ppxscal/embedding_network huggingface dataset:
Wired pigs: ad-hoc wireless sensor networks in studies of animal welfare
Authors: I. McCauley, B. Matthews, L. Nugent, A. Mather, J. Simons
Venue: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors (2005)

The potential for the use of ad-hoc wireless sensor network technology in experimental investigations in animal welfare was explored in a study of the effect of the immediate environment on the body temperature of pigs. Sensors to simultaneously measure core and surface temperature were implanted in four pigs and monitored for a week using the open source application, TinyDB. Concurrently, a network of environmental sensors measuring predominantly temperature and humidity was placed around the pigs and this network was managed and monitored using a commercial package, Sensicast Developers Version (Sensicast DV). Approximately 100000 data points were gathered during the study. It was found to be significantly easier to develop, deploy and maintain the sensor network using Sensicast DV, and that there were significant problems when TinyDB was faced with large amounts of frequent sampling. However, TinyDB provided greater flexibility than Sensicast DV in its capacity to support more sensor platforms.
A Tk OpenGL widget
Authors: Claudio Esperança
Venue: Proceedings of the 5th conference on Annual Tcl/Tk Workshop 1997 - Volume 5 (1997)

We present TkOGL, a Tk widget that enables the creation and display of 3D graphics using the OpenGL API. Our approach features a reasonably complete Tcl binding to the core OpenGL functionality, as well as a set of extensions that implement a higher-level interface to many common utility functions such as those provided by the OpenGL utility library (GLU).
A modified joint source-channel model for transliteration
Authors: Asif Ekbal, Sudip Kumar Naskar, Sivaji Bandyopadhyay
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Most machine transliteration systems transliterate out of vocabulary (OOV) words through intermediate phonemic mapping. A framework has been presented that allows direct orthographical mapping between two languages that are of different origins employing different alphabet sets. A modified joint source-channel model along with a number of alternatives have been proposed. Aligned transliteration units along with their context are automatically derived from a bilingual training corpus to generate the collocational statistics. The transliteration units in Bengali words take the pattern C+M where C represents a vowel or a consonant or a conjunct and M represents the vowel modifier or matra. The English transliteration units are of the form C*V* where C represents a consonant and V represents a vowel. A Bengali-English machine transliteration system has been developed based on the proposed models. The system has been trained to transliterate person names from Bengali to English. It uses the linguistic knowledge of possible conjuncts and diphthongs in Bengali and their equivalents in English. The system has been evaluated and it has been observed that the modified joint source-channel model performs best with a Word Agreement Ratio of 69.3% and a Transliteration Unit Agreement Ratio of 89.8%.
Power-law shot noise model for the ultrasound RF echo
Authors: M. A. Kutay
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

We model the radio-frequency (RF) ultrasound echo by a shot noise process with narrow-band power-law filter function. As a consequence, the in-phase and quadrature components of the return signal are shown to exhibit 1/f/sup /spl beta// type spectral behavior. The envelope also exhibits this type of spectral behavior but with a different exponent. The model parameters, namely the rate of the point process and the power-law exponent, are related to tissue density and attenuation, respectively. Since these tissue characteristics change due to disease, estimates of the model parameters are investigated as potential tissue characterization features. We validate our claims based on clinical ultrasound images.
Proposal of Dynamic Module Library for System Level Modeling and Simulation of Dynamically Reconfigurable Systems
Authors: Kenji Asano, Junji Kitamichi, Kenichi Kuroda
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

In this paper, we propose a library for the system level modeling and simulation of dynamically reconfigurable architectures( DRAs). Using the proposed library, the designer can model the system specifications including modules for the dynamic generation and elimination that are needed in the design of dynamically reconfigurable systems. In addition, we evaluate the proposed library by the modeling and simulation of sample circuits, such as multi-context DRA and partially DRA. Using the proposed library, we can model the system specifications as much the same amount as a detailed description, such as one using multiplexers and de-multiplexers, which is a modeling formula for describing multi-context DRA. Under some conditions, higher-speed simulation is possible using the proposed library.
Efficient compilation of a class of variational forms
Authors: Robert C. Kirby, Anders Logg
Venue: ACM Transactions on Mathematical Software (TOMS) (2007)

