ppxscal/embedding_network huggingface dataset:
On vertex-vertex systems and their use in geometric and biological modelling
Authors: Colin Smith
Venue:  (2006)

In the areas of geometry and biology, there are a number of modelling problems that require the creation and manipulation of discrete surfaces that behave dynamically. For example, in geometric modelling there are surface subdivision algorithms that require the repeated insertion of vertices into a polygon mesh. In biological modelling there is the question of modelling growing surfaces, such as a growing flower or a growing tissue of cells. In these cases, there is the open question of how to model dynamical systems with a dynamical structure of a 2-manifold topology, discrete surfaces that have components that change in character, connectivity and number over time. However, the selection of available tools for modelling dynamical surfaces is limited. There have been some proposed solutions for limited cases, such as cell systems for modelling cells. But there is still a need for a methodology and tools for dealing with dynamical surfaces in general. In this dissertation, I present a methodology for modelling dynamical systems with a dynamical structure of a 2-manifold topology. This methodology is comprised of the vertex-vertex data structure and algebra and is implemented in the vertex-vertex software environment. I also demonstrate its application with examples in the domains of geometric and biological modelling.
Personalized Communication Avoiding Node Contention on Distributed Memory Systems
Authors: Sanjay Ranka, Jhy-Chun Wang, Manoj Kumar
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 01 (1993)

In this paper, we present several algorithms for per forming all-to-many personalized communication on distributed memory parallel machines. Each proces sor sends a different message (of potentially different size) to a subset of all the processors involved in the collective communication. The algorithms are based on decomposing the communication matrix into a set of partial permutations. We study the effectiveness of our algorithms both from the view of static scheduling as well as runtime scheduling.
Broadband eigenvector methods for towed array shape estimation with a single source
Authors: J. J. Smith
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

This paper investigates two techniques for extending the narrowband (NB) eigenvector method for towed array shape estimation to process broadband sources. These techniques are the weighted incoherent broadband processor (WIB) and the weighted quasi-coherent broadband processor (WQB). It is demonstrated, both analytically and via computer simulations, that the two broadband processors can dramatically improve the bias and variance of the receiver position estimates, compared to the NB technique. The results of computer simulations also demonstrate that the WQB method has a lower SNR threshold than the NB and incoherent methods.
Server Autonomic Grouping Process for the Wireless Network Environment
Authors: John Tsiligaridis, Raj Acharya
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

The problem of server performance in a contemporary, rapidly developed and multi-discipline environment is examined. Multiple requests in a very short time increase the number of connections and push the server to the limit. For autonomous server operations many of the offered services need to be self-managed. A collaborative system involving nodes, Base Stations (BSs) and servers is developed, as well as a new query processing method based on group and query prediction mobility (GQM) via Data Mining techniques. Data sources' administration during the execution of the query plan becomes primary interest especially for the starting query server. The proposed server grouping process, server's scale up capabilities and the application of Data Mining concepts in a wireless environment can contribute a lot to optimize the query plan and increase server independency. Various methods in distributed data exploration and exploitation, supporting server's semi-autonomous operational behavior, are developed. Simulation results are provided.
GASIM: a fast Galois field based simulator for functional model
Authors: D. K. Pradhan, A. K. Singh, T. L. Rajaprabhu, A. M. Jabir
Venue: Proceedings of the High-Level Design Validation and Test Workshop, 2005. on Tenth IEEE International (2005)

This paper presents a fast logic simulator based on Galois field. This is designed to act as an underlying tool for all finite field applications considering the fact that simulation plays an important role in all these applications. Three approaches for finite field representation and its evaluation are discussed. In addition an approach for normalizing the finite field based decision diagrams is also presented. The experimental results show the trade-off that can be made by using different design representations between spatial complexity and speed. Also the results show that it can be used in conventional simulation environment to achieve speedup.
Mirage: a microeconomic resource allocation system for sensornet testbeds
Authors: B. N. Chun, P. Buonadonna, A. AuYoung
Venue: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors (2005)

