashion and disputes that practitioner knowledge of fashion is predominantly tacit. This research contributes to the understanding of practitioner knowledge and proposes an object based model of practitioner research as an alternative to existing practice-led methodologies. The thesis theorises fashion objects as a site of significant knowledge and argues their potential to record and communicate fashion knowledge and disseminate practice-led research.
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This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.
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Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.
Resumo:
Budgie Smuggler is the first work of a series entitled slang, reflecting upon other, often unintended meanings behind popular Australian expressions. Synonymous with Australian beach humour, the term budgie smuggler unintentionally masks the desperately tragic plight of wildlife trafficked every year within and beyond our borders. Bird wildlife are fiercely protectively of their kin, often flocking to a site of distress of those trapped or injured - a commotion ensues, helping to scare predators away. The work contemplates our own position and action in response to our captive feathered friends. Budgie Smuggler is a soft resin/silicon, cotton material, fibreglass and recycled object based artwork.
Resumo:
The Taita Hills in southeastern Kenya form the northernmost part of Africas Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor. Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable reflectance throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular reflectance field measurements were taken and where horizontal visibility meteorological data concurrent with image acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive surface reflectance factor within an RMSE of < 0.02 ps in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium- and high-resolution optical satellite imagery, as well the utilized SPOT data.
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We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.
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Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanics. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero backlash belts can be used, making the StiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics.
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An important characteristic of virtual assembly is interaction. Traditional di-rect manipulation in virtual assembly relies on dynamic collision detection, which is very time-consuming and even impossible in desktop virtual assembly environment. Feature-matching isa critical process in harmonious virtual assembly, and is the premise of assembly constraint sens-ing. This paper puts forward an active object-based feature-matching perception mechanism and afeature-matching interactive computing process, both of which make the direct manipulation in vir-tual assembly break away from collision detection. They also help to enhance virtual environmentunderstandability of user intention and promote interaction performance. Experimental resultsshow that this perception mechanism can ensure that users achieve real-time direct manipulationin desktop virtual environment.
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Study on the structural coupling relationship between basin and range is not only helpful to recognize the basin formation and evolution systematically, but also to guide petroleum exploration in the basin. As a late Paleozoic Orogen, the South Tianshan Mountains reactivated and uplifted rapidly during the Cenozoic, and led to the Mesozoic-Cenozoic considerable thick deposits in the Kuqa Depression. The researches of the dissertation were carried out in the Kuqa depression-South Tianshan M ountain s ystem, a nd t he b rittle m icrotectonics w. ere c hosen as t he m ost important object. Based on observations and measurements of the field, we made detailed investigations on the geometry and kinematics of this area, and analyzed the abutting and cutting relationships and relative sequence of many brittle structures, such as joint, shear fractures, faults and some small-scale structures related to them closely. According to those brittle fractures' relationships with stress, the nature and variation of regional palaeostress field during the Cenozoic were studied through inversion of fault slip data and inferring stress state from joint sequences. And the deformation time was estimated primarily via ESR dating of faulting. Results show that the stress field varies as well in times as in space. The maximal principal stress direction shifted from the vertical to the horizontal, and stress regime from weak extension to strong compression from the Paleogene to the Neogene regionally. During the late Neogene, the structural deformation of the South Tianshan and the basin-range boundary was dominated by near N-S extension, while near N-S compressive deformation in the interior of the Kuqa Depression. There exits obvious differential stress state from the north to the south. ESR dating of the faulting during the Cenozoic indicates that, the normal faulting in the north edge of the Kuqa Depression have been active all along from the Miocene to the early Pleistocene, but the thrusting and reverse faulting in the interior only been active from the Pliocene to the early Pleistocene. On the base of those geological data and some geophysical information and theoretical calculation results, we infer that, the different stress regime the basin-range system is ascribed to the vertical uplift of the Tianshan Mountain. It was the vertical uplift that lead to the gravity-driven gliding of thick layers lying on the faulted basement from the South Tianshan Mountain to the Kuqa depression, and to folding and thrusting in the interior and frontal of the Kuqa depression. Combining the structural evolution with petroleum geological conditions of the Kuqa Depression, we think that the strong compressive deformation of the Kuqa Depression during rapid uplifting of the Tianshan Mountains from the Pliocene to the early Pleistocene play crucial role in the structural trap formation and proliferous gas accumulation.
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There is extensive agreement that attention may play a role in spatial stimmlus coding (Lu & Proctor, 1995). Some authors investigated the effects of spatial attention on the spatial coding by using spatial cueing procedure and spatial Stroop task. The finding was that the stroop effects were modulated by spatial cueing. Three hypotheses including attentional shift account, referential coding account, and event integration account were used to explain the modulation of spatial cueing over the spatial Stroop effects. In these previous studies, on validly cued trials, cue and target not only appeared at the same location, but also in the same object, which resulted in both location and object cued. Consequently, the modulation of spatial attentional cueing over spatial Stroop effects was confounded with the role of object-based attention. In the third chapter of this dissertation, using a modification of double rectangles cueing procedure developed by Egly, Driver and Rafal (1994) and spatial Stroop task employed by Lupiñez and Funes (2005), separate effects of spatial attention and object-based attention on the location code of visual stimuli were investigated. Across four experiments, the combined results showed that spatial Stroop effects were modulate by object-based attention, but not by location-based attention. This pattern of results could be well explained by event integration account, but not by attentional shift account and referential coding account. In the fourth chapter, on the basis of the prior chapter, whether the modulation of attentional cueing on location code occurred at the stage of perceptual identification or response choice was investigated. The findings were that object-based attention modulated spatial Stroop effects and did not modulate the Simon effects, whereas spatial attention did not modulate Stroop and Simon effects. This pattern of results partially replicated the outcome of the previous chapter. The previous studies generally argued that the conflicts of spatial Stroop task and Simon task respectively occurred at at the stage of perceptual identification and response choice. Therefore, it is likely to conclude that the modulation of attention over spatial Stroop effect was mediated by object-based attention, and this modulation occurred at the stage perceptual identification. Considering that the previous studies mostly investigated the effects of attention captured by abrupt onset on the spatial Stroop effects, few studies investigated the effects of attention captured by offset cue on the spatial Stroop effects. The aim of the fifth chapter was to investigate the role of attention induced by offset and abrupt onset cue in the spatial Stroop task. These results showed that attention elicited by offset cue or abrupt onset cue modulated the spatial Stroop effects, which reconciled with event integration account.
Resumo:
In terms of a general time theory which addresses time-elements as typed point-based intervals, a formal characterization of time-series and state-sequences is introduced. Based on this framework, the subsequence matching problem is specially tackled by means of being transferred into bipartite graph matching problem. Then a hybrid similarity model with high tolerance of inversion, crossover and noise is proposed for matching the corresponding bipartite graphs involving both temporal and non-temporal measurements. Experimental results on reconstructed time-series data from UCI KDD Archive demonstrate that such an approach is more effective comparing with the traditional similarity model based algorithms, promising robust techniques for lager time-series databases and real-life applications such as Content-based Video Retrieval (CBVR), etc.
Resumo:
Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.
Resumo:
Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.
