ppxscal/embedding_network huggingface dataset:
Up close and pedagogical: computing academics talk about teaching
Authors: Cat Kutay, Raymond Lister
Venue: Proceedings of the 8th Austalian conference on Computing education - Volume 52 (2006)

This paper describes and enacts a process for bootstrapping a more systematic discussion of computing education within a school of computing at a research-intensive Australasian university. Thus far, the project has gone through three stages. In the first stage, some academics were interviewed about their approach to teaching. In the second stage, selected anonymous quotes from the interviews were presented and discussed by other interested members of the school at workshops. In the final stage, selected anonymous quotes from the interviews and workshops were placed on a web-based survey, to which interested members of the school responded. These forms of data will be used to drive further stages of debate within the school. The theoretical underpinnings of this project are Wenger's concept of a community of practice, phenomenography, and socially constructivism. The aim is not to instruct the academics in any "right way" to teach. Instead, the aim is to facilitate debate, where the teachers identify the problems, and in finding the solutions they construct their own "pedagogic reality". As facilitators of this process, the authors of this paper highlighted dialectically opposed views in quotes from the teachers, and then allow the teachers to synthesise those views into a more sophisticated view. Our ultimate project aim is to grow a teaching community that balances reified theories of teaching and learning with participation in a community of practice.
On Characterizing and Analyzing Diffusion Tensor Images by Learning their Underlying Manifold Structure
Authors: Parmeshwar Khurd, Ragini Verma, Christos Davatzikos
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

The growing importance of diffusion tensor imaging (DTI) in studying the white matter architecture in normal and pathologic states necessitates the development of tools for comprehensive analysis of diffusion tensor data. Operations such as multivariate statistical analysis and hypothesis testing, interpolation and filtering, must now be performed on tensor data, and must overcome challenges introduced by the non-linearity and high dimensionality of the tensors. In this paper, we present a novel approach to performing these computations by modeling the underlying manifold structure of the tensors, using a combination of two manifold learning techniques, isometric mapping (ISOMAP) and local tangent space alignment (LTSA). While ISOMAP identifies the dimensionality of the manifold of the tensors and embeds the tensors into a linear space, facilitating statistical computations therein, operations like interpolation and filtering, integral to the process of normalization, require the reconstruction of the tensor in the tensor domain. To obtain this reverse mapping from the linear space to the tensor domain, i.e. to the domain of the original tensor data, we use LTSA. The modeling of the underlying manifold structure renders our approach better applicable to tensor data than existing methods that may not always be able to capture the non-linearity present in the tensors under consideration. In various simulations with known ground truth, we demonstrate the effectiveness of our framework based on ISOMAP and LTSA in performing a comprehensive analysis of DTI data.
Reputation in self-organized communication systems and beyond
Authors: Jochen Mundinger, Jean-Yves Le Boudec
Venue: Proceedings from the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer & communications sytems (2006)

Efficiently handling reputation is important in dealing with free-riding, malicious attacks and random failures in self-organized communication systems. At the same time, work in this context is often found to be relevant in many other disciplines, in particular the social sciences. A number of distributed reputation systems have been proposed and analyzed, although research has not been very coherent. In this paper, for the first time, we provide an overview of the state-of-the-art in the various computer science communities as well as the social sciences. In particular, we present results obtained from our mathematical model devised to investigate the impact of liars on their peers' reputation about a subject. We find that liars have no impact unless their number exceeds a certain threshold (phase transition behaviour). We give precise formulae and quantify the impact, thereby providing insight into fundamental questions in social networks as well as facilitating performance evaluation and optimization of distributed reputation systems in communication networks. We conclude by suggesting fundamental directions for future research into reputation.
Welcome from General Chair Workshop on Secure Software Engineering Education and Training
Authors: Samuel T. Jr. Redwine
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

The subject matter for this one-day workshop is the experience, current situation, and future of education and training in software engineering of (more) secure software. This is a workshop for those from education, government, and industry at all levels doing education or training in secure software engineering and for those who would like to - as well as others interested in the subject of secure software engineering or the required workforce.
H/sup /spl infin// adaptive filtering
Authors: B. Hassibi, T. Kailath
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

