486 resultados para Specific recognition
Resumo:
The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.
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Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining strategies have been adapted to reduce noisy information from extracted features; however, text-mining techniques suffer from low frequency. The key issue is how to discover relevance features in text documents to fulfil user information needs. To address this issue, we propose a new method to extract specific features from user relevance feedback. The proposed approach includes two stages. The first stage extracts topics (or patterns) from text documents to focus on interesting topics. In the second stage, topics are deployed to lower level terms to address the low-frequency problem and find specific terms. The specific terms are determined based on their appearances in relevance feedback and their distribution in topics or high-level patterns. We test our proposed method with extensive experiments in the Reuters Corpus Volume 1 dataset and TREC topics. Results show that our proposed approach significantly outperforms the state-of-the-art models.
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This paper describes a texture recognition based method for segmenting kelp from images collected in highly dynamic shallow water environments by an Autonomous Underwater Vehicle (AUV). A particular challenge is image quality that is affected by uncontrolled lighting, reduced visibility, significantly varying perspective due to platform egomotion, and kelp sway from wave action. The kelp segmentation approach uses the Mahalanobis distance as a way to classify Haralick texture features from sub-regions within an image. The results illustrate the applicability of the method to classify kelp allowing construction of probability maps of kelp masses across a sequence of images.
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Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.
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How do you identify "good" teaching practice in the complexity of a real classroom? How do you know that beginning teachers can recognise effective digital pedagogy when they see it? How can teacher educators see through their students’ eyes? The study in this paper has arisen from our interest in what pre-service teachers “see” when observing effective classroom practice and how this might reveal their own technological, pedagogical and content knowledge. We asked 104 pre-service teachers from Early Years, Primary and Secondary cohorts to watch and comment upon selected exemplary videos of teachers using ICT (information and communication technologies) in Science. The pre-service teachers recorded their observations using a simple PMI (plus, minus, interesting) matrix which were then coded using the SOLO Taxonomy to look for evidence of their familiarity with and judgements of digital pedagogies. From this, we determined that the majority of preservice teachers we surveyed were using a descriptive rather than a reflective strategy, that is, not extending beyond what was demonstrated in the teaching exemplar or differentiating between action and purpose. We also determined that this method warrants wider trialling as a means of evaluating students’ understandings of the complexity of the digital classroom.
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"In this chapter the authors present a critique of Participatory Evaluation as worked in development projects, in this case, in Nepal. The article works between established claims that Participatory Evaluation builds capacity at programmatic and organisational levels, and the specific experiences of these claims in the authors’ current work. They highlight the need to address key difficulties such as high turn-over of staff and resulting loss of capacity to engage in Participatory Evaluation, and the difficulty of communication between academic as compared with local practical wisdoms. A key issue is the challenge of addressing the inevitable issues of power inequities that such approaches encounter. While Participatory Evaluation has been around for some time, it has only enjoyed more widespread recognition of its value in comparatively recent times, with its uptake in international development environments. To this extent, the practice is still in its early stages of development, and Jo, June and Michael’s work contributes to strengthening and more comprehensively understanding it. With regard to the meta-theme of this publication, this chapter is an example of how context not only influences the methodology to be used and the praxis of how it is to be used, but contributes to early explication of the core nature of an emerging methodology."
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Software to create individualised finite element (FE) models of the osseoligamentous spine using pre-operative computed tomography (CT) data-sets for spinal surgery patients has recently been developed. This study presents a geometric sensitivity analysis of this software to assess the effect of intra-observer variability in user-selected anatomical landmarks. User-selected landmarks on the osseous anatomy were defined from CT data-sets for three scoliosis patients and these landmarks were used to reconstruct patient-specific anatomy of the spine and ribcage using parametric descriptions. The intra-observer errors in landmark co-ordinates for these anatomical landmarks were calculated. FE models of the spine and ribcage were created using the reconstructed anatomy for each patient and these models were analysed for a loadcase simulating clinical flexibility assessment. The intra-observer error in the anatomical measurements was low in comparison to the initial dimensions, with the exception of the angular measurements for disc wedge and zygapophyseal joint (z-joint) orientation and disc height. This variability suggested that CT resolution may influence such angular measurements, particularly for small anatomical features, such as the z-joints, and may also affect disc height. The results of the FE analysis showed low variation in the model predictions for spinal curvature with the mean intra-observer variability substantially less than the accepted error in clinical measurement. These findings demonstrate that intra-observer variability in landmark point selection has minimal effect on the subsequent FE predictions for a clinical loadcase.
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This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.
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The effect of two different DNA minor groove binding molecules, Hoechst 33258 and distamycin A, on the binding kinetics of NF-κB p50 to three different specific DNA sequences was studied at various salt concentrations. Distamycin A was shown to significantly increase the dissociation rate constant of p50 from the sequences PRDII (5′-GGGAAATTCC-3′) and Ig-κ B (5′-GGGACTTTCC-3′) but had a negligible effect on the dissociation from the palindromic target-κB binding site (5′-GGGAATTCCC-3′). By comparison, the effect of Hoechst 33258 on binding of p50 to each sequence was found to be minimal. The dissociation rates for the protein–DNA complexes increased at higher potassium chloride concentrations for the PRDII and Ig-κB binding motifs and this effect was magnified by distamycin A. In contrast, p50 bound to the palindromic target-κB site with a much higher intrinsic affinity and exhibited a significantly reduced salt dependence of binding over the ionic strength range studied, retaining a KD of less than 10 pM at 150 mM KCl. Our results demonstrate that the DNA binding kinetics of p50 and their salt dependence is strongly sequence-dependent and, in addition, that the binding of p50 to DNA can be influenced by the addition of minor groove-binding drugs in a sequence-dependent manner.
