ppxscal/embedding_network huggingface dataset:
From the prototype to the final embedded system using the Ocarina AADL tool suite
Authors: Jerome Hugues, Bechir Zalila, Laurent Pautet, Fabrice Kordon
Venue: ACM Transactions on Embedded Computing Systems (TECS) (2008)

Building distributed deal-time embedded systems requires a stringent methodology, from early requirement capture to full implementation. However, there is a strong link between the requirements and the final implementation (e.g., scheduling and resource dimensioning). Therefore, a rapid prototyping process based on automation of tedious and error-prone tasks (analysis and code generation) is required to speed up the development cycle. In this article, we show how the AADL (Architecture Analysis and Design Language), which appeared in late 2004, helps solve these issues thanks to a dedicated tool suite. We then detail the prototyping process and its current implementation: Ocarina.
A Novel Algorithm of Color Tongue Image Segmentation Based on HSI
Authors: Jian-qiang Du, Yan-sheng Lu, Ming-feng Zhu, Kang Zhang, Cheng-hua Ding
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

It is fundamental work for objective tongue inspection to accurately segment tongue body from original image. This paper presents a new color tongue image segmentation algorithm based on HSI model. The Original image was converted to HSI space firstly. Then it was segmented by threshold value of hue and intensity component before it was converted to binary image. Finally the sequential algorithm was used to quickly mark the connected area and morphologic method was applied to fill little holes in the tongue body area. Experimental result shows it is a fast algorithm with good segmentation effect.
Information Assurance and Secure Streaming Algorithm Based on Cubic Roots of Integers
Authors: Boris S. Verkhovsky
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

In this paper three communication issues are considered: 1) security 2) reliability and 3) streaming of information. For the security of communication a new public-key cryptography algorithm, based on extraction of cubic roots modulo composite n=pq, is described. The paper demonstrates how to intertwine both the security requirement and communication assurance into one algorithmic protocol. Several examples of reliability protocols are introduced and their efficiencies (probabilities of failure, bandwidth requirement per block of transmitted ciphertext and complexities of decryption per block of ciphertext) are analyzed and compared.
Performance Analysis of the OGSA-DAI 3.0 Software
Authors: Kun Wang, Yuejian Xie, Sanli Li, Xiaoying Wang
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

OGSA-DAI provides an extensible Web service-based framework that allows data resources to be incorporated into Grid fabrics. The current OGSA-DAI release (OGSA-DAI GT 3.0), published in Sep. 2007, is a complete rewrite of its former version. In this paper we describe the performance of some key components. Under the predefined profiling environment, approach and tools, we conduct profiling from four perspectives: activity and resource performance, data query process performance, database connection and the pressure test. The profiling results would provide guides for the developers to make amendments in their future release, and for users to choose appropriate usages.
A theory of personalisation of appearance: quantitative evaluation of qualitatively derived data
Authors: A. F. Monk, J. O. Blom
Venue: Behaviour & Information Technology (2007)

Using qualitative data, Blom and Monk (2003) derived a theory of why people choose to personalise the appearance of their PCs and mobile phones. This paper describes some quantitative data that provide some support for, and some modifications to, the theory. Individuals having personal home pages were recruited to fill in a questionnaire that assesses dispositions to personalise and its effects. In addition the 82 home pages were inspected to assess the extent of personalisation. This correlated significantly with the dispositions 'Frequency of Use' and 'Knowledge of Personalisation'. The questionnaire items corresponding to effects were factor analysed. A four-factor solution suggested item groupings similar, but not identical, to those used in the theory. There are significant positive correlations between the extent of personalisation and cognitive effects and enduring emotional effects. The value of quantitative data for confirming and refining a qualitative theory is discussed.
Finding popular categories for RFID tags
Authors: Bo Sheng, Chiu Chiang Tan, Qun Li, Weizhen Mao
Venue: Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing (2008)

As RFID tags are increasingly attached to everyday items, it quickly becomes impractical to collect data from every tag in order to extract useful information. In this paper, we consider the problem of identifying popular categories of RFID tags out of a large collection of tags, without reading all the tag data. We propose two algorithms based on the idea of group testing, which allows us to efficiently derive popular categories of tags. We evaluate our solutions using both theoretical analysis and simulation.
Model identification and closed-loop control strategies for propofol anesthesia using bispectral index (BIS)
Authors: Hector Reboso Morales, Juan A. Mendez Perez, Jose A. Reboso Moreles, Leopoldo Acosta Sanchez, Santiago Torres Al Varez, Felipe Gonzalez Miranda
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

