ppxscal/embedding_network huggingface dataset:
Keyword Extraction from Documents Using a Neural Network Model
Authors: Taeho Jo, Malrey Lee, Thomas M. Gatton
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

A document surrogate is usually represented in a list of words. Because not all words in a document reflect its content, it is necessary to select important words from the document that relate to its content. Such important words are called keywords and are selected with a particular equation based on Term Frequency (TF) and Inverted Document Frequency (IDF). Additionally, the position of each word in the document and the inclusion of the word in the title should be considered to select keywords among words contained in the text. The equation based on these factors gets too complicated to be applied to the selection of keywords. This paper proposes a neural network back propagation model in which these factors are used as the features and feature vectors are generated to select keywords. This paper will show that the proposed neural network backpropagation approach outperforms the equation in distinguishing keywords.
ERP Nonword Rhyming Effects in Children and Adults
Authors: Donna Coch, Giordana Grossi, Wendy Skendzel, Helen Neville
Venue: Journal of Cognitive Neuroscience (2005)

In a simple prime&ndash;target auditory rhyming event-related potential (ERP) paradigm with adults and 6-, 7-, and 8-year-old children, nonword stimuli (e.g., nin&ndash;rin, ked&ndash;voo) were used to investigate neurocognitive systems involved in rhyming and their development across the early school years. Even absent semantic content, the typical CNV to primes and late rhyming effect (RE) to targets were evident in all age groups. The RE consisted of a more negative response to nonrhyming targets as compared to rhyming targets over posterior sites, with a reversal of this pattern at lateral anterior sites. The hypothesis that the CNV indexes phonological memory processes was not well supported by correlation analyses conducted with the ERP measures and scores on standardized behavioral tests. However, the onset of the rhyming effect was later in those scoring lower on phonological awareness measures.
An OS-level Framework for Providing Application-Aware Reliability
Authors: Long Wang, Zbigniew Kalbarczyk, Weining Gu, Ravishankar K. Iyer
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

The paper describes the reliability microkernel framework (RMK), a loadable kernel module for providing application-aware reliability and dynamically configuring reliability mechanisms installed in RMK. The RMK prototype is implemented in Linux and supports detection of application/OS failures and transparent application checkpointing. Experiment results show that the OS hang detection, which exploits characteristics of application and system behavior, can achieve high coverage (100% in our experiments) and low false positive rate. Moreover, the performance overhead is negligible because instruction counting is performed in hardware.
A software architecture for physical layer wireless network emulation
Authors: Glenn Judd, Peter Steenkiste
Venue: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation characterization (2006)

Despite their widespread deployment, many aspects of wireless network performance are poorly understood, and there is great room from improvement in wireless network reliability and performance. A key obstacle to understanding and improving wireless networks has been the lack of a realistic yet flexible experimental methodology. Physical layer wireless network emulation promises to achieve much of the flexibility of wireless simulators while maintaining much of the realism of real wireless networks. We have developed a software architecture that tames the complexity of physical layer wireless network emulation, and presents users with a powerful yet ease-to-use interface. We present several case studies showing how this software architecture allows complex wireless experiments to be conducted in an efficient manner while still enabling novice users to quickly run simple experiments.
Modulation and demodulation techniques for underwater acoustic communications
Authors: John G. Proakis
Venue: Proceedings of the 1st ACM international workshop on Underwater networks (2006)

This paper is focused on the characteristics of underwater acoustic communication channels and their implications on the design of bandwidth efficient modulation and demodulation techniques. Both noncoherent and phase coherent modulation and demodulation techniques are considered, and their performance, bandwidth efficiency and implementation complexity are compared.Single carrier and multicarrier (OFDM) modulation and demodulation techniques are also considered. It is illustrated that the performance of high data rate single carrier systems is severely impacted by intersymbol interference (ISI) due to channel dispersion and that powerful equalization algorithms are required to reduce the performance loss caused by ISI. The use of coding in such single carrier systems makes it possible to perform turbo equalization in order to achieve further performance gains. Multicarrier (OFDM) modulation may be used to eliminate the need for high complexity equalizers in channels where the time variations are sufficiently slow relative to the symbol rate carried by each of the subcarriers in the multicarrier system.Further increases in bandwidth efficiency are possible through spatial multiplexing. To achieve this objective, recent work on underwater acoustic communications has focused on MIMO techniques to increase the data rate and improve performance through signal diversity. This work on MIMO will be discussed.As a final topic in this paper, we consider multiple access techniques suitable for use in underwater acoustic networks. The suitability of FDMA, TDMA and CDMA is assessed in view of the characteristics of underwater acoustic channels.
Simulation as support for production planning in small and medium enterprise: a case study
Authors: Roberto Mosca, Lucia Cassettari, Roberto Revetria, Gianluca Magro
Venue: Proceedings of the 37th conference on Winter simulation (2005)

