ppxscal/embedding_network huggingface dataset:
Symmetry groups of Bailey's transformations for 10φ9-series
Authors: S. Lievens, J. Van der Jeugt
Venue: Journal of Computational and Applied Mathematics (2007)

Although most of the symmetry groups or ''invariance groups'' associated with two term transformations between (basic) hypergeometric series have been studied and identified, this is not the case for the most general transformation formulae in the theory of basic hypergeometric series, namely Bailey's transformations for @f910-series. First, we show that the invariance group for both Bailey's two term transformations for terminating @f910-series and Bailey's four term transformations for non-terminating @f910-series (rewritten as a two term transformation of a so-called @F-series) is isomorphic to the Weyl group of type E"6. We continue our recent research concerning the group structure underlying three term transformations [S. Lievens, J. Van der Jeugt, Invariance groups of three term transformations for basic hypergeometric series, J. Comput. Appl. Math. 197 (2006) 1-14] and demonstrate that the group associated with a three term transformation between these @F-series, each admitting Bailey's two term transformation, is the Weyl group of type E"7. We do this by giving a description of the root system of type E"7 that allows to find a transformation between equivalent three term identities in an easy way. A computation shows that there are five, essentially different, three term transformations between these @F-series; we give an explicit form of each of these five transformations in an elegant way. To our knowledge only one of these transformations has appeared in the literature.
Extracting personal characteristics from human movement
Authors: J. Hoshino
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

We propose a new method for extracting personal characteristics from 3D body movement. We introduce the eigen action space to represent the personal characteristics. First, we estimate the average action from a set of 3D pose parameters from different people. Then we create the eigen action space from the covariance matrices of 3D pose parameters using the KL transform. Because the eigen action space consists of orthogonal base vectors, the 3D pose parameters of a person are represented as a point. A similarity measure is calculated from points in the action eigen space. Also, actions with new personal characteristics can be reconstructed by sampling new points in the eigen action space.
LOBOS: (linux OS boots OS) booting a kernel in 32-bit mode
Authors: Ron Minnich
Venue: Proceedings of the 4th annual Linux Showcase & Conference - Volume 4 (2000)

LOBOS (Linux Os Boots OS) is a system call that allows a running Linux kernel to boot a new kernel, without leaving 32-bit protected mode and, in particular, without using the BIOS in any way. This capability in turn allows Linux to be used as a network bootstrap program and even as a BIOS, both of which we are working on now. In this paper we discuss how LOBOS works, how we use it, and how LOBOS makes Linux usable as a BIOS, replacing the proprietary PC BIOSes we have today. LOBOS has been used by two other groups as a reference implementation for their Linux-boots-Linux system calls. One of these other implementations, bootimg, may become a part of the 2.4 kernel.
Performance Enhancement of Header Compression over Asymmetric Wireless Links Based on the Objective Speech Quality Measurement
Authors: Norihiro Fukumoto, Hideaki Yamada
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet (2007)

A variety of conversational multimedia services have been developed and provided for a FMC (Fixed Mobile Convergence) environment, which contains a variety of wireless networks, such as 1x EV-DO (1x EVolution Data Only), WiMAX (Worldwide Interoperability for Microwave Access), WiFi (Wireless Fidelity) and combinations. The bandwidths of several wireless networks are asymmetric and restricted. For example, for the asymmetric link, 1x EV-DO specifies the peak rates for downlink and uplink as 2.4Mbit/s and 153Kbit/s. A header compression scheme for the transmitted packets of conversational multimedia signals is an effective solution for these scarce links, especially in the IPv6 environment. However, ways to improve the performance of the header compression scheme have not been thoroughly evaluated quantitatively considering the quality of conversational multimedia services over the asymmetric wireless links where the transmission characteristics of the up and down links are quite different. This paper presents the results of a study that examined ways to improve the performance of the header compression scheme based on control of the header compression parameters considering speech quality over the asymmetric wireless link. The paper also presents experimental verifications of the efficiency of our proposal using a practical implementation.
A Concurrent Multi Target Tracker: Benchmarking and Portability
Authors: Salim Hariri, Rajesh Yadav, Balaji Thiagarajan, Sung-Yong Park, Mahesh Subramanyan, Rajashekar Reddy, G. C. Fox
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

With the current advances in computing and network technology and software, the gap between parallel and distributed computing environment is gradually becoming narrower. Consequently, parallel programs run on parallel as well as distributed systems. However, programming and porting complex applications to such environment is challenging task and not well understood. In this paper, we use a concurrent multi target tracker as a running example to analyze and evaluate performance of two different parallel implementations on parallel and distributed systems. We have benchmarked both these implementations on different architectures that vary from a network of worksta¬ tions{SUN, IBM RS6000) to parallel computers (CM5, iPSC 860) using different parallel/distributed message passing tools{PVM, p4, EXPRESS).
Frame discrimination training for HMMs for large vocabulary speech recognition
Authors: D. Povey
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