The Bispectral Index (BIS) is an electroencephalogram-derived measure of anesthetic depth. A closed-loop control system was developed using BIS as the control variable, different control algorithms based on PID and fuzzy logic, and a propofol target-controlled infusion system as the control actuator. A system identification based on ARX parametric estimation was performed and validated with a study on 10 patients. A time-variable model was obtained and turned out to be reliable to describe the process behavior and allowed the design of specially adapted control strategies with results that are being validated.
Bidding decision model for the card game Tarok
Authors: Domen Marinčič, Matjaž Gams, Mitja Luštrek
Venue: Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (2006)

In the paper we present a decision model for bidding in the card game four-player tarok. The decision model was built on the basis of Bayesian networks. We developed a program called Tarok7 for playing four-player tarok, which served as a testbed for evaluating the decision model. With the help of Tarok7 program, the model was compared to human experts. The results of the comparison show high matching of the program's bidding with the bidding of human experts.
Speech enhancement by joint statistical characterization in the Log Gabor Wavelet domain
Authors: Suman Senapati, Sandipan Chakroborty, Goutam Saha
Venue: Speech Communication (2008)

In speech enhancement, Bayesian Marginal models cannot explain the inter-scale statistical dependencies of different wavelet scales. Simple non-linear estimators for wavelet-based denoising assume that the wavelet coefficients in different scales are independent in nature. However, wavelet coefficients have significant inter-scale dependencies. This paper introduces a new method that uses the inter-scale dependency between the coefficients and their parents by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimators are derived by Maximum a Posteriori (MAP) estimation theory. The proposed work presents two different joint shrinkage estimators. In first, the inter-scale variance of LGW coefficients is kept constant which gives a closed form solution. In second, a relatively more complex approach is presented where variance is not constrained to be constant. It is also shown that the proposed methods show better performance when speech uncertainty is taken into consideration. The robustness of the proposed frameworks are tested on 50 speakers of POLYCOST and YOHO speech corpus in four different noisy environments against four established speech enhancement algorithms. Experimental results show that the proposed estimators yield a higher improvement in Segmental SNR (S-SNR) and also lower Log Spectral Distortion (LSD) compared to other estimators. In the second evaluation, the proposed speech enhancement techniques are found to give more robust Digit Recognition in noisy conditions on the AURORA 2.0 speech corpus compared to competing methods.
Triplet Markov Fields for the Classification of Complex Structure Data
Authors: Juliette Blanchet, Florence Forbes
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

We address the issue of classifying complex data. We focus on three main sources of complexity, namely the high dimensionality of the observed data, the dependencies between these observations and the general nature of the noise model underlying their distribution. We investigate the recent {\it Triplet Markov Fields} and propose new models in this class designed for such data and in particular allowing very general noise models. In addition, our models can handle the inclusion of a learning step in a consistent way so that they can be used in a supervised framework. One advantage of our models is that whatever the initial complexity of the noise model, parameter estimation can be carried out using state-of-the-art Bayesian clustering techniques under the usual simplifying assumptions. As generative models, they can be seen as an alternative, in the supervised case, to discriminative Conditional Random Fields. Identifiability issues underlying the models in the non supervised case, are discussed while the models performance is illustrated on simulated and real data exhibiting the mentioned various sources of complexity.
Numerical schemes for low Mach wave breaking
Authors: Frédéric Golay, Philippe Helluy
Venue: International Journal of Computational Fluid Dynamics (2007)

In this work, we describe a finite volume scheme for the computation of incompressible air-water flows. We use an artificial compressibility approach that permits us to use a completely explicit scheme. We describe successively the low Mach preconditioning of the scheme, the Riemann solver and then the non-conservative approach that is used to suppress velocity-pressure oscillations, the second order extensions and the parallel implementation. Then this is applied to the simulation of the breaking of a wave on a 15% slope.
A robust new method for the remote estimation of LAI in montane and boreal forests
Authors: D. M. McAllister, C. Valeo
Venue: International Journal of Remote Sensing (2007)