H/sup /spl infin// optimal estimators guarantee the smallest possible estimation error energy over all possible disturbances of fixed energy, and are therefore robust with respect to model uncertainties and lack of statistical information on the exogenous signals. We have shown that if the prediction error is considered, then the celebrated LMS adaptive filtering algorithm is H/sup /spl infin// optimal. We consider prediction of the filter weight vector itself, and for the purpose of coping with time-variations, exponentially weighted, finite-memory and time-varying adaptive filtering. This results in some new adaptive filtering algorithms that may be useful in uncertain and non-stationary environments. Simulation results are given to demonstrate the feasibility of the algorithms and to compare them with well-known H/sup 2/ (or least-squares based) adaptive filters.
Appropriate Agile Measurement: Using Metrics and Diagnostics to Deliver Business Value
Authors: Deborah Hartmann, Robin Dymond
Venue: Proceedings of the conference on AGILE 2006 (2006)

Agile Software Development continually measures both our product and the process used to create it, to allow improvement. With increased popularity, more risk-averse groups are being drawn to Agile, bringing with them modes of evaluation incompatible with Agile values and principles. These outmoded metrics drive dysfunctional behaviors which threaten the integrity of an emerging Agile culture. This paper collects some of the current thinking on appropriate Agile metrics, and proposes simple tools for use by teams or organizations. The intention of these tools is to foster dialogue about the appropriateness of metrics in a given context, and thereby to encourage measurements more congruent with the objectives of Agile teamwork.
Fluid sketching of directed graphs
Authors: James Arvo, Kevin Novins
Venue: Proceedings of the 7th Australasian User interface conference - Volume 50 (2006)

We describe a prototype sketch-based system that allows users to draw and manipulate directed graphs using gestural input exclusively. The system incorporates the notion of fluid sketching, which attempts to recognize and beautify what the user is drawing while it is being drawn. This concept applies to both the drawing of vertices, which are morphed to circles, and to the drawing of edges, which are approximated on-the-fly by a constrained projection onto low-order polynomials. Consequently, all user-drawn strokes are cleaned up by continuously morphing or projecting them to the nearest geometrically precise shapes. The system has a unique look and feel in that the currently-displayed graph is always at or in transition toward a clean and precise representation of what the user has drawn or is in the process of drawing. When vertices of the graph are dragged to new locations or edges are reshaped, the original graph connectivity is maintained while simultaneously retaining some of its original user-drawn character, such as vertex size and placement, and overall edge shape.
Introducing perpetual analytics
Authors: Jeff Jonas
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Common strategies to liberate an organization's information assets for situational awareness frequently rely on infrastructure components such as data integration, enterprise search, federation, data warehousing, and so on. And while these traditional platforms enable analysts to get better and faster answers to their queries, the next big advance will change this paradigm. Users cannot be expected to formulate and ask every smart question every day. And to escape this impractical and un-scalable model, the new paradigm will involve technologies where "the data finds the data" and "relevance finds the user." Perpetual Analytics describes a class of application whereby enterprise context is assembled, in real-time, on data streams as fast as operational systems record observations. Context construction is a "data finds the data" activity which enables events of interest to be streamed to subscribers. In this talk, I will talk at some depth about the dynamics of such systems including scalability and sustainability.
Serving Learning and Assessment in SCALE
Authors: Maria Grigoriadou, Evangelia Gouli, Agoritsa Gogoulou, Maria Samarakou
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve leaning and assessment. SCALE supports individualized and collaborative learning and engages learners in different forms of assessment by providing various functions and by embedding a number of tools. Personalized navigation support and feedback are offered, based on learner's knowledge level and preferences.
Exact reconstruction from periodic nonuniform samples
Authors: B. Foster, C. Herley
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

We examine the problem of reconstructing a discrete-time signal given only n of its M-phase components. Borrowing analysis from the field of perfect reconstruction filter banks enables us to derive necessary and sufficient conditions under which reconstruction is possible. Essentially, in a perfect reconstruction system, the conditions required to reconstruct from partial information are equivalent to the conditions needed to ensure that the rest of the information does not contribute to the reconstructed signal. This allows us to reconstruct multiband signals which have an overall bandwidth of no more than B, yet cannot be reconstructed from uniformly spaced samples at the minimum rate of B/2/spl pi/.
Some typical classes of t-norms and the 1-Lipschitz Condition
Authors: Benjamin Callejas Bedregal, Ivan Pan
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

