934 resultados para Convolutional codes
Resumo:
Professional discourse in education has been the focus of research conducted mostly with teachers and professional practitioners but the work of students in the built environment has largely been ignored. This article presents an analysis of students’ visual discourse in the final professional year of a landscape architecture course in Brisbane, Australia. The study has a multi-method design and includes drawings, interviews and documentary materials, but focuses on the drawings in this paper. Using the theory of Bernstein, the analysis considers student representations as interrelations between professional identity and discretionary space for legitimate knowledge formation in landscape planning. It shows a shift in how students persuade the teacher of their expanding views of this field. The discussion of this shift centres on the professional knowledge that students choose rather than need to learn. It points to the differences within a class that a teacher must address in curriculum design in a contemporary professional course.
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In this paper we present a novel distributed coding protocol for multi-user cooperative networks. The proposed distributed coding protocol exploits the existing orthogonal space-time block codes to achieve higher diversity gain by repeating the code across time and space (available relay nodes). The achievable diversity gain depends on the number of relay nodes that can fully decode the signal from the source. These relay nodes then form space-time codes to cooperatively relay to the destination using number of time slots. However, the improved diversity gain is archived at the expense of the transmission rate. The design principles of the proposed space-time distributed code and the issues related to transmission rate and diversity trade off is discussed in detail. We show that the proposed distributed space-time coding protocol out performs existing distributed codes with a variable transmission rate.
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The present paper addresses the findings of a preliminary investigation into policy and codes of conduct pertaining to the use of laptops and PDA’s in business meetings. The purpose of this study was to conduct a review of policies or codes of conduct pertaining to the use of laptops and PDAs in meetings. The investigation included academic literature, policy searches in the public domain of the Internet, as well as personal contact with target industries (large corporations – N=1000 + employees). The results highlight the dearth of policy and codes of conducts pertaining to the use of laptops and PDA’s in business meetings. Consequently, given the growing interdependence between mobile technologies and the contemporary workplace, there exists an opportunity for communication professionals to further research and develop policy and codes of conduct in this area. Implications for corporate communication policies and practices are also discussed.
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In this paper we propose a new method for face recognition using fractal codes. Fractal codes represent local contractive, affine transformations which when iteratively applied to range-domain pairs in an arbitrary initial image result in a fixed point close to a given image. The transformation parameters such as brightness offset, contrast factor, orientation and the address of the corresponding domain for each range are used directly as features in our method. Features of an unknown face image are compared with those pre-computed for images in a database. There is no need to iterate, use fractal neighbor distances or fractal dimensions for comparison in the proposed method. This method is robust to scale change, frame size change and rotations as well as to some noise, facial expressions and blur distortion in the image
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Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.
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This paper focuses on codes of practice in domestic (in-country) and international (out of country) philanthropic giving/grantmaking, their similarities and differences. Codes of principle and practice are interesting not so much because they accurately reflect differences in practice on the ground, but rather because they indicate what is considered important or relevant, as well as aspirational. Codes tell us what people are most concerned about – what is seen to be in need of regulation or reminder.
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We propose to use a simple and effective way to achieve secure quantum direct secret sharing. The proposed scheme uses the properties of fountain codes to allow a realization of the physical conditions necessary for the implementation of no-cloning principle for eavesdropping-check and authentication. In our scheme, to achieve a variety of security purposes, nonorthogonal state particles are inserted in the transmitted sequence carrying the secret shares to disorder it. However, the positions of the inserted nonorthogonal state particles are not announced directly, but are obtained by sending degrees and positions of a sequence that are pre-shared between Alice and each Bob. Moreover, they can confirm that whether there exists an eavesdropper without exchanging classical messages. Most importantly, without knowing the positions of the inserted nonorthogonal state particles and the sequence constituted by the first particles from every EPR pair, the proposed scheme is shown to be secure.
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We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.
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We observe that MDS codes have interesting properties that can be used to construct ideal threshold schemes. These schemes permit the combiner to detect cheating, identify cheaters and recover the correct secret. The construction is later generalised so the resulting secret sharing is resistant against the Tompa-Woll cheating.
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Many educators are currently interested in using computer-mediated communications (CMCs) to support learning and creative practice. In my work I have been looking at how we might create drama through using cyberspaces, working with teachers and students in secondary school contexts. In trying to understand issues that have arisen and ways of working with the data I have found a number of frameworks helpful for analysing the online interactions. These frameworks draw from O'Toole's work on contexts negotiated in the creation of drama and other frameworks drawn from Wertsch, Bakhtin and Vygotsky's work on speech utterances, dialogic processes and internalisation of learning. The contexts and factors which must be negotiated in online communications within learning contexts are quite complex and educators may need to provide parameters and protocols to ensure appropriate languages, genres and utterances are utilised. The paper explores some of the types of languages, genres and utterances that emerged from a co-curricula drama project and issues that arose, including the importance of establishing processes for giving and receiving critical feedback This paper is of relevance to those whose research strategies may involve the use of computer-mediated communications as well as those utilising cyberspaces in educational contexts.
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This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.
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Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.
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This paper describes the limitations of using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) to characterise patient harm in hospitals. Limitations were identified during a project to use diagnoses flagged by Victorian coders as hospital-acquired to devise a classification of 144 categories of hospital acquired diagnoses (the Classification of Hospital Acquired Diagnoses or CHADx). CHADx is a comprehensive data monitoring system designed to allow hospitals to monitor their complication rates month-to-month using a standard method. Difficulties in identifying a single event from linear sequences of codes due to the absence of code linkage were the major obstacles to developing the classification. Obstetric and perinatal episodes also presented challenges in distinguishing condition onset, that is, whether conditions were present on admission or arose after formal admission to hospital. Used in the appropriate way, the CHADx allows hospitals to identify areas for future patient safety and quality initiatives. The value of timing information and code linkage should be recognised in the planning stages of any future electronic systems.