This paper describes the application of a discriminative HMM parameter estimation technique called frame discrimination (FD), to medium and large vocabulary continuous speech recognition. Previous work has shown that FD training can give better results than maximum mutual information (MMI) training for small tasks. The use of FD for much larger tasks required the development of a technique to be able to rapidly find the most likely set of Gaussians for each frame in the system. Experiments on the resource management and North American business tasks show that FD training can give comparable improvements to MMI, but is less computationally intensive.
A Bloch Decomposition-Based Split-Step Pseudospectral Method for Quantum Dynamics with Periodic Potentials
Authors: Zhongyi Huang, Shi Jin, Peter A. Markowich, Christof Sparber
Venue: SIAM Journal on Scientific Computing (2007)

We present a new numerical method for accurate computations of solutions to (linear) one-dimensional Schro&uml;dinger equations with periodic potentials. This is a prominent model in solid state physics where we also allow for perturbations by nonperiodic potentials describing external electric fields. Our approach is based on the classical Bloch decomposition method, which allows us to diagonalize the periodic part of the Hamiltonian operator. Hence, the dominant effects from dispersion and periodic lattice potential are computed together, while the nonperiodic potential acts only as a perturbation. Because the split-step communicator error between the periodic and nonperiodic parts is relatively small, the step size can be chosen substantially larger than for the traditional splitting of the dispersion and potential operators. Indeed it is shown by the given examples that our method is unconditionally stable and more efficient than the traditional split-step pseudospectral schemes. To this end a particular focus is on the semiclassical regime, where the new algorithm naturally incorporates the adiabatic splitting of slow and fast degrees of freedom.
Algorithms for discovering communities in complex networks
Authors: Narsingh Deo
Venue:  (2006)

It has been observed that real-world random networks like the WWW, Internet, social networks, citation networks, etc., organize themselves into closely-knit groups that are locally dense and globally sparse . These closely-knit groups are termed communities. Nodes within a community are similar in some aspect. For example in a WWW network, communities might consist of web pages that share similar contents. Mining these communities facilitates better understanding of their evolution and topology, and is of great theoretical and commercial significance. Community related research has focused on two main problems: community discovery and community identification. Community discovery is the problem of extracting all the communities in a given network, whereas community identification is the problem of identifying the community, to which, a given set of nodes belong. We make a comparative study of various existing community-discovery algorithms. We then propose a new algorithm based on bibliographic metrics, which addresses the drawbacks in existing approaches. Bibliographic metrics are used to study similarities between publications in a citation network. Our algorithm classifies nodes in the network based on the similarity of their neighborhoods. One of the drawbacks of the current community-discovery algorithms is their computational complexity. These algorithms do not scale up to the enormous size of the real-world networks. We propose a hash-table-based technique that helps us compute the bibliometric similarity between nodes in O( m &Delta;) time. Here m is the number of edges in the graph and &Delta;, the largest degree. Next, we investigate different centrality metrics. Centrality metrics are used to portray the importance of a node in the network. We propose an algorithm that utilizes centrality metrics of the nodes to compute the importance of the edges in the network. Removal of the edges in ascending order of their importance breaks the network into components, each of which represent a community. We compare the performance of the algorithm on synthetic networks with a known community structure using several centrality metrics. Performance was measured as the percentage of nodes that were correctly classified. As an illustration, we model the ucf.edu domain as a web graph and analyze the changes in its properties like densification power law, edge density, degree distribution, diameter, etc., over a five-year period. Our results show super-linear growth in the number of edges with time. We observe (and explain) that despite the increase in average degree of the nodes, the edge density decreases with time.
Random geometric graphs: an algorithmic perspective
Authors: Judea Pearl, Deborah Estrin
Venue:  (2006)

