ppxscal/embedding_network huggingface dataset:
Networked Instrumentation for Nanotechnologies Using WS-Resources and WS-Notification
Authors: Jungwook Seo, Ernie W. Hill
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

We present a review of a stateful Web Service that manages networked instrumentation for Nanotechnology research on the Grid. The Web Service that we have implemented is based on WSResource Framework (WSRF) and WS-Notification and is designed especially for a Scanning Electron Microscope (SEM) that can provide scientists with 1 nanometer resolution images. We outline the roles of 'Resource Home 'in WSRF, which manages WSResources, in implementations and also presents how WS-Resources in different domains interact with each other for subsequent job execution. Additionally, this paper proposes a new approach of networked instrumentation using virtual objects. A variety of tools such as Globus Toolkit 4(GT4) Core, XML based languages Java and Java3D have been utilized for this implementation.
A Hybrid SOM-Based Document Organization System
Authors: Renato Fernandes Correa, Teresa Bernarda Ludermir
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

This paper presents and evaluates a hybrid system to self-organization of massive document collections based on Self-Organizing Maps. The hybrid system uses prototypes generated by a clustering algorithm to training the document maps, thus reducing the training time of large maps. We test the system with two clustering algorithms: k-means and the AY method. The experiments were carried out with the Reuters- 21758 v1.0 collection. The performance of the system was measured in terms of text categorization effectiveness on test set and training time. The experimental results show that proposed system generate pretty good document maps and that the system had similar effectiveness performance with both clustering methods, however the use of k-means generated the smallest training time.
Clustering in WSN with Latency and Energy Consumption Constraints
Authors: Bassam Aoun, Raouf Boutaba
Venue: Journal of Network and Systems Management (2006)

Sensor networks have emerged as a revolutionary technology for querying the physical world and hold promise in a wide variety of applications. However, the extremely energy constrained nature of these networks necessitate that their architecture be designed in an energy-aware manner. Clustering is the architecture of choice as it keeps the traffic local; sensor nodes would send only to nearby cluster-head within a fixed radius, independent of the network size.In this paper we address the problem of clustering in WSNs, subject to upper bounds on the maximum latency, the energy consumed by intermediate nodes, and clusters size. Those constraints are necessary for the reliability of the system and for extending its lifetime. We propose a polynomial time algorithm consisting of recursively computing minimum weighted dominating sets, while respecting latency and energy consumption constraints. We compare our algorithm to other alternatives and show that it consistently outperforms them.
Automatic Encoding of Polyphonic Melodies in Musicians and Nonmusicians
Authors: Takako Fujioka, Laurel J. Trainor, Bernhard Ross, Ryusuke Kakigi, Christo Pantev
Venue: Journal of Cognitive Neuroscience (2005)

In music, multiple musical objects often overlap in time. Western polyphonic music contains multiple simultaneous melodic lines (referred to as "voices") of equal importance. Previous electrophysiological studies have shown that pitch changes in a single melody are automatically encoded in memory traces, as indexed by mismatch negativity (MMN) and its magnetic counterpart (MMNm), and that this encoding process is enhanced by musical experience. In the present study, we examined whether two simultaneous melodies in polyphonic music are represented as separate entities in the auditory memory trace. Musicians and untrained controls were tested in both magnetoencephalogram and behavioral sessions. Polyphonic stimuli were created by combining two melodies (A and B), each consisting of the same five notes but in a different order. Melody A was in the high voice and Melody B in the low voice in one condition, and this was reversed in the other condition. On 50% of trials, a deviant final (5th) note was played either in the high or in the low voice, and it either went outside the key of the melody or remained within the key. These four deviations occurred with equal probability of 12.5% each. Clear MMNm was obtained for most changes in both groups, despite the 50% deviance level, with a larger amplitude in musicians than in controls. The response pattern was consistent across groups, with larger MMNm for deviants in the high voice than in the low voice, and larger MMNm for in-key than out-of-key changes, despite better behavioral performance for out-of-key changes. The results suggest that melodic information in each voice in polyphonic music is encoded in the sensory memory trace, that the higher voice is more salient than the lower, and that tonality may be processed primarily at cognitive stages subsequent to MMN generation.
When TCP Breaks: Delay- and Disruption- Tolerant Networking
Authors: Stephen Farrell, Vinny Cahill, Dermot Geraghty, Ivor Humphreys, Paul McDonald
Venue: IEEE Internet Computing (2006)

