993 resultados para IMAGE SPECTRUM


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Researchers examined the sun-protective intentions and behavior of young, Caucasian, Australian sportswomen aged between 17 and 35 years (N = 100). The study adopted a 2 x 2 experimental design, comparing group norms (supportive vs. non-supportive) and image norms (tanned vs. pale) related to sun protection and taking into account group identification with friends and peers in the sport. While no significant findings emerged involving image norms, regression analyses revealed a significant two-way interaction for group norm x identification on recreational sportswomen's intentions to engage in sun protection in the next fortnight. Participants identifying strongly with their group had stronger intentions to engage in sun protection when exposed to a norm reflecting fellow recreational sportswomen engaging in sun-protective actions in comparison to those exposed to a non-supportive group. In addition, while prior intentions to engage in sun protection were not significantly related to sun-protection behavior, post-manipulation intentions after exposure to the sun-protective information that was provided were significantly related to follow-up behavior. Overall, the findings supported the importance of group-based social influences, rather than tanned media images, on sun-protective decisions among young recreational sportswomen and provided a targeted source for intervention strategies encouraging sun safety among this at-risk group for repeated sun exposure.

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We propose a computationally efficient image border pixel based watermark embedding scheme for medical images. We considered the border pixels of a medical image as RONI (region of non-interest), since those pixels have no or little interest to doctors and medical professionals irrespective of the image modalities. Although RONI is used for embedding, our proposed scheme still keeps distortion at a minimum level in the embedding region using the optimum number of least significant bit-planes for the border pixels. All these not only ensure that a watermarked image is safe for diagnosis, but also help minimize the legal and ethical concerns of altering all pixels of medical images in any manner (e.g, reversible or irreversible). The proposed scheme avoids the need for RONI segmentation, which incurs capacity and computational overheads. The performance of the proposed scheme has been compared with a relevant scheme in terms of embedding capacity, image perceptual quality (measured by SSIM and PSNR), and computational efficiency. Our experimental results show that the proposed scheme is computationally efficient, offers an image-content-independent embedding capacity, and maintains a good image quality

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Bulk amount of graphite oxide was prepared by oxidation of graphite using the modified Hummers method and its ultrasonication in organic solvents yielded graphene oxide (GO). X-ray diffraction (XRD) pattern, X-ray photoelectron (XPS), Raman and Fourier transform infrared (FTIR) spectroscopy indicated the successful preparation of GO. XPS survey spectrum of GO revealed the presence of 66.6 at% C and 30.4 at% O. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) images of the graphene oxide showed that they consist of a large amount of graphene oxide platelets with a curled morphology containing of a thin wrinkled sheet like structure. AFM image of the exfoliated GO signified that the average thickness of GO sheets is ~1.0 nm which is very similar to GO monolayer. GO/epoxy nanocomposites were prepared by typical solution mixing technique and influence of GO on mechanical and thermal properties of nanocomposites were investigated. As for the mechanical behaviour of GO/epoxy nanocomposites, 0.5 wt% GO in the nanocomposite achieved the maximum increase in the elastic modulus (~35%) and tensile strength (~7%). The TEM analysis provided clear image of microstructure with homogeneous dispersion of GO in the polymer matrix. The improved strength properties of GO/epoxy nanocomposites can be attributed to inherent strength of GO, the good dispersion and the strong interfacial interactions between the GO sheets and the polymer matrix. However, incorporation of GO showed significant negative effect on composite glass transition temperature (Tg). This may arise due to the interference of GO on curing reaction of epoxy.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manner. In this paper, we address the lack of a systematic exploration of the fundamental relations that can be used to capture the behavior of concurrent systems, i.e., co-occurrence, conflict, causality, and concurrency. Besides the definition of the spectrum of behavioral relations, which we refer to as the 4C spectrum, we also show that our relations give rise to implication lattices. We further provide operationalizations of the proposed relations, starting by proposing techniques for computing relations in unlabeled systems, which are then lifted to become applicable in the context of labeled systems, i.e., systems in which state transitions have semantic annotations. Finally, we report on experimental results on efficiency of the proposed computations.

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Highly sensitive infrared cameras can produce high-resolution diagnostic images of the temperature and vascular changes of breasts. Wavelet transform based features are suitable in extracting the texture difference information of these images due to their scale-space decomposition. The objective of this study is to investigate the potential of extracted features in differentiating between breast lesions by comparing the two corresponding pectoral regions of two breast thermograms. The pectoral regions of breastsare important because near 50% of all breast cancer is located in this region. In this study, the pectoral region of the left breast is selected. Then the corresponding pectoral region of the right breast is identified. Texture features based on the first and the second sets of statistics are extracted from wavelet decomposed images of the pectoral regions of two breast thermograms. Principal component analysis is used to reduce dimension and an Adaboost classifier to evaluate classification performance. A number of different wavelet features are compared and it is shown that complex non-separable 2D discrete wavelet transform features perform better than their real separable counterparts.

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This thesis is an innovative study for organic synthesis using supported gold nanoparticles as photocatalysts under visible light irradiation. It especially examines a novel green process for efficient hydroamination of alkynes with amines. The investigation of other traditional reduction and oxidation reactions also adds significantly to the knowledge of gold nanoparticles and titania nanofibres as photocatalysts for organic synthesis.