We investigate the compilation of general multilinear variational forms over affines simplices and prove a representation theorem for the representation of the element tensor (element stiffness matrix) as the contraction of a constant reference tensor and a geometry tensor that accounts for geometry and variable coefficients. Based on this representation theorem, we design an algorithm for efficient pretabulation of the reference tensor. The new algorithm has been implemented in the FEniCS Form Compiler (FFC) and improves on a previous loop-based implementation by several orders of magnitude, thus shortening compile-times and development cycles for users of FFC.
Integration of speech to computer-assisted translation using finite-state automata
Authors: Shahram Khadivi, Richard Zens, Hermann Ney
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

State-of-the-art computer-assisted translation engines are based on a statistical prediction engine, which interactively provides completions to what a human translator types. The integration of human speech into a computer-assisted system is also a challenging area and is the aim of this paper. So far, only a few methods for integrating statistical machine translation (MT) models with automatic speech recognition (ASR) models have been studied. They were mainly based on N-best rescoring approach. N-best rescoring is not an appropriate search method for building a real-time prediction engine. In this paper, we study the incorporation of MT models and ASR models using finite-state automata. We also propose some transducers based on MT models for rescoring the ASR word graphs.
A Note on Linear Time Algorithms for Maximum Error Histograms
Authors: Sudipto Guha, Kyuseok Shim
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Histograms and Wavelet synopses provide useful tools in query optimization and approximate query answering. Traditional histogram construction algorithms, e.g., V-Optimal, use error measures which are the sums of a suitable function, e.g., square, of the error at each point. Although the best-known algorithms for solving these problems run in quadratic time, a sequence of results have given us a linear time approximation scheme for these algorithms. In recent years, there have been many emerging applications where we are interested in measuring the maximum (absolute or relative) error at a point. We show that this problem is fundamentally different from the other traditional {\rm{non}}{\hbox{-}}\ell_\infty error measures and provide an optimal algorithm that runs in linear time for a small number of buckets. We also present results which work for arbitrary weighted maximum error measures.
Multi-program approach for simulating recorded extracellular signals generated by neurons coupled to microelectrode arrays
Authors: Paolo Massobrio, Giuseppe Massobrio, Sergio Martinoia
Venue: Neurocomputing (2007)

Purpose of this paper is to present a new tool for characterizing the coupling between neurons and micro-electrode arrays (MEAs), based on a multi-program simulation approach. As a result, recorded extracellular signals generated by networks of neurons coupled to MEAs can be simulated with a combined interaction of modified and developed models implemented in simulation programs such as Spice, Neuron, and Matlab. The proposed approach allows an efficient simulation of the behaviour of the specific neuron-electrode junctions and the simulation of synaptically connected neuronal populations. Models of the neuron, synapse, microelectrode and neuron-electrode junction are presented and comparison between simulation results and multi-site extracellular recordings are shown.
QCCS: A Formal Model to Enforce QoS Requirements in Service Composition
Authors: Sun Meng
Venue: Proceedings of the First Joint IEEE/IFIP Symposium on Theoretical Aspects of Software Engineering (2007)

Assuring quality of service (QoS) requirements is critical when assembling a Service-oriented Application (SOA) from a repository of existing services. This paper presents an approach for assuring satisfaction of QoS requirements in service-oriented systems.We investigate a calculus called QCCS, for representing both behaviour and QoS requirements in services. The notion of quantified bisimulation on services provide us a measure on the degree of equivalence of services based on costs. We introduce a quantified version of CTL and show how QoS properties of services can be specified in our framework.
Energy-Efficient Data Dissemination for Wireless Sensor Networks
Authors: Marcel Busse, Thomas Haenselmann, Wolfgang Effelsberg
Venue: Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops (2007)

In order to disseminate a large amount of data through a sensor network, it is common to split the data into small-sized chunk packets. If the data is additionally encoded by a forward error correction (FEC) code, missed chunks can be recovered. Fountain codes are a special kind of FEC code which have the property that the sender provides the data in a virtually endless stream by combining original chunks at random. No matter which chunks get lost, each receiver only needs any k chunks from the stream. In broadcast scenarios, fountains have the additional advantage that only little redundancy is required, even if several receivers have missed different chunks. We will show the benefit of Fountain codes in wireless sensor networks in comparison to raw transmissions and other FEC codes. To support the actual data dissemination, we propose two generic distributed protocols: an acknowledgement-based and a request-based protocol. The evaluation is carried out in a real testbed consisting of 20 sensor nodes.
Smart cards in hostile environments
Authors: Howard Gobioff, Sean Smith, J. D. Tygar, Bennet Yee
Venue: Proceedings of the 2nd conference on Proceedings of the Second USENIX Workshop on Electronic Commerce - Volume 2 (1996)