The authors give an overview of current work on delay- and disruption-tolerant networking and review the overall architecture proposed by the Internet Research Task Force's Delay Tolerant Networking Research Group. Their approach to networking makes no assumption that nodes will have end-to-end connectivity, which could be missing with extremely high-latency connections, if the nodes are only in contact with one another infrequently or if contacts are being continually disrupted. They also describe the main protocols the group is developing and give examples of some pilot networks that use these protocols.
An efficient interprocedural dynamic slicing method
Authors: G. B. Mund, Rajib Mall
Venue: Journal of Systems and Software (2006)

We present an efficient interprocedural dynamic slicing algorithm for structured programs. We first propose an intraprocedural dynamic slicing algorithm, and subsequently extend it to handle interprocedural calls. Our intraprocedural dynamic slicing algorithm uses control dependence graph as the intermediate program representation, and computes precise dynamic slices. The interprocedural dynamic slicing algorithm uses a collection of control dependence graphs (one for each procedure) as the intermediate program representation, and computes precise dynamic slices. We show that our proposed interprocedural dynamic slicing algorithm is more efficient than the existing dynamic slicing algorithms. We also discuss how our algorithm can be extended to efficiently handle recursion, composite data structures and pointers.
Mobile devices to be applied as supporting tools in research methods class for undergraduate students
Authors: Eteokleous Mikleia
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Mobile devices are becoming part of the educational environment. In this case, mobile devices role as supporting tools is under investigation. Specifically, undergraduate college students appear to have time-management and organization problems regarding designing, and constructing the research process and developing their research reports. Hypothesis is made that if a SMS alert system remind students for deadlines and other organizational issues related to the research process, the time management and organization problems will be addressed.
Modeling and simulation of consumer credit originations processes
Authors: Hung-Nan Chen, Jihong Jin, Geetha Rajavelu, Charles Reichenbach
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Staffing decisions in a consumer credit origination environment have a significant impact on the financial institution's costs as well as customer service levels. Staff resources account for a substantial portion of the expenses in processing and servicing home equity or consumer loans. This paper describes a staffing model, known as the Capacity Planning Simulation Model (CPSM), used in the Originations Division of Wells Fargo Bank's Consumer Credit Group. The CPSM utilizes process mapping, spreadsheet modeling, and Monte Carlo simulation to model demand uncertainty and process variation, observed during the course of processing a consumer credit loan. We review the model formulation, verification, validation, and application.
Base Address Recognition with Data Flow Tracking for Injection Attack Detection
Authors: Satoshi Katsunuma, Hiroyuki Kurita, Ryota Shioya, Kazuto Shimizu, Hidetsugu Irie, Masahiro Goshima, Shuichi Sakai
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

Vulnerabilities such as buffer overflows exist in some programs, and such vulnerabilities are susceptible to address injection attacks. The input data tracking method, which was proposed before, prevents I-data, which are the data derived from the input data, being used as addresses. However, the rules to determine address injection attacks are vague, which produces many false-positives and falsenegatives in detection results. Generally, the data used as an address consist of a base address and an address offset. We propose an architectural technique to prevent Idata overwriting B-data, which are the data used as base addresses in this paper. It dynamically recognizes the Idata and the B-data. Address injection is detected if I-data that are not B-data are used as addresses. We implemented the proposed technique on a Pentium-based Bochs emulator and investigated its detection capability. I believe that the technique is the most accurate injection detection technique proposed thus far.
Feedback in Hypothesis Testing: An ERP Study
Authors: David Papo, Pierre-Marie Baudonnière, Laurent Hugueville, Jean-Paul Caverni
Venue: Journal of Cognitive Neuroscience (2003)

We used event-related potentials (ERPs) to probe the effects of feedback in a hypothesis testing (HT) paradigm. Thirteen college students serially tested hypotheses concerning a hidden rule by judging its presence or absence in triplets of digits and revised them on the basis of an exogenous performance feedback. ERPs time-locked to performance feedback were then examined. The results showed differences between responses to positive and negative feedback at all cortical sites. Negative feedback, indicating incorrect performance, was associated to a negative deflection preceding a P300-like wave. Spatiotemporal principal component analysis (PCA) showed the interplay between early frontal components and later central and posterior ones. Lateralization of activity was selectively detectable at frontal sites, with a left frontal dominance for both positive and negative feedback. These results are discussed in terms of a proposed computational model of trial-to-trial feedback in HT in which the cognitive and emotive aspects of feedback are explicitly linked to putative mediating brain mechanisms. The properties of different feedback types and feedback-related deficits in depression are also discussed.
An embedded boundary method for viscous, conducting compressible flow
Authors: Zoran Dragojlovic, Farrokh Najmabadi, Marcus Day
Venue: Journal of Computational Physics (2006)