In this paper, we argue that a microeconomic resource allocation scheme, specifically the combinatorial auction, is well suited to testbed resource management. To demonstrate this, we present the Mirage resource allocation system. In Mirage, testbed resources are allocated using a repeated combinatorial auction within a closed virtual currency environment. Users compete for testbed resources by submitting bids which specify resource combinations of interest in space/time (e.g., "any 32 MICA2 motes for 8 hours anytime in the next three days") along with a maximum value amount the user is willing to pay. A combinatorial auction is then periodically run to determine the winning bids based on supply and demand while maximizing aggregate utility delivered to users. We have implemented a fully functional and secure prototype of Mirage and have been operating it in daily use for approximately four months on Intel Research Berkeley's 148-mote sensornet testbed.
Customer Service Says the Darnedest Things
Authors: Paul F. Dubois
Venue: Computing in Science and Engineering (2007)

Contributing editor Paul F. Dubois takes a light-hearted look at how much computer science resembles customer service
Real-time recognition of broadcast radio speech
Authors: G. D. Cook
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

This paper presents a real-time speech recognition system used to transcribe broadcast radio speech. The system is based on ABBOT, the hybrid connectionist-HMM large vocabulary continuous speech recognition system developed at the Cambridge University Engineering Department. Developments designed to make the system more robust to acoustic variability and to improve performance when decoding spontaneous speech are described. Modifications necessary to increase the speed of the system so that it operates in real-time are also described. Recognition results and latency figures are presented for speech collected from broadcast news segments on BBC Radio 4.
A new simulation-based property checking algorithm based on partitioned alternative search space traversal
Authors: Qingwei Wu, M. S. Hsiao
Venue: Proceedings of the High-Level Design Validation and Test Workshop, 2005. on Tenth IEEE International (2005)

We present a new logic-simulation-based algorithm that explores the search space defined by partitioned internal circuit nodes. Two powerful features are proposed to increase the effectiveness during search space exploration and counter-example generation for verifying safety properties. These include: (1) new search space constituted by internal nodes instead of state variables, (2) static learning on multiple nodes to further enlarge the target. These two features are integrated with the following techniques during our simulation: incorporation of a BCP (Boolean constraint propagation) engine for multiple nodes implication and multiple-time-frame GA (genetic algorithm) search. Because only logic simulation is needed in our algorithm, the computational effort is low. Experimental results on large benchmark circuits have shown that this logic-simulation-based verifier achieves significantly better results compared with existing formal verification tools and simulation-based methods.
Design and implementation of a direct access file system (DAFS) kernel server for FreeBSD
Authors: Kostas Magoutis
Venue: Proceedings of the BSD Conference 2002 on BSD Conference (2002)

The Direct Access File System (DAFS) is an emerging commercial standard for network-attached storage on server cluster interconnects. The DAFS architecture and protocol leverage network interface controller (NIC) support for user-level networking, remote direct memory access, effcient event notification, and reliable communication. This paper describes the design of the first implementation of a DAFS kernel server for FreeBSD, using existing interfaces with minor kernel modifications. We experimentally demonstrate that the current server structure can attain read throughput of more than 100 MB/s over a 1.25 Gb/s network even for small (i.e. 4K) block sizes when prefetching using an asynchronous client API. To reduce multithreading overhead and integrate the NIC with the host virtual memory system, our forthcoming system will incorporate new FreeBSD kernel support for asynchronous vnode I/O interfaces, integrating network and disk event notification and handling, and VM support for remote direct memory access. We believe our proposed kernel support is necessary to scale event-driven file servers to multi-gigabit network speeds.
Multi-level feature trees: A pragmatic approach to managing highly complex product families
Authors: Mark-Oliver Reiser, Matthias Weber
Venue: Requirements Engineering (2007)

Feature modeling has become a popular technique for domain analysis and variability management. However, it is still a considerable challenge to apply this technique to product families and organizational contexts of high complexity like the product range of a global automotive corporation. Managing everything as a single product family with a global feature tree is virtually impossible owing to the enormous complexity, but if the product range is split up into several smaller, independent product lines with separate feature models, systematic reuse and strategic variability management across these portions is lost. In this article, we present multi-level feature trees, which offer a compromise between a single global and several smaller, independent feature trees. Other development artifacts may also be arranged in this way if the multi-level concept is adapted to them. This is shown exemplarily for requirements artifacts in Telelogic Doors. Finally, we describe scenarios showing how this concept can be put into practice.
Extraction of Person Silhouettes from Surveillance Imagery using MRFs
Authors: Vinay Sharma, James W. Davis
Venue: Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision (2007)