One often hears the claim that smart cards are the solution to a number of security problems, including those arising in point-of-sale systems. In this paper, we characterize the minimal properties necessary for the secure smart card point-of-sale transactions. Many proposed systems fail to provide these properties: problems arise from failures to provide secure communication channels between the user and the smart card while operating in a potentially hostile environment (such as a point-of-sale application.) Moreover, we discuss several types of modifications that can be made to give smart cards additional input/output capacity with a user, and describe how this additional I/O can address the hostile environment problem. We give a notation for describing the effectiveness of smart cards under various environmental assumptions. We discuss several security equivalences among different scenarios for smart cards in hostile environments. Using our notation, these equivalences include: • private input a private output • trusted input + one-bit trusted output a trusted output + one-bit trusted input • secure input a secure output.
Application of Graph-based Data Mining to Metabolic Pathways
Authors: Chang Hun You, Lawrence B. Holder, Diane J. Cook
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data that has been generated by long-term research encourages us to move our focus to a systems-level understanding of bio-systems. A biological network, containing various biomolecules and their relationships, is a fundamental way to describe bio-systems. Multi-relational data mining finds the relational patterns in both the entity attributes and relations in the data. A graph consisting of vertices and edges between these vertices is a natural data structure to represent biological networks. This paper presents a graph representation of metabolic pathways to contain all features, and describes the application of graph-based relational learning algorithms in both supervised and unsupervised scenarios. Supervised learning finds the unique substructures in a specific type of pathway, which help us understand better how pathways differ. Unsupervised learning shows hierarchical clusters that describe the common substructures in a specific type of pathway, which allow us to better understand the common features in pathways.
Prototype Visualization Tools For Multi-Experiment Performance Analysis
Authors: Roberto Araiza, Jaime Nava, Alan Taylor, Patricia Teller, David Cronk, Shirley Moore
Venue: Proceedings of the HPCMP Users Group Conference (2006)

The analysis of modern, parallelized applications, such as scientific modeling, is of interest to a variety of people within the computing community of the Department of Defense (DoD). Persons desiring insight into the performance of these large programs include application users, application programmers/developers, portfolio and center managers, and others. The analysis needed requires the examination of large data sets obtained from various performance analysis sources including, but not limited to, hardware counters, software event counters, communications event counters, and unrelated instrumentation code inserted into programs. The PCAT (PerformanCe Analysis Team) at the University of Texas-El Paso (UTEP) has developed a suite of tools consisting of a performance database access tool and four different visualization methods to aid diverse DoD users in analyzing certain performance issues associated with serial and, especially, parallel programs. The tools are written in Java and provide multiple views of different aspects of performance metrics associated with a performance database. Preliminary analysis of two different codes resulted in PCAT users identifying possible sources of performance degradation solely from examination of performance metrics, without access to the source code.
Decision feedback equalizer with two's complement computation sharing multiplication
Authors: Hunsoo Choo
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

We present an architecture of a high performance decision feedback equalizer based on a computation sharing multiplier. The computation sharing multiplier (CSHMR) uses a redundant number scheme and targets removal of computational redundancy by computation re-use. Use of CSHMR leads to high performance FIR filtering operation by re-using optimal precomputations. A decision feedback equalizer (DFE) implementation based on CSHMR in a 0.35 /spl mu/ technology shows 34% improvement in the operating speed over DFE using a Wallace tree multiplier.
Joint source channel coding of images over frequency selective channels using DCT and multicarrier BPAM
Authors: V. Kafedziski
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

A novel approach to joint source and channel coding for frequency selective channels is presented. Multicarrier modulation is used to obtain an equivalent vector channel to the frequency selective channel and utilize the linear coding procedure of Lee and Petersen (1976). The use of the block pulse amplitude transmission results in graceful degradation of the decoded signal for low channel SNR. The new procedure shows very good performance for image transmission over frequency selective channels with deep nulls in the frequency response, in the very low channel SNR region. Both the encoder and decoder are computationally very inexpensive in terms of design and implementation, compared to the digital transmission with channel optimized vector quantization. Results for transmission of a Gauss-Markov source and "Lena" image on several typical channels are presented. 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
Resilience, Production Yield and Self-Configuration in the Future Massively Defective Nanochips
Authors: Jacques Henri Collet, Piotr Zajac
Venue: Proceedings of the 13th IEEE International On-Line Testing Symposium (2007)