This paper studies the relation between the satisfaction of the Lipschitz condition by t-norms for constant 1 (1- Lipschitz condition) and some other properties of t-norms. In this sense, we will consider some well know classes of continuous t-norms, such as Archimedean and non Archimedean, and the nilpotent and strict subclasses of Archimedean t-norms. Also will be proved that the unique automorphism which preserves the 1- Lipschitz condition of any t-norm is the identity.
On the problem of proper reparametrization for rational curves and surfaces
Authors: Sonia Pérez-Díaz
Venue: Computer Aided Geometric Design (2006)

A rational parametrization of an algebraic curve (resp. surface) establishes a rational correspondence of this curve (resp. surface) with the affine or projective line (resp. affine or projective plane). This correspondence is a birational equivalence if the parametrization is proper. So, intuitively speaking, a rational proper parametrization trace the curve or surface once. We consider the problem of computing a proper rational parametrization from a given improper one. For the case of curves we generalize, improve and reinterpret some previous results. For surfaces, we solve the problem for some special surface's parametrizations.
Bitext alignment for statistical machine translation
Authors: William Byrne
Venue:  (2006)

Bitext alignment is the task of finding translation equivalence between documents in two languages, collections of which are commonly known as bitext. This dissertation addresses the problems of statistical alignment at various granularities from sentence to word with the goal of creating Statistical Machine Translation (SMT) systems. SMT systems are statistical pattern processors based on parameterized models estimated from aligned bitext training collections. The collections are large enough that alignments must be created using automatic methods. The bitext collections are often available as aligned documents, such as news stories, which usually need to be further aligned at the sentence level and the word level before statistics can be extracted from the bitext. We develop statistical models that are learned from data in an unsupervised way. Language independent alignment algorithms are derived for efficiency and effectiveness. We first address the problem of extracting bitext chunk pairs, which are translation segments at the sentence or sub-sentence level. To extract these bitext chunk pairs, we formulate a model of translation as a stochastic generative model over parallel documents, and derive several different alignment procedures through various formulations of the component distributions. Based on these models we propose a hierarchical chunking procedure that produces chunk pairs by a series of alignment operations in which coarse alignment of large sections of text is followed by a more detailed alignment of their subsections. We show practical benefits with this chunking scheme, observing in particular that it makes efficient use of bitext by aligning sections of text that simpler procedures would discard as spurious. For the problem of word alignment in bitext, we propose a novel Hidden Markov Model based Word-to-Phrase (WtoP) alignment model, which is formulated so that alignment and parameter estimation can be performed efficiently using standard HMM algorithms. We find that the word alignment performance of the WtoP model is comparable to that of IBM Model-4, currently considered the state of the art, even in processing large bitext collections. We use this Word-to-Phrase model to define a posterior distribution over translation phrase pairs in the bitext, and develop a phrase-pair extraction procedure based on this posterior distribution. We show that this use of the phrase translation posterior distribution allows us to extract a richer inventory of phrases than results from with current techniques. In the evaluation of large Chinese-English SMT systems, we find that systems derived from word-aligned bitext created using the WtoP model perform comparably to systems derived from Model-4 word alignments, and in Arabic-English we find significant gains from using WtoP alignments.
An FPGA-Based Verification Framework for Real-Time Vision Systems
Authors: Gooitzen van der Wal, Frederic Brehm, Michael Piacentino, James Marakowitz, Eduardo Gudis, Azhar Sufi, James Montante
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Field-Programmable Gate Arrays (FPGAs) have become a mainstay in the digital electronics world both for the ease of implementation as well as their inherent usefulness in incrementally refining hardware designs. When moving to an Application Specific Integrated Circuit (ASIC) or System on a Chip (SoC), verification becomes a very time consuming process, with virtually no room for error. As a result, a variety of methods have been devised to decrease the risk when creating an ASIC or SoC. We describe a hardware and software framework for testing real-time vision algorithms for lowering the uncertainty in FPGA and SoC development, while reducing the SoC verification time. The framework benefits from hardware and software verification, ease of reconfiguration for testing multiple vision algorithms, and an iterative hardware/ software co-design.
Time-frequency analysis of Doppler radar data using Gabor data-adaptive weighting window
Authors: B. Ristich
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