Two promising techniques for estimating Leaf Area Index (LAI) using remote sensing are Linear Spectral Mixture Analysis (LSMA) and Modification of Spectral Vegetation Indices (MSVI). The Normalized Distance Method (ND), which uses principles employed by the LSMA and MSVI techniques, is introduced in this study. These three methods are applied to a region of montane forest in Kananaskis Country, Alberta, Canada, in order to estimate LAI. In situ measurements of LAI in 10 deciduous and 10 coniferous plots, and a SPOT-4 image taken at the height of the growing season, provided test data that produced relationships for LAI in pure stands of either coniferous or deciduous vegetation using each of the three methods. All methods exhibited varying degrees of performance and demonstrated significant dependence on vegetation type. The ND method produced relationships with coefficients of determination (R 2) of 0.86 and 0.65 for coniferous and deciduous vegetation, respectively; the MSVI method (when using the adjusted Normalized Difference Vegetation Index) produced relationships with R 2 values of 0.79 and 0.59 for coniferous and deciduous vegetation, respectively; and the LSMA technique produced relationships with R 2 values of 0.83 and 0.0 for coniferous and deciduous vegetation, respectively.
Demystifying RESTful Data Coupling
Authors: Steve Vinoski
Venue: IEEE Internet Computing (2008)

Developers who favor technologies that promote interface specialization typically raise two specific objections to the uniform-interface constraint designed into the Representational State Transfer (REST) architectural style. One is that different resources should each have specific interfaces and methods that more accurately reflect their precise functionality. The other objection to the concept of a uniform interface is that it merely shifts all coupling issues and other problems to the data exchanged between client and server. Yet, that's based on the invalid assumption that the data exchanged in a REST system is just like the data exchanged in systems such as Web services and Corba, which require interface specialization.
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Authors: Dingding Wang, Tao Li, Shenghuo Zhu, Chris Ding
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of documents. Many approaches use statistics and machine learning techniques to extract sentences from documents. In this paper, we propose a new multi-document summarization framework based on sentence-level semantic analysis and symmetric non-negative matrix factorization. We first calculate sentence-sentence similarities using semantic analysis and construct the similarity matrix. Then symmetric matrix factorization, which has been shown to be equivalent to normalized spectral clustering, is used to group sentences into clusters. Finally, the most informative sentences are selected from each group to form the summary. Experimental results on DUC2005 and DUC2006 data sets demonstrate the improvement of our proposed framework over the implemented existing summarization systems. A further study on the factors that benefit the high performance is also conducted.
Ultrasonic wave feature extraction for neural network classification in not accessible pipes
Authors: G. Acciani, G. Brunetti, G. Fornarelli, C. Guaragnella
Venue: Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation (2005)

The ultrasonic inspection technique can be very useful to determine the state of non reachable structure. In this paper a method based on the neural network classification to evaluate the corrosion level of non accessible pipes is shown. A set of optimal features constitutes the database and feeds the neural network. These features are chosen by time and frequency features extracted from simulated ultrasonic waves. The results show that the method perform a good recognition rate and the different classes are useful for the human decision to evaluate the corrosion level of the pipe under test.
Categorization of land-cover change processes based on phenological indicators extracted from time series of vegetation index data
Authors: F. Lupo, M. Linderman, V. Vanacker, E. Bartholomé, E. F. Lambin
Venue: International Journal of Remote Sensing (2007)

A straightforward method for categorizing temporal patterns of land-cover change is presented. Two successive years of enhanced vegetation index (EVI) data derived from the Moderate Resolution Imagery Spectrometer (MODIS) were analysed. Five phenological indicators were extracted. Based on the inter-annual difference of each of the five indicators, indices of change in phenology were calculated. An unsupervised classification of these five indices of change applied to pixels characterized by a high change magnitude led to the identification of seven categories of land-cover change patterns. Thirty-one per cent of the change pixels could clearly be explained by a difference in only one or two phenological indicators, e.g. a shift in the start of the growing season or an interruption of the growing season due to floods. The remaining change pixels were explained by a combination of more than two indices of change. The output of this analysis is an allocation of change pixels to broad categories of land-cover change as a preliminary step for finer resolution analyses.
A matroid-friendly basis for the quasisymmetric functions
Authors: Kurt W. Luoto
Venue: Journal of Combinatorial Theory Series A (2008)

A new Z-basis for the space of quasisymmetric functions (QSym, for short) is presented. It is shown to have nonnegative structure constants, and several interesting properties relative to the quasisymmetric functions associated to matroids by the Hopf algebra morphism F of Billera, Jia, and Reiner [L.J. Billera, N. Jia, V. Reiner, A quasisymmetric function for matroids, arXiv:math.CO/0606646]. In particular, for loopless matroids, this basis reflects the grading by matroid rank, as well as by the size of the ground set. It is shown that the morphism F distinguishes isomorphism classes of rank two matroids, and that decomposability of the quasisymmetric function of a rank two matroid mirrors the decomposability of its base polytope. An affirmative answer to the Hilbert basis question raised in [L.J. Billera, N. Jia, V. Reiner, A quasisymmetric function for matroids, arXiv:math.CO/0606646] is given.
Exploring the throughput-fairness tradeoff of deadline scheduling in heterogeneous computing environments
Authors: Vasumathi Sundaram, Abhishek Chandra, Jon Weissman
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