We describe a self-configuration methodology to tolerate defective nodes in chips organized in massively replicative architectures as those shown below in Figure 1, made up of hundreds of cores in a highly defective technology. Note that the keyword of this presentation is not configuration but self-configuration. The basic idea is that chips will become so complex that it will be unrealistic to consider diagnosing all nodes and all routes with some external equipment. Contrarily, chips should become autonomous and adaptative to preserve their resilience, and as little external interventions as possible should be involved to control the start up phase and the subsequent operation. By self-configuration we mean self-diagnosis of cores through mutual tests (both at startup and possibly at runtime), self-configuration of communications, self-shutdown of the cores which cannot take part to the processing, and ultimately, adaptative task allocation and redundant execution at runtime to cope with transient faults.
Using image classification for biomedical literature retrieval
Authors: Brigitte Mathiak, Andreas Kupfer, Tatjana Scope, Britta Stormann, Silke Eckstein
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

The aim of literature retrieval is to find significant papers on a given topic. In previous publications, we examined the use of choosing these papers based on the pictures they include. To refine this approach we seek to employ picture classification to further narrow down the number of interesting pictures presented. This can be useful, for example, when looking for the results of specific experiments. The classification can also be useful as a data cleansing step, to omit all unnecessary pictures not used as a figure. We use a method originally designed to distinguish between photos and computer-generated pictures on the web. We show that this method can not only be used to distinguish between raw data and derived representation figures, we can also reliably eliminate non-figure pictures in the document, like text pages and logos. We tested this approach on two different data sets with different topics and different non-figure problems, both with satisfactory results.
Determining Fault Tolerance of XOR-Based Erasure Codes Efficiently
Authors: Jay J. Wylie, Ram Swaminathan
Venue: Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (2007)

We propose a new fault tolerance metric for XOR-based erasure codes: the minimal erasures list (MEL). A minimal erasure is a set of erasures that leads to irrecoverable data loss and in which every erasure is necessary and sufficient for this to be so. The MEL is the enumeration of all minimal erasures. An XOR-based erasure code has an irregular structure that may permit it to tolerate faults at and beyond its Hamming distance. The MEL completely describes the fault tolerance of an XOR-based erasure code at and beyond its Hamming distance; it is therefore a useful metric for comparing the fault tolerance of such codes. We also propose an algorithm that efficiently determines the MEL of an erasure code. This algorithm uses the structure of the erasure code to efficiently determine the MEL. We show that, in practice, the number of minimal erasures for a given code is much less than the total number of sets of erasures that lead to data loss: in our empirical results for one corpus of codes, there were over 80 times fewer minimal erasures. We use the proposed algorithm to identify the most fault tolerant XOR-based erasure code for all possible systematic erasure codes with up to seven data symbols and up to seven parity symbols.
Scalable QoS Degradation Locating from End-to-End Quality of Flows on Various Routes
Authors: Masayoshi Kobayashi, Tutomu Murase
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (2007)

Methods to infer the locations of QoS degradation from end-to-end quality of flows have been proposed. These methods find the minimum set of links that covers all the bad quality flows and infer the links as the locations of QoS degradation. Since the computational complexity to find the minimum set cover is high, these methods have a difficulty in the scalability for the large-scale networks. In this paper, we propose a scalable locating method in which a network is (logically) divided into subnetworks. Bad quality flows going across the sub-networks create the dependency among sub-networks in inferring. Resolving this dependency, our proposed method enables each sub-network to run inferring algorithm independently in parallel. Simulation results show that the proposed method can reduce the inferring time significantly while the accuracy of inferring is not degraded.
A Comparison of Active-Contour Models Based on Blurring and on Marginalization
Authors: A. E. C. Pece
Venue: Proceedings of the 14th International Conference on Computer Communications and Networks (2005)

Many different active-contour models have been proposed over the last 20 years, but very few comparisons between them have been carried out. Further, most of these comparisons have been either exclusively theoretical or exclusively experimental. This paper presents a combined theoretical and experimental comparison between two contour models. The models are put into a common theoretical framework and performance comparisons are carried out on a vehicle tracking task in the PETS test sequences. Using a Condensation tracker helps to find the few frames where either model fails to provide a good fit to the image. The results show that (a) neither model has a definitive advantage over the other, and (b) Kalman filtering might actually be more effective than particle filtering for both models.