A random geometric graph G (n, r) is a graph resulting from placing n points uniformly at random on the unit square (or on the unit disk) and connecting two points iff their Euclidean distance is at most the radius r(n). Recently, this class of random graphs has gained relevance as a natural model for wireless ad-hoc and sensor networks. Investigating properties of these graphs can unearth properties of the real-life systems they model and allow for the design of efficient algorithms. In this work, we study properties of random geometric graphs motivated by challenges encounter in sensor networks applications. Sensor networks are constructed from a large number of low-cost, low-power sensors equipped with wireless communication and limited processing capabilities. These devices are expected to be embedded densely into the environment and cooperate to achieve high level tasks. In many cases, the network created by these devices is subject to dramatic structural changes due to failures, node mobility and other factors. Motivated by the disadvantage entailed by topology driven algorithms (e.g. the need to maintain data structures and to execute expensive recovery mechanisms), we investigate algorithms that require no knowledge of network topology, in particular algorithms based on random walks. The investigation we carry out in this dissertation attempts to asses the efficiency of random-walk-based algorithms. Surprisingly we show that despite their simplicity, random-walk-based algorithms can be competitive with optimal topology driven strategies for certain tasks. In particular, we analyze three properties of random walks on these graphs, the mixing time, the cover time and the partial cover time that are essential to determining the efficiency of this approach for sensor network tasks. We also investigated another property of random geometric graphs which has implication for routing and topological control in sensor networks. The goal here is to construct a special subgraph, the Restricted Delaunay Graph, that permits efficient routing, based only on local information. We bound the number of messages needed for this task in these networks and presents a novel algorithm, based on the graph properties, that is more efficient than previous ones. We offer a new extension of random geometric graphs called random distance graphs. to explain some interesting similarities between random geometric graphs and the familiar model of Bernoulli random graphs1. Interestingly while, neither random geometric graphs nor Bernoulli random graphs are suitable to model social networks, a typical case of random distance graphs can captures important properties of social networks. These properties, known as "Small World", includes small average path length and high clustering have been the distinctive mark of many natural networks. 1A Bernoulli random graph (a.k.a. Erdo&huml;s-R&eacute;nyi graph) B (n, p) is a random graph with n nodes in which each edge is chosen independently at random with an edge probability p(n).
DAW: A Distributed Antiworm System
Authors: Shigang Chen, Yong Tang
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

A worm automatically replicates itself across networks and may infect millions of servers in a short period of time. It is conceivable that the cyberterrorists may use a widespread worm to cause major disruption to the Internet economy. Much recent research concentrates on propagation models and early warning, but the defense against worms is largely an open problem. We propose a distributed antiworm architecture (DAW) that automatically slows down or even halts the worm propagation within an Internet service provider (ISP) network. New defense techniques are developed based on the behavioral difference between normal hosts and worm-infected hosts. Particularly, a worm-infected host has a much higher connection-failure rate when it randomly scans the Internet. This property allows DAW to set the worms apart from the normal hosts. We propose a temporal rate-limit algorithm and a spatial rate-limit algorithm, which makes the speed of worm propagation configurable by the parameters of the defense system. The effectiveness of the new techniques is evaluated analytically and by simulations.
Interview with Alan Ganek and Mark Potts
Authors: Dejan Milojicic
Venue: IEEE Internet Computing (2007)

Trend Wars host, Dejan Milojicic, recently discussed service management with Alan Ganek, the chief technology officer (CTO) of IBM Tivoli, and Mark Potts, Hewlett-Packard (HP) Fellow and chief technologist of HP Software.
Voilà, Your Network is IPv6 Enabled!
Authors: Rita Puzmanova
Venue: IEEE Distributed Systems Online (2007)

A review of "Deploying IPv6 Networks" by Ciprian P. Popoviciu, Eric Levy-Abegnoli, and Patrick Grossetete
Minimum classification error training for a small amount of data enhanced by vector-field-smoothed Bayesian learning
Authors: J. Takahashi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

This paper describes an efficient method of attaining the highest level of recognition performance yet achieved in minimum classification error (MCE) training for a small amount of data. This method combines MCE and vector-field-smoothed Bayesian learning called MAP/VFS. In the proposed method, the training capability of MCE in robust acoustic modeling can be significantly enhanced with MAP/VFS. In the method, MCE training is performed using an initial model trained through MAP/VFS. The same data are used in both training. For speaker adaptation using 50-word training data, the error reduction rate drastically rises to 47% compared with 16.5% when using only MCE. This high rate, in which 39% is due to MAP, an additional 4% is due to VFS, and a further improvement of 4% is due to MCE, can be attained by enhancing MCE training capability with MAP/VFS.
On-chip testing of MEMS using pseudo-random test sequences
Authors: L. Rufer, S. Mir, E. Simeu, C. Domingues
Venue: Proceedings of the Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (2003)