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Microvessel density (MVD) is a widely used surrogate measure of angiogenesis in pathological specimens and tumour models. Measurement of MVD can be achieved by several methods. Automation of counting methods aims to increase the speed, reliability and reproducibility of these techniques. The image analysis system described here enables MVD measurement to be carried out with minimal expense in any reasonably equipped pathology department or laboratory. It is demonstrated that the system translates easily between tumour types which are suitably stained with minimal calibration. The aim of this paper is to offer this technique to a wider field of researchers in angiogenesis.

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Background Adenocarcinoma of the esophagogastric junction (AEG) as described by Siewert et al. is classified as one entity in the latest (7th Edition) American Joint Cancer Committee/International Union Against Cancer (AJCC/UICC) manual, compared with the previous mix of esophageal and gastric staging systems. The origin of AEG tumors, esophageal or gastric, and their biology remain controversial, particularly for AEG type II (cardia) tumors. Methods We adapted a large prospective database (n = 520: 180 type I, 182 type II, 158 type III) to compare AEG tumors under the new TNM system Pathological variables associated with prognosis were compared (pT, pN, stage, differentiation, R status, lymphovascular invasion, perineural involvement, number of positive nodes, percent of positive nodes, and tumor length), as well as overall survival. Results Compared with AEG type I tumors, type II and type III tumors had significantly (p\0.05) more advanced pN stages, greater number and percentage of positive nodes, poorer differentiation, more radial margin involvement, and more perineural invasion. In AEG type I, 14/180 patients (8%) had[6 involved nodes (pN3), compared with 16 and 30% of patients classified type II and III, respectively. Median survival was significantly (p = 0.03) improved for type I patients (38 months) compared with those with tumors classified as type II (28 months) and type III (24 months). In multivariate analysis node positivity and pN staging but not AEG site had an impact on survival. Conclusions In this series AEG type I is associated with more favorable pathologic features and improved outcomes compared with AEG type II and III. This may reflect earlier diagnosis, but an alternative possibility, that type I may be a unique paradigm with more favorable biology, requires further study. © Société Internationale de Chirurgie 2010.

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There are several methods for determining the proteoglycan content of cartilage in biomechanics experiments. Many of these include assay-based methods and the histochemistry or spectrophotometry protocol where quantification is biochemically determined. More recently a method based on extracting data to quantify proteoglycan content has emerged using the image processing algorithms, e.g., in ImageJ, to process histological micrographs, with advantages including time saving and low cost. However, it is unknown whether or not this image analysis method produces results that are comparable to those obtained from the biochemical methodology. This paper compares the results of a well-established chemical method to those obtained using image analysis to determine the proteoglycan content of visually normal (n=33) and their progressively degraded counterparts with the protocols. The results reveal a strong linear relationship with a regression coefficient (R2) = 0.9928, leading to the conclusion that the image analysis methodology is a viable alternative to the spectrophotometry.

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Provision of an individually responsive education requires a comprehensive understanding of the inner worlds of learners, such as their feelings and thoughts. However, this is difficult to achieve when learners, such as those with Autism Spectrum Disorders (ASD) and cognitive difficulties, have problems with communication. To address this issue, the current exploratory descriptive study sought the views of 133 Singaporean parents and teachers of school-age learners with ASD and cognitive difficulties regarding the inner experience of their children and students. The findings highlight the variety of abilities and difficulties found in how these learners experience their own mental states and understand those of others. These abilities and difficulties are characterized according to type of mental state and analysed in line with three qualia, those of experience, recursive awareness and understanding. The findings indicate that learners show a greater awareness of their own mental states compared to their ability to understand these same mental states in others. Educational implications are discussed.

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In the expanding literature on creative practice research, art and design are often described as a unified field. They are bracketed together (art-and-design), referred to as interchangeable terms (art/design), and nested together, as if the practices of one domain encompass the other. However it is possible to establish substantial differences in research approaches. In this chapter we argue that core distinctions arise out of the goals of the research, intentions invested in the resulting “artefacts” (creative works, products, events), and the knowledge claims made for the research outcomes. Moreover, these fundamental differences give rise to a number of contingent attributes of the research such as the forming contexts, methodological approaches, and ways of evidencing and reporting new knowledge. We do not strictly ascribe these differences to disciplinary contexts. Rather, we use the terms effective practice research and evocative practice research to describe the spirit of the two distinctive research paradigms we identify. In short, effective practice research (often pursued in design fields) seeks a solution (or resolution) to a problem identified with a particular community, and it produces an artefact that addresses this problem by effecting change (making a situation, product or process more efficient or effective in some way). On the other hand, evocative practice research (often pursued by creative arts fields) is driven by individual pre-occupations, cultural concerns or human experience more broadly. It produces artefacts that evoke affect and resonance, and are poetically irreducible in meaning. We cite recent examples of creative research projects that illustrate the distinctions we identify. We then go on to describe projects that integrate these modes of research. In this way, we map out a creative research spectrum, with distinct poles as well as multiple hybrid possibilities. The hybrid projects we reference are not presented as evidence an undifferentiated field. Instead, we argue that they integrate research modes in deliberate, purposeful and distinctive ways: employing effective practice research methods in the production of evocative artefacts or harnessing evocative (as well as effective) research paradigms to effect change.

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This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

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In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.

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The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.