The proposed application is related to an Italian small factory that produces, assembles, and sells mechanical components for awnings. In such factories BPR (Business Process Engineering) usually takes place without the support of Modeling & Simulation although such methodologies have proved to be very effective and helpful. Main reasons for that have to be investigated in the high costs usually associated with a simulation study, especially for data collection, model building and model validation. In order to avoid this problem a general-purpose simulation framework was designed enabling self-build according to production process information stored in a relational database. Moreover, the simulation model was used in conjunction with a statistical analysis tool in order to build the relationship among selected parameters and the proposed objective function by mean of Response Surface Methodology and 2nd order regressions meta-models. Authors applied the proposed schema to several industrial applications obtaining interesting results.
A Computational Role for Dopamine Delivery in Human Decision-Making
Authors: David M. Egelman, Christophe Person, P. Read Montague
Venue: Journal of Cognitive Neuroscience (1998)

Recent work suggests that fluctuations in dopamine delivery at target structures represent an evaluation of future events that can be used to direct learning and decision-making. To examine the behavioral consequences of this interpretation, we gave simple decision-making tasks to 66 human subjects and to a network based on a predictive model of mesencephalic dopamine systems. The human subjects displayed behavior similar to the network behavior in terms of choice allocation and the character of deliberation times. The agree ment between human and model performances suggests a direct relationship between biases in human decision strategies and fluctuating dopamine delivery. We also show that the model offers a new interpretation of deficits that result when dopamine levels are increased or decreased through disease or pharmacological interventions. The bottom-up approach presented here also suggests that a variety of behavioral strategies may result from the expression of relatively simple neural mechanisms in different behavioral contexts.
Computing by commuting
Authors: Juhani Karhumäki, Michal Kunc, Alexander Okhotin
Venue: Theoretical Computer Science (2006)

We consider the power of the following rewriting: given a finite or regular set X of words and an initial word w, apply iteratively the operation which deletes a word from X from one of the ends of w and simultaneously catenates another word from X to the opposite end of w. We show that if the deletion is always done at the beginning and the catenation at the end, and the choice of a word to be catenated does not depend on the word erased, then the generated language is always regular, though the derivability relation is not, in general, rational. If the deletion and the catenation are done arbitrarily at the opposite ends, the language need not be regular. If the catenation is done at the same end as the deletion, the relation of derivability is rational even if the catenated word can depend on the word erased.
Impact of Radio Irregularities on Topology Tradeoffs of WSNs
Authors: G. De Marco, T. Yang, L. Barolli
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

The radio model usually used in most of studies on wireless sensor networks is spherical. This means that the received power at a certain distance is the same in all directions. Every radio engineer knows that this is not the case encountered in real hardware. Here, we show that the analysis of such a network by simulation is not trivial when one uses more realistic radio models. We emphasise this problem by comparing the impact of realistic simulations on the study of the infrastructure trade-offs of sensors networks. As expected, simulations confirm that more advanced simulation techniques are required in order to take into account wireless channel models and to bound the simulation time as well.
Rate Control Scheme Based on Cauchy R-D Optimization Model for H.264/AVC under Low Delay Constraint
Authors: N. Eiamjumrus, S. Aramvith
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Base on the observation that Cauchy distribution provides an accurate estimates of rate and distortion characteristics of video sequences. In this paper, we propose to use a new rate control scheme based on Cauchy R-D optimization model for bit allocation of H.264 for low delay constraint. One solution which has been proposed in this paper use the Lagrange Multiplier technique as the cost function to find rate and distortion model subject to target bit rate constraint resulting in optimum of quantization step sizes. Model parameters are estimated using linear regression analysis. We propose a simple rate control scheme that achieves for new Cauchy R-D model in basic unit layer under low delay constraint. The target bits for each frame are determined according to their buffer status, combined with number of bits use in the previous frame. The technique proposed has been implemented on H.264 video coder. Experimental showed that the proposed can be achieves an improvement of average PSNR with smooth video quality and less frame skipping compared to the JM8.6 rate control.
The use of hints by human and computer tutors: the consequences of the tutoring protocol
Authors: Gregory Hume, Joel Michael, Allen Rovick, Martha Evens
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