We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object shape using a simple training phase requiring no manual segmentation. Based on the observation that most interesting objects (e.g., people) have regular and closed boundaries, we exploit relations between these features to extract mid-level cues, such as continuity and closure. For segmentation, we employ a Markov Random Field that combines these cues with information learned from training. The algorithm is evaluated for extracting person silhouettes from surveillance images, and quantitative results are presented.
Discriminative training of Gaussian mixture models for large vocabulary speech recognition systems
Authors: L. R. Bahl
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

Two discriminative techniques are described (and evaluated) for estimating the parameters of the Gaussians in a large vocabulary speech-recognition system. The first technique is based on using a modification of the maximum mutual information (MMI) objective function, and appears to provide no improvement over standard ML estimation. The second technique is based on a heuristic correction of the Gaussian parameters, and is seen to give a 2-5% improvement over ML estimation.
A unified model of early word learning: Integrating statistical and social cues
Authors: Chen Yu, Dana H. Ballard
Venue: Neurocomputing (2007)

Previous studies on early language acquisition have shown that word meanings can be acquired by an associative procedure that maps perceptual experience onto linguistic labels based on cross-situational observation. Recently, a social-pragmatic account focuses on the effect of the child's social-cognitive capacities, such as joint attention and intention reading. This paper argues that statistical and social cues can be seamlessly integrated to facilitate early word learning. To support this idea, we first introduce a statistical learning mechanism that provides a formal account of cross-situational observation. A unified model is then presented that is able to make use of different kinds of embodied social cues, such as joint attention and prosody in maternal speech, in the statistical learning framework. In a computational analysis of infant data, our unified model performs significantly better than the purely statistical approach in computing word-meaning associations.
Improving the subjective quality of low bit rate subband/wavelet coded images
Authors: Yuen-Wen Lee
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

Distortion resulting from ringing and/or aliasing is the most objectionable subjective distortion normally appearing in low bit rate subband/wavelet coded images. This paper presents a method for significantly reducing both ringing and aliasing, while still achieving low bit rates and requiring low encoding/decoding complexity. The method employs a new signal dependent two-band filter bank system that employs short FIR filters, yet results in a relatively small loss of aliasing cancellation in its synthesis section. The signal dependent part of the filter bank is the statistical linear prediction used to decorrelate the subband signals. Experimental results indicate that this approach can achieve very good subjective quality at low bit rates.
Blind separation of linear mixtures of digital signals using successive interference cancellation iterative least squares
Authors: Tao Li
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

We consider blind separation of linear mixtures of digital communication signals in noise. When little or nothing can be assumed about the mixing matrix, signal separation may be achieved by exploiting structural properties of the transmitted signals. ILSP and ILSE are two iterative least squares (ILS) separation algorithms that exploit the finite-alphabet property. ILSE is monotonically convergent and performs very well, but its complexity is exponential in the number of signals; ILSP is computationally cheaper, but is not guaranteed to converge monotonically, and leaves much to be desired in terms of BER-SNR performance relative to ILSE. We propose two computationally efficient and provably monotonically convergent ILS blind separation algorithms based on an optimal scaling Lemma. The signal estimation step of both algorithms is reminiscent of successive interference cancellation (SIC) ideas. For well-conditioned data and moderate SNR, the proposed algorithms attain the performance of ILSE at the complexity cost of ILSP.
Proceedings of the 2nd workshop on Domain specific aspect languages
Venue: Aspect-oriented software development (2007)

Although the majority of work in the AOSD community focuses on general-purpose aspect languages (e.g. AspectJ), seminal work on AOSD proposed a number of domainspecific aspect languages, such as COOL for concurrency management and RIDL for serialization, RG, AML, and others. A growing trend of research in the AOSD community is returning to this seminal work, as witnessed by the high attendance rate at the DSAL06 workshop, held as part of GPCE06/OOPSLA06. The workshop aimed to bring the research communities of domain-specific language engineering and domainspecific aspect design together. In the previous successful edition we approached domain-specific aspect languages from a language implementation point of view, where advances in the field of domain-specific language engineering were investigated to answer the implementation challenges of aspect languages. In this second edition, we approached the design and implementation of new domain-specific aspect languages, as well as the composition at all levels (from design to implementation) of these languages or individual features. The workshop sought contributions related to domainspecific aspect languages, more particularly (but not limited to): &bull; design of DSALs &bull; successful DSALs and their applications &bull; issues in both design and implementation of DSALs &bull; methodologies and tools suitable for creating DSALs &bull; mechanisms for interaction detection and handling in DSALs &bull; theoretical foundations for DSALs &bull; analysis about the specificity spectrum in aspect languages &bull; key challenges for future work in the area
Quantifying the Possible Financial Consequences of Failure for making a Risk Based Decision
Authors: Omar Khadeer Hussain, Elizabeth Chang, Farookh Khadeer Hussain, Tharam S. Dillon
Venue: Proceedings of the Second International Conference on Internet Monitoring and Protection (2007)