The evolution of an inertial fusion energy (IFE) chamber involves a repetition of short, intense depositions of energy (from target ignition) into a reaction chamber, followed by the turbulent relaxation of that energy through shock waves and thermal conduction to the vessel walls. We present an algorithm for 2D simulations of the fluid inside an IFE chamber between fueling repetitions. Our finite-volume discretization for the Navier-Stokes equations incorporates a Cartesian grid treatment for irregularly-shaped domain boundaries. The discrete conservative update is based on a time-explicit Godunov method for advection, and a two-stage Runge-Kutta update for diffusion accommodating state-dependent transport properties. Conservation is enforced on cut cells along the embedded boundary interface using a local redistribution scheme so that the explicit time step for the combined approach is governed by the mesh spacing in the uniform grid. The test problems demonstrate second-order convergence of the algorithm on smooth solution profiles, and the robust treatment of discontinuous initial data in an IFE-relevant vessel geometry.
Modeling and controlling the heart conductive system
Authors: A. Loskutov, S. Rybalko, E. Zhuchkova
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

A model of the cardiac tissue as a conductive excitable system with a pacemaker under external stimuli is proposed. At certain conditions this model is reduced to the standard circle map. It is analytically shown that 2-periodic perturbations of the constructed map lead to the stabilization of the prescribed orbits and thus, allow us to realize the control of complex cardiac rhythms and remove the heart behaviour to the required dynamical regime.
Using Historical In-Process and Product Metrics for Early Estimation of Software Failures
Authors: Nachiappan Nagappan, Thomas Ball, Brendan Murphy
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

The benefits that a software organization obtains from estimates of product quality are dependent upon how early in the product cycle that these estimates are available. Early estimation of software quality can help organizations make informed decisions about corrective actions. To provide such early estimates we present an empirical case study of two large scale commercial operating systems, Windows XP and Windows Server 2003. In particular, we leverage various historical in-process and product metrics from Windows XP binaries to create statistical predictors to estimate the post-release failures/failure-proneness of Windows Server 2003 binaries. These models estimate the failures and failure-proneness of Windows Server 2003 binaries at statistically significant levels. Our study is unique in showing that historical predictors for a software product line can be useful, even at the very large scale of the Windows operating system.
Pattern statistics and Vandermonde matrices
Authors: Massimiliano Goldwurm, Violetta Lonati
Venue: Theoretical Computer Science (2006)

In this paper, we determine some limit distributions of pattern statistics in rational stochastic models. We present a general approach to analyze these statistics in rational models having an arbitrary number of strongly connected components. We explicitly establish the limit distributions in most significant cases; they are characterized by a family of unimodal density functions defined by means of confluent Vandermonde matrices.
Individual Differences in the Modulation of Fear-Related Brain Activation by Attentional Control
Authors: Andrew Mathews, Jenny Yiend, Andrew D. Lawrence
Venue: Journal of Cognitive Neuroscience (2004)

In this article, we consider the extent to which variations in the neural activation associated with fear-related stimuli are obligatory or optional. More specifically, we investigated modulation of activation according to type of encoding operation, and how this relates to individual differences in fearfulness and attentional control. In an fMRI study, fear-related (relative to neutral) pictures preferentially activated many of the regions involved in a hierarchical system responsible for organizing defensive behavior, and differential activation in some of these areas was related to self-reported individual variations in fearfulness. Preferential activation according to type of stimulus persisted to a limited extent even when attention was diverted from its emotional aspects. Importantly, however, encoding tasks involving attention to emotional versus nonemotional attributes of the same pictures revealed a pattern of greater activation during emotional encoding, similar to that differentiating fear-related from neutral stimuli. Again, the degree of modulation varied according to individual differences. We conclude that fear-related pictures can recruit activation in the defensive system even when attention is directed elsewhere, but that the extent of this activation is modulated by attentional control mechanisms. More critically, both differential activation and its modulation by attentional control are related to individual variations in emotional vulnerability, in a manner that conforms to predictions derived from existing theoretical accounts.
Connectivity, Performance, and Resiliency of IP-Based CDMA Radio Access Networks
Authors: Tian Bu, Mun Choon Chan, Ram Ramjee
Venue: IEEE Transactions on Mobile Computing (2006)