Resumo:
Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.
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Gene expression profiling using microarrays and xenograft transplants of human cancer cell lines are both popular tools to investigate human cancer. However, the undefined degree of cross hybridization between the mouse and human genomes hinders the use of microarrays to characterize gene expression of both the host and the cancer cell within the xenograft. Since an increasingly recognized aspect of cancer is the host response (or cancer-stroma interaction), we describe here a bioinformatic manipulation of the Affymetrix profiling that allows interrogation of the gene expression of both the mouse host and the human tumour. Evidence of microenvironmental regulation of epithelial mesenchymal transition of the tumour component in vivo is resolved against a background of mesenchymal gene expression. This tool could allow deeper insight to the mechanism of action of anti-cancer drugs, as typically novel drug efficacy is being tested in xenograft systems.
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The expression of transgenes in plant genomes can be inhibited by either transcriptional gene silencing or posttranscriptional gene silencing (PTGS). Overexpression of the chalcone synthase-A (CHS-A) transgene triggers PTGS of CHS-A and thus results in loss of flower pigmentation in petunia. We previously demonstrated that epigenetic inactivation of CHS-A transgene transcription leads to a reversion of the PTGS phenotype. Although neomycin phosphotransferase II (nptII), a marker gene co-introduced into the genome with the CHS-A transgene, is not normally silenced in petunia, even when CHS-A is silenced, here we found that nptII was silenced in a petunia line in which CHS-A PTGS was induced, but not in the revertant plants that had no PTGS of CHS-A. Transcriptional activity, accumulation of short interfering RNAs, and restoration of mRNA level after infection with viruses that had suppressor proteins of gene silencing indicated that the mechanism for nptII silencing was posttranscriptional. Read-through transcripts of the CHS-A gene toward the nptII gene were detected. Deep-sequencing analysis revealed a striking difference between the predominant size class of small RNAs produced from the read-through transcripts (22 nt) and that from the CHS-A RNAs (21 nt). These results implicate the involvement of read-through transcription and distinct phases of RNA degradation in the coincident PTGS of linked transgenes and provide new insights into the destabilization of transgene expression.
Resumo:
For the past decade, at least, varieties of small, hand held networked instruments have appeared on the global scene, selling in record numbers, and being utilized by all manner of persons from the old to the young; children, women, men, the wealthy and the poor and in all countries. Their presences bespeak a radical shift in telecommunications infrastructure and the future of communications. They are particularly visible in urban areas where mobile transmission network infrastructure (3G, 4G, cellular and Wi-Fi) is more established and substantial, options more plentiful, and density of populations more dramatic. These end user products—I phones, cell phones, Blackberries, DSi, DS, IPads, Zooms, and others – of the mobile communications industry are the latest, hottest globalized commodities. At the same time, wirelessness, or the state of being wireless, and therefore capable of taking along one's networks, communicating from unlikely spaces, and navigating with GPS, is a complex social, political and economic communications phenomenon of early 21st century life. This thesis examines the specter of being wireless in cities. It lends the entire idea an experimentally envisioned, historical and planned context wherein personalization of media tools is seen both as a design development of corporate, artistic, and military imagination, as well as a profound social phenomenon enabling new forms of sharing, belonging, and urban community. In doing that it asserts the parameters of a new mobile space which, aside from clear benefits to humankind by way of mobility, has reinscribed numerous categories including gender. Moreover, it posits the recognition of other, more nuanced theoretical spaces for complex readings of gender and gendered use, including some instantiation of the notion of 'network' itself as a cyborgian and gendered social form. Additionally, cities are studied as places where technology is not only quickly popularized, but is connected to larger political interests, such as the reading of data, tracking of information, and the new security culture. In so doing the work has been undertaken as an urban spatial analysis and experimental ethnography, utilizing architectural, feminist, techno-utopian, industrial and theoretical literatures as discursive underpinnings from whence understandings and interpretations of mobile space, the mobile office, networked mobility, and personal media have come, linking the space of cities to specific, pioneering urban public art projects in which voice, texting and MMS have been utilized in expressions of ubiquitous networks and urban history. Through numerous examples of techno art, the thesis discusses the 'wireless city' as an emerging cultural, socially constructed economic and spatial entity, both conceived and formed through historic processes of urbanization.
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Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.
Resumo:
Background Parents play a significant role in shaping youth physical activity (PA). However, interventions targeting PA parenting have been ineffective. Methodological inconsistencies related to the measurement of parental influences may be a contributing factor. The purpose of this article is to review the extant peer-reviewed literature related to the measurement of general and specific parental influences on youth PA. Methods A systematic review of studies measuring constructs of PA parenting was conducted. Computerized searches were completed using PubMed, MEDLINE, Academic Search Premier, SPORTDiscus, and PsycINFO. Reference lists of the identified articles were manually reviewed as well as the authors' personal collections. Articles were selected on the basis of strict inclusion criteria and details regarding the measurement protocols were extracted. A total of 117 articles met the inclusionary criteria. Methodological articles that evaluated the validity and reliability of PA parenting measures (n=10) were reviewed separately from parental influence articles (n=107). Results A significant percentage of studies used measures with indeterminate validity and reliability. A significant percentage of articles did not provide sample items, describe the response format, or report the possible range of scores. No studies were located that evaluated sensitivity to change. Conclusion The reporting of measurement properties and the use of valid and reliable measurement scales need to be improved considerably.