In a financial e-commerce interaction it is rational for the initiating agent to analyze beforehand the possible risk in interacting with any other agent. Doing so would give the initiating agent an idea of direction in which its interaction might head and also help it to make an informed decision of its future course of action with that particular agent. For risk analysis in the context of e-commerce interactions, the initiating agent has to determine beforehand the probability of failure and the possible consequences of failure in interacting with an agent. In this paper, we propose a methodology by which the initiating agent can determine beforehand the possible consequences of failure in its resources, according to the demand of its future interaction with an agent.
Design and modelling of a microsensor for atmospheric electric field measurement
Authors: Zheng Cui, Chao Gong, Shanhong Xia
Venue: Proceedings of the Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (2003)

A new type of electrical field sensor has been investigated for application in atmospheric electrical field measurement. The sensing principal is based on deflection of electrons under an external electrical field. Computer simulation of electron deflection has been carried out using a boundary integral method. It is demonstrated that electron deflection is linearly dependent on external field but inversely proportional to the collector voltage. By controlling the collector voltage, it is possible to dynamically control the sensitivity of the field sensor or the measurement range. An experimental sensor has been made. Preliminary experiment has revealed some practical issues in the sensor and further investigation is needed.
Secure Communication Trees in Ad Hoc Networks
Authors: Jan Nikodem, Maciej Nikodem
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

In this paper we examine the communication trees widely used in ad hoc networks. These trees can be used in a number of ways e.g. to route or broadcast messages and to aggregate information. In this paper we propose a new key distribution protocol for large and dynamic ad hoc networks over unreliable channel. Protocol proposed here involves broadcast exclusion based on polynomial interpolation and secret key cryptography. Proposed scheme ensures security of broadcast and one-to- one communication, message authentication and gives a possibility to verify routing information. It also ensures t-resilience which means that up to t nodes can be compromised without influencing the security.
Human-interactive annealing for turning threat to opportunity in technology development
Authors: Yoshiharu Maeno, Kiichi Ito, Kenichi Horie, Yukio Ohsawa
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

Human-interactive annealing is a new method for understanding invisible but relevant events, and inventing hypothetical scenarios. The human-interactive annealing is elaborated for texts. It is applied to patents for acquiring opportunity in technology development. An illustrative experiment on discovering opportunity by analyzing US patent texts on knowledge acquisition is demonstrated. A few sample hypothetical scenarios on emerging technological elements are obtained.
Forwards-backwards averaging for adaptive beamforming and STAP
Authors: M. Zatman
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

We investigate the use of forwards backwards (f/b) averaging for estimating the interference-only covariance matrix used for adaptive beamforming and space-time adaptive processing (STAP). We demonstrate that the estimation loss is reduced by the use of the extra samples available through f/b averaging, and in STAP a new type of f/b averaging can quadruple the number of samples available. Importantly, we present a new result which shows that unknown array manifold errors have little effect on the performance of f/b averaging. The gain from f/b averaging is demonstrated on data from the Mountaintop database.
The LMK algorithm with time-varying forgetting factor for adaptive system identification in additive output-noise
Authors: O. Tanrikulu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

Adaptive algorithms are susceptible to noise signals due to the perturbation of the gradient direction. Depending upon the statistics of the noise, various cost functions can be minimised. The least mean kurtosis (LMK) adaptive algorithm is a stochastic gradient approach that uses the kurtosis of the error signal. Depending upon the noise distribution, the forgetting factor used in the LMK algorithm must be chosen optimally. A version of the LMK is presented, in which the forgetting factor is made time-varying such that if the output-noise distribution is unknown, which is almost always the case in practice, the algorithm will tune its forgetting factor in sympathy with the noise distribution. Hence the proposed algorithm is more flexible than the least mean square (LMS) and least mean fourth (LMF) adaptive algorithms under noisy conditions.