This paper presents a method for an on-chip fast and accurate broadband determination of MEMS behaviour. This technique is based on impulse response (IR) evaluation using pseudo-random Maximum-Length Sequences (MLS). The MLS approach is capable of providing vastly superior dynamic range in comparison to the straightforward technique using an impulse excitation and is thus an optimal solution for measurements in noisy environments and for low-power test signals. The use of a pseudo-random sequence for testing makes the practical on-chip implementation very efficient in terms of the extra hardware required for on-chip testing. We will exemplify this technique for the case of MEMS structures such as cantilevers and bridges, by determining their mechanical and thermal behaviour using just electrical tests.
MON: on-demand overlays for distributed system management
Authors: Jin Liang, Steven Y. Ko, Indranil Gupta, Klara Nahrstedt
Venue: Proceedings of the 2nd conference on Real, Large Distributed Systems - Volume 2 (2005)

This paper presents the management overlay network (MON) system that we are building and running on the PlanetLab testbed. MON is a distributed system designed to facilitate the management of large distributed applications. Toward this goal, MON builds on-demand overlay structures that allow users to execute instant management commands, such as query the current status of the application, or push software updates to all the nodes. The on-demand approach enables MON to be light-weight, requiring minimum amount of resources when no commands are executed. It also frees MON from complex failure repair mechanisms, since no overlay structure is maintained for a prolonged time. MON is currently running on more than 300 nodes on the Planet-Lab. Our initial experiments on the PlanetLab show that MON has good performance, both in terms of command response time and achieved bandwidth for software push.
Adaptive space-time DFE (AST-DFE) receiver for GSM/DCS-1800 mobile communication system with spatial diversity
Authors: M. A. Lagunas
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

We consider using smart antenna array technique for GSM/DCS-1800 mobile communication system to combat fast dispersive fading channel and cochannel interference (CCI). By exploiting Laurent's (1986) AMP (amplitude modulation pulse) representation for GMSK signal, we first construct a linearized SI4O (single-input and four-output) model for a single-antenna GMSK receiver in terms of the de-rotation operation and T/2 fractionally sampling. With this linear model and spatial diversity, we then develop a so-called adaptive space-time decision-feedback-equalizer (AST-DFE) receiver, which is much simpler than the MLSE-based receiver. Adapted by the RLS algorithm, this receiver can cope with time-varying channels with high fading rate. Besides, to increase the capacity of GSM system, the receiver can be easily upgraded to multiuser detection operation. With computer simulations, we investigate the above AST-DFE receivers under different GSM channel models. It is demonstrated that by using the antenna array for reception, the space-time processing techniques can significantly improve the system performance as well as system capacity, as compared to the receiver with only a single antenna.
Computational Techniques for Accompaniment and Measuring of Otology Pathologies
Authors: V. Heck Junior, A. v. Wangenheim, D. D. Abdala, E. Comunello, S. S. Costa, C. C. Dornelles
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

The following article presents a computational methodology to assist the assessment of tympanic pathologies, particularly chronic otitis media, based on digital otoscopic images. A computational system which implements the methodology is described. This approach does not impose additional effort to the acquisition protocol and diagnosis of tympanic pathologies. In preliminary tests, it has shown precision and easiness of use. The presented methodology and system were tested by the Otitis Media Center of Brazil (Com.Br) with a case base of 660 patients, resulting in 1320 bilateral tympanic images.
Discourse generation using utility-trained coherence models
Authors: Radu Soricut, Daniel Marcu
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

We describe a generic framework for integrating various stochastic models of discourse coherence in a manner that takes advantage of their individual strengths. An integral part of this framework are algorithms for searching and training these stochastic coherence models. We evaluate the performance of our models and algorithms and show empirically that utility-trained log-linear coherence models outperform each of the individual coherence models considered.
The performance of Bluetooth system in the presence of WLAN interference in an office environment
Authors: O. Karjalainen
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 02 (2002)

This paper presents measured performance of the Bluetooth link in a presence of WLAN interference in an office environment. The investigation was done using three different measurement scenarios. In the first scenario the corresponding devices were connected to the same computer. In the second one the receivers were separated and finally the transmitters were separated from each other as well. The results show that with a little planning both systems can truly coexist and the experienced performance degradations can be kept in a reasonable level.
Ultra Low Voltage Operation with Bootstrap Scheme for Single Power Supply SOI-SRAM
Authors: Masaaki Iijima, Masayuki Kitamura, Masahiro Numa, Akira Tada, Takashi Ipposhi
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

This paper presents an SOI-SRAM design employing a bootstrap scheme for ultra low voltage operation. The Active Body-biasing Control (ABC) with PD-SOI is a key idea to enhance the boosting effect owing to a strong capacitive coupling. Our ABC-bootstrap scheme enables boosting the word line (WL) voltage higher than the supply voltage in short transition time without dual power supply rails. Simulation results have shown improvement in both the access time and operation at ultra low supply voltage less than 0.5V.