Our study of two expert human tutors reveals that, while they employ many tactics, they (virtually) always try hinting to remedy problems. Hints are occasionally mentioned in the Intelligent Tutoring System (ITS) literature but there has been no systematic study of this phenomenon. Our ITS, CIRCSIM-Tutor (CST), is designed to assist first year medical students to learn to reason about blood pressure regulation. Our study of human tutoring sessions is the basis for the design of CST. Our protocol (both human and computer tutoring sessions) begins with an explanation of a problem (a disturbance to the circulatory system). The student then makes predictions about the ensuing qualitative causal effects. This is followed by an interactive dialogue. This protocol allows for the student to ask questions, although this rarely happens. Other ITSs and automated training systems require that the student work on a problem and explicitly ask for help. The ITS literature has examples of how other systems differ in tutoring protocol, knowledge domain and student population. How do these differences affect the use of hints?
Evaluating the importance of virtual memory for Java
Authors: Y. Becerra, T. Cortes, J. Garcia, N. Navarro
Venue: Proceedings of the 2003 IEEE International Symposium on Performance Analysis of Systems and Software (2003)

The Java language has rapidly become widespread and it is being used to implement a broad range of applications, including applications with high resource requirements. For this reason, it is important to evaluate the suitability of the Java environment to execute such applications. This paper presents an evaluation of the effects of memory management in the context of memory intensive Java applications executed on a virtual memory system. The goal of this work is to detect the most critical memory management issues for Java applications performance. We measure the overhead that each memory management task adds to the application execution, and we determine which part of this overhead is due to the memory access pattern of the application and which part is due to the interaction between the different memory management tasks.
Quasi-monte carlo simulation in a LIBOR market model
Authors: Xuefeng Jiang, John R. Birge
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Quasi-Monte Carlo (QMC) methods have been extensively applied to pricing complex derivatives. We apply quasi-Monte Carlo simulation to LIBOR market models based on the Brace-Gatarek-Musiela/Jamshidian framework. We price exotic interest-rate derivatives and compare the results using pseudo random sequences and different low discrepancy sequences.
Moral intensity and ethical decision-making: a contextual extension
Authors: Tim Goles, Gregory B. White, Nicole Beebe, Carlos A. Dorantes, Barbara Hewitt
Venue: ACM SIGMIS Database (2006)

This paper explores the role of an individual's perception of situation-specific issues on decision-making in ethical situations. It does so by examining the influence of moral intensity on a person's perceptions of an ethical problem, and subsequent intentions. Moral intensity (Jones, 1991) is an issue-contingent model of ethical decision-making based on the supposition that situations vary in terms of the moral imperative present in that situation. An individual's decision is guided by his or her assessment of six different components that collectively comprise the moral intensity of the situation. The relationship between the components of moral intensity and the decision-making process is tested through the use of scenarios that present IS-related ethical situations. The results indicate that moral intensity plays a significant role in shaping the perceptions and intentions of individuals faced with IS-related ethical situations. The conclusion drawn from this is that, consistent with prior research, the decision-making process is influenced by an individual's perception of situation-specific issues; that is, the moral intensity of the situation.
Estimation of few light sources from environment maps for fast realistic rendering
Authors: Naveen Dachuri, Seung Man Kim, Kwan H. Lee
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

In recent times, images of real world are being widely used for seamless integration of virtual objects into real world scenes. Images of real world, commonly know as environment maps, acts as source of natural lighting i.e. are used as representation of distant illumination at a point. In Image Based Lighting (IBL) technique each pixel of a high dynamic range image (HDRI) is used as a source of real world illumination. Although the method produces realistic rendering results but requires high computation time. One way to fasten rendering process is to use few light sources instead of thousands of light sources in HDRI (environment map). In this paper we present a method to estimate few light samples from environment map that closely mimics the actual natural lighting of a real world. The estimated light parameters could be used in interactive and augmented reality applications, where computation time is a vital factor.
Multiple Face Model of Hybrid Fourier Feature for Large Face Image Set
Authors: Wonjun Hwang, Gyutae Park, Jongha Lee, Seok-Cheol Kee
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