IP-based Radio Access Networks (RAN) are expected to be the next generation access networks in UMTS and CDMA networks. The question of connectivity, i.e., how best to connect base stations to the Radio Network Controllers (RNC) in an IP-based RAN, has not been addressed by researchers. Furthermore, given a connection configuration, an RNC selection algorithm that assigns an incoming call to an RNC is also necessary. This paper examines RAN connectivity and its impact on the performance and resiliency of the wireless network using different RNC selection algorithms. For homogeneous networks, we show that the proposed Min-Load-1 algorithm, which allows at most one hard handoff in order to accommodate each incoming call request, delivers performance close to the optimal algorithm. We also show that allowing a few base stations to connect to two RNCs (a 10 percent increase in the number of links in our network) results in resiliency to RNC failures that is comparable to the resiliency of RANs with full-mesh connectivity. Finally, for heterogeneous networks, we show that the Min-Load-k algorithm (with at most k hard handoffs per call) is effective in handling load imbalances. These results provide strong motivation for deploying IP-based RAN, as they suggest that enhancing current point-to-point RAN with few additional links and allowing a few hard handoffs to accommodate incoming calls can result in significant gains in performance and resiliency.
On the stability and convergence of Feintuch's algorithm for adaptive IIR filtering
Authors: M. Rupp, A. H. Sayed
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

Gradient-descent adaptive algorithms are among the most widely used in current practice, with many different variants that generally fit into two major groups: one group includes algorithms that are especially suited for FIR (or finite-impulse-response) modeling, while the other group includes algorithms that are tailored for IIR (or infinite-impulse-response) modeling. In the first group, the regression (or data) vectors do not depend on the unknown parameters, which leads to convenient linear models that often facilitate the analysis of the algorithms. In the second category, on the other hand, the regression vectors are dependent on the unknown parameters, thus giving rise to nonlinear functionals and to a richer structure that requires a more thorough analysis. This paper focuses on a widely used adaptive IIR algorithm, the so-called Feintuch's (1976) algorithm, and provides a study of its robustness, stability, and convergence properties in a deterministic framework.
Memory-Based In Situ Learning for Unmanned Vehicles
Authors: Patrick McDowell, Brian S. Bourgeois, Donald A. Sofge, S. S. Iyengar
Venue: Computer (2006)

Researchers are using a sensor-input-based metric to develop a team of robots that would have the capability to learn their roles and improve strategies so that they can meet their overall goals in dynamic unstructured environments such as underwater or urban settings in which communications and monitoring are difficult.
An average values global model for the switched reluctance machine
Authors: A. J. Pires, J. F. Martins, P. J. Branco, J. A. Dente
Venue: Mathematics and Computers in Simulation (2006)

The main subject of this paper is to present a new simplified global model for the switched reluctance machine (SRM), useful, namely, for the command and control analysis of this kind of system. The concepts of power and energy are used in the global model construction, with the definition of global parameters and variables. This new global model presents an advantage over the classical detailed one, which is the reduction of the number of dynamic equations. The time-dependent global parameters disadvantage, which appears in the model construction process, is overcome with the consideration of average values for global variables and global parameters, allowing the representation of the machine non-detailed behavior. An average values global model is obtained. An 8/6 SRM with four phases, eight stator poles and six rotor poles is characterized and used for illustration of the system behavior, regarding its variables evolution. In the SRM command it is assumed that the m.m.f, is imposed, which means that the system current is controlled.
Learning Monotone Decision Trees in Polynomial Time
Authors: Ryan O' Donnell, Rocco A. Servedio
Venue: Proceedings of the 21st Annual IEEE Conference on Computational Complexity (2006)

We give an algorithm that learns any monotone Boolean function f : {-|1, 1}^n \to¨ {-1, 1} to any constant accuracy, under the uniform distribution, in time polynomial in n and in the decision tree size of f. This is the first algorithm that can learn arbitrary monotone Boolean functions to high accuracy, using random examples only, in time polynomial in a reasonable measure of the complexity of f. A key ingredient of the result is a new bound showing that the average sensitivity of any monotone function computed by a decision tree of size s must be at most \sqrt{log s}. This bound has already proved to be of independent utility in the study of decision tree complexity [27]. We generalize the basic inequality and learning result described above in various ways; specifically, to partition size (a stronger complexity measure than decision tree size), p-biased measures over the Boolean cube (rather than just the uniform distribution), and real-valued (rather than just Boolean-valued) functions.
Exposing digital forgeries through chromatic aberration
Authors: Micah K. Johnson, Hany Farid
Venue: Proceedings of the 8th workshop on Multimedia and security (2006)

Virtually all optical imaging systems introduce a variety of aberrations into an image. Chromatic aberration, for example, results from the failure of an optical system to perfectly focus light of different wavelengths. Lateral chromatic aberration manifests itself, to a first-order approximation, as an expansion/contraction of color channels with respect to one another. When tampering with an image, this aberration is often disturbed and fails to be consistent across the image. We describe a computational technique for automatically estimating lateral chromatic aberration and show its efficacy in detecting digital tampering.