The author summarizes the development of a data-adaptive smoothed Wigner-Ville function (WVF) time-frequency representation (TFR) that suppresses cross terms and noise effects. A Gabor TFR of a data set is performed to obtain the Gabor coefficients relative to the selected Gabor basis wavelet. Because the Gabor TFR involves only linear operations on the data, no cross-term artifacts are introduced. Published maximum likelihood tests can then be applied to the Gabor coefficients to sort those estimated to be signal-related Gabor coefficients from those estimated to be noise-related coefficients (Friedlander and Porat, 1987, 1989, 1992). The signal-related Gabor coefficients only are then used to form a data-adaptive multiplicative weighting kernel applied to the complex ambiguity function computed from the data which is double Fourier transformed to create a filtered WVF TFR. This processing approach retains the usual time-frequency localization properties of the WVF on actual signal components, while suppressing the effect of cross terms and noise components by essentially forcing the WVF TFR to have zero support where zero support was found in the Gabor TFR. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Auditory Peripersonal Space in Humans
Authors: Alessandro Farnè
Venue: Journal of Cognitive Neuroscience (2002)

In the present study we report neuropsychological evidence of the existence of an auditory peripersonal space representation around the head in humans and its characteristics. In a group of right brain-damaged patients with tactile extinction, we found that a sound delivered near the ipsilesional side of the head (20 cm) strongly extinguished a tactile stimulus delivered to the contralesional side of the head (cross-modal auditory&mdash;tactile extinction). By contrast, when an auditory stimulus was presented far from the head (70 cm), cross-modal extinction was dramatically reduced. This spatially specific cross-modal extinction was most consistently found (i.e., both in the front and back spaces) when a complex sound was presented, like a white noise burst. Pure tones produced spatially specific cross-modal extinction when presented in the back space, but not in the front space. In addition, the most severe cross-modal extinction emerged when sounds came from behind the head, thus showing that the back space is more sensitive than the front space to the sensory interaction of auditory&ndash;tactile inputs. Finally, when cross-modal effects were investigated by reversing the spatial arrangement of cross-modal stimuli (i.e., touch on the right and sound on the left), we found that an ipsilesional tactile stimulus, although inducing a small amount of cross-modal tactile&ndash;auditory extinction, did not produce any spatial-specific effect. Therefore, the selective aspects of cross-modal interaction found near the head cannot be explained by a competition between a damaged left spatial representation and an intact right spatial representation. Thus, consistent with neurophysiological evidence from monkeys, our findings strongly support the existence, in humans, of an integrated cross-modal system coding auditory and tactile stimuli near the body, that is, in the peripersonal space.
GA-Based Internet Traffic Classification Technique for QoS Provisioning
Authors: Junghun Park, Hsiao-Rong Tyan, C.-C. Jay Kuo
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

A fast and robust scheme that classifies Internet packets according to their application types is proposed in this work. The scheme is deployed at ISP for QoS provisioning, scalability and reliability. The proposed classification scheme consists of two steps: feature selection and classification. For feature selection, practical features are extracted using the modified multistage filter. By using the genetic algorithm (GA) and a variant of the wrapper method, we obtain two sets of features for comparison. As to classifiers, decision trees such as J48 and REPTree. The decision trees are trained with selected features from real traffics. The trained decision trees are compared with a classifier using the NBKE approach in terms of accuracy and robustness. It is demonstrated by simulation results that decision trees with features selected by GA gives the best performance. Finally, early classification with modified multistage filters is proposed to reduce collision errors for fast and robust performance.
The Context of Uncertainty Modulates the Subcortical Response to Predictability
Authors: Amanda Bischoff-grethe, Megan Martin, Hui Mao, Gregory S. Berns
Venue: Journal of Cognitive Neuroscience (2001)

Implicit motor learning tasks typically involve comparisons of subject responses during a sequence versus a random condition. In neuroimaging, brain regions that are correlated with a sequence are described, but the temporal relationship of sequence versus nonsequence conditions is often not explored. We present a functional magnetic resonance imaging (fMRI) study describing activation related to sequential predictability in an implicit sensorimotor learning task and the history (context) dependence of these effects. Participants regarded four squares displayed horizontally across a screen and pressed a button when any one of the four targets was illuminated in a particular color. A repeating spatial sequence with varying levels of predictability was embedded within a random color presentation. Both the right dorsolateral prefrontal cortex (R DLPFC) and right caudate displayed a positive correlation to increasing predictability, whereas the left posterior parietal cortex (L PPC) displayed a negative correlation. However, the activation changes within the caudate were significant when transitioning from high predictability to low predictability but not for the reverse case, suggesting a sensitivity not only to predictability but to order effects as well. These results support the hypothesized relationship between basal ganglia and visuomotor sequential learning, but demonstrate the importance of context upon sequence learning.