The face recognition system based on the only single classifier considering the restricted information can not guarantee the generality and superiority of performances in a real situation. To challenge such problems, we propose the hybrid Fourier features extracted from different frequency bands and multiple face models. The hybrid Fourier feature comprises three different Fourier domains; merged real and imaginary components, Fourier spectrum and phase angle. When deriving Fourier features from three Fourier domains, we define three different frequency bandwidths, so that additional complementary features can be obtained. After this, they are individually classified by Linear Discriminant Analysis. This approach makes possible analyzing a face image from the various viewpoints to recognize identities. Moreover, we propose multiple face models based on different eye positions with a same image size, and it contributes to increasing the performance of the proposed system. We evaluated this proposed system using the Face Recognition Grand Challenge (FRGC) experimental protocols known as the largest data sets available. Experimental results on FRGC version 2.0 data sets has proven that the proposed method shows better verification rates than the baseline of FRGC on 2D frontal face images under various situations such as illumination changes, expression changes, and time elapses.
New Dynamic Load Balancing for Parallel Modified PrefixSpan
Authors: Makoto Takaki, Keiichi Tamura, Toshihide Sutou, Hajime Kitakami
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

A motif that is a featured pattern is discovered from the frequent patterns in amino acid sequences. To extract frequent patterns at high speed, a parallel Modified PrefixSpan with a master-worker paradigm was proposed. However, a master-worker paradigm has a performance limitation when the number of PCs increases. To address this disadvantage, the distributed worker paradigm is adapted to the parallel Modified PrefixSpan. In order to obtain an effective speed-up ratio, we propose a new dynamic load balancing. The characteristics of dynamic load balancing are a smallgrain task and a Cache-based Random Steal schema. When a 100-scale PC cluster was used, the experimental results showed a speed-up ratio of 95 times.
Color Vision and the Four-Color-Map Problem
Authors: Dale Purves, Beau Lotto, Thomas Polger
Venue: Journal of Cognitive Neuroscience (2000)

Four different colors are needed to make maps that avoid adjacent countries of the same color. Because the retinal image is two dimensional, like a map, four dimensions of chromatic experience would also be needed to optimally distinguish regions returning spectrally different light to the eye. We therefore suggest that the organization of human color vision according to four-color classes (reds, greens, blues, and yellows) has arisen as a solution to this logical requirement in topology.
Dynamic time-warp compensation for correlation of long sequences
Authors: R. Prandolini, M. Moody
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Dynamic time-warping of direct-sequence spread-spectrum causes a deterioration in the process gain when time-linear correlation is applied. Applications with channels that suffer this effect are moving platforms such as to airborne communications, acoustic communications, and tape recorders. Of these, the tape recorder has the most severe time-warp. This paper describes a low powered PN-sequence which is added to the audio, such that the audible quality is not impaired. This is used for authentication of the tape recording. Tape speed errors from wow and flutter cause time based errors and a loss of the detection process gain. A technique for recovering the process gain and detecting the PN-sequence from this channel using a dynamic programming algorithm is presented.
Landmark-Based Geodesic Computation for Heuristically Driven Path Planning
Authors: Gabriel Peyre, Laurent D. Cohen
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

This paper presents a new method to quickly extract geodesic paths on images and 3D meshes. We use a heuristic to drive the front propagation procedure of the classical Fast Marching. This results in a modification of the Fast Marching algorithm that is similar to the A algorithm used in artificial intelligence. In order to find very quickly geodesic paths between any given couples of points, we advocate for the initial computation of distance maps to a set of landmark points and make use of these distance maps through a relevant heuristic. We show that our method brings a large speed up for large scale applications that require the extraction of geodesics on images and 3D meshes. We introduce two distortion metrics in order to find an optimal seeding of landmark points for the targeted applications. We also propose a compression scheme to reduce the memory requirement without impacting the quality of the extracted paths.
A new least-squares approach to differintegration modeling
Authors: Manuel D. Ortigueira, António J. Serralheiro
Venue: Signal Processing (2006)

In this paper a new least-squares (LS) approach is used to model the discrete-time fractional differintegrator. This approach is based on a mismatch error between the required response and the one obtained by the difference equation defining the auto-regressive, moving-average (ARMA) model. In minimizing the error power we obtain a set of suitable normal equations that allow us to obtain the ARMA parameters. This new LS is then applied to the same examples as in [R.S. Barbosa, J.A. Tenreiro Machado, I.M. Ferreira, Least-squares design of digital fractional-order operators, FDA'2004 First IFAC Workshop on Fractional Differentiation and Its Applications, Bordeaux, France, July 19-21, 2004, P. Ostalczyk, Fundamental properties of the fractional-order discrete-time integrator, Signal Processing 83 (2003) 2367-2376] so performance comparisons can be drawn. Simulation results show that both magnitude frequency responses are essentially identical. Concerning the modeling stability, both algorithms present similar limitations, although for different ARMA model orders.