The scalability and computing power of large-scale computational platforms has made them attractive for hosting compute-intensive time-critical applications. Many of these applications are composed of computational tasks that require specific deadlines to be met for successful completion. In this paper, we show that combining redundant scheduling with deadline-based scheduling in these systems leads to a fundamental tradeoff between throughput and fairness. We propose a new scheduling algorithm called Limited Resource Earliest Deadline (LRED) that couples redundant scheduling with deadline-driven scheduling in a flexible way by using a simple tunable parameter to exploit this tradeoff. Our evaluation of LRED shows that LRED provides a powerful mechanism to achieve desired throughput or fairness under high loads and low timeliness environments.
Selecting good expansion terms for pseudo-relevance feedback
Authors: Guihong Cao, Jian-Yun Nie, Jianfeng Gao, Stephen Robertson
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Pseudo-relevance feedback assumes that most frequent terms in the pseudo-feedback documents are useful for the retrieval. In this study, we re-examine this assumption and show that it does not hold in reality - many expansion terms identified in traditional approaches are indeed unrelated to the query and harmful to the retrieval. We also show that good expansion terms cannot be distinguished from bad ones merely on their distributions in the feedback documents and in the whole collection. We then propose to integrate a term classification process to predict the usefulness of expansion terms. Multiple additional features can be integrated in this process. Our experiments on three TREC collections show that retrieval effectiveness can be much improved when term classification is used. In addition, we also demonstrate that good terms should be identified directly according to their possible impact on the retrieval effectiveness, i.e. using supervised learning, instead of unsupervised learning.
A Family of Nonparametric Statistics for LROC Curves
Authors: Liansheng Tang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

The location response operating characteristic (LROC) curve provides an elegant tool to evaluate observer performance in both correctly localizing a lesion in an abnormal image and distinguishing an abnormal image from a normal image, while the receiver operating characteristic (ROC) curve is only able to evaluate an observer's performance of the latter task. At the beginning of this paper, we review a general family of nonparametric summary statistics for ROC curves. After we discuss a parametric LROC method, we propose an alternative nonparametric method to estimate the area under the LROC curve. Our estimator consists of a general family of nonparametric summary statistics for LROC curves. We illustrated the use of our estimator through a diagnostic imaging example.
Distributed Authentication Systems Enhanced by Quantum Protocols
Authors: Adrian Kapczynski, Marcin Sobota
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

In the article problem of securing distributed biometric authentication system was discussed. After introduction to biometric domain, the key issues connected with secure communication in distributed authentication environments were briefly described. In this work a concept of enhancement of biometric authentication system by application of quantum protocols was formulated. Two quantum protocols were analyzed. Obtained experimental results enable further development of research work in chosen area.
EMG-based hand gesture recognition for realtime biosignal interfacing
Authors: Jonghwa Kim, Stephan Mastnik, Elisabeth André
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2008)

In this paper the development of an electromyogram (EMG) based interface for hand gesture recognition is presented. To recognize control signs in the gestures, we used a single channel EMG sensor positioned on the inside of the forearm. In addition to common statistical features such as variance, mean value, and standard deviation, we also calculated features from the time and frequency domain including Fourier variance, region length, zerocrosses, occurrences, etc. For realizing real-time classification assuring acceptable recognition accuracy, we combined two simple linear classifiers (k-NN and Bayes) in decision level fusion. Overall, a recognition accuracy of 94% was achieved by using the combined classifier with a selected feature set. The performance of the interfacing system was evaluated through 40 test sessions with 30 subjects using an RC Car. Instead of using a remote control unit, the car was controlled by four different gestures performed with one hand. In addition, we conducted a study to investigate the controllability and ease of use of the interface and the employed gestures.
Proceedings of the nineteenth conference on Australasian database - Volume 75
Venue: ACM International Conference Proceeding Series; Vol. 313 (2008)

The Australasian Database Conference series is an annual forum for exploring research, development, and novel applications of database systems. The Nineteenth Australasian Database Conference, ADC 2008, is being held at The University of Wollongong as part of the Australasian Computer Science Week. ADC 2008 invited submission of papers describing original contributions in all fields of database research and applications. We received 42 submissions of full papers, and each was thoroughly reviewed by at least three experts, either members of the programme committee or else colleagues under their supervision. After extensive discussion, the committee accepted 18 papers, each of which had good support from the reviewers as a technically sound, important and well presented contribution to the field. We thank all the reviewers for their work in making this conference a valuable experience for the participants.