ppxscal/embedding_network huggingface dataset:
Reflecting upon Feelings: An fMRI Study of Neural Systems Supporting the Attribution of Emotion to Self and Other
Authors: Kevin N. Ochsner, Kyle Knierim, David H. Ludlow, Josh Hanelin, Tara Ramachandran, Gary Glover
Venue: Journal of Cognitive Neuroscience (2004)

Understanding one's own and other individual's emotional states is essential for maintaining emotional equilibrium and strong social bonds. Although the neural substrates supporting ref lection upon one's own feelings have been investigated, no studies have directly examined attributions about the internal emotional states of others to determine whether common or distinct neural systems support these abilities. The present study sought to directly compare brain regions involved in judging one's own, as compared to another individual's, emotional state. Thirteen participants viewed mixed valence blocks of photos drawn from the International Affective Picture System while whole-brain fMRI data were collected. Preblock cues instructed participants to evaluate either their emotional response to each photo, the emotional state of the central figure in each photo, or (in a baseline condition) whether the photo was taken indoors or outdoors. Contrasts indicated (1) that both self and other judgments activated the medial prefrontal cortex (MPFC), the superior temporal gyrus, and the posterior cingulate/precuneus, (2) that self judgments selectively activated subregions of the MPFC and the left temporal cortex, whereas (3) other judgments selectively activated the left lateral prefrontal cortex (including Broca's area) and the medial occipital cortex. These results suggest (1) that self and other evaluation of emotion rely on a network of common mechanisms centered on the MPFC, which has been hypothesized to support mental state attributions in general, and (2) that medial and lateral PFC regions selectively recruited by self or other judgments may be involved in attention to, and elaboration of, internally as opposed to externally generated information.
Cooperative collision warning using dedicated short range wireless communications
Authors: Tamer ElBatt, Siddhartha K. Goel, Gavin Holland, Hariharan Krishnan, Jayendra Parikh
Venue: Proceedings of the 3rd international workshop on Vehicular ad hoc networks (2006)

The emergence of the 802.11a-based Dedicated Short Range Communications (DSRC) standard and advances in mobile ad hoc networking create ample opportunity for supporting delay-critical vehicular safety applications in a secure, resource-efficient, and reliable manner. In this paper, we focus on the suitability of DSRC for a class of vehicular safety applications called Cooperative Collision Warning (CCW), where vehicles periodically broadcast short messages for the purposes of driver situational awareness and warning. First, we present latency and success probability results of Forward Collision Warning (FCW) applications over DSRC. Second, we explore two design issues that are highly relevant to CCW applications, namely performance trends with distance and potential avenues for broadcast enhancements. Simulation results reveal interesting insights and trade-offs related to application-perceived latency and packet success probability performance. For instance, we conjecture the existence of an optimal broadcast rate that minimizes our novel latency measure for safety applications, and we characterize it for plausible scenarios.
Emblem Detections by Tracking Facial Features
Authors: Atul Kanaujia, Yuchi Huang, Dimitris Metaxas
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Tracking facial features across large head rotations is a challenging research problem. Both 2D and 3D model based approaches have been proposed for feature analysis from multiple views. Accurate feature tracking enables useful video processing applications like emblem detection(an event or movement that symbolizes an idea), facial expressions recognition, morphing and synthesis. A crucial requirement is generalizability of the tracking framework across appearance variations, presence of facial hair and illumination changes. We propose a framework to detect emblems that combines active shape model with a predictive face aspect model to track features across large head movements and runs close to real time. Active Shape Model(ASM) is a deformable model for shape registration that detect facial features by combining prior shape information with the observed image data. Our view based framework represents various head poses by multiple 2D shape models and accounts for large head rotations by dynamically switching between them. Our switching variable (the current model to use) is discriminatively predicted from the SIFT descriptors computed over the bounding box of low resolution face image. We demonstrate the use of tracking framework to recognize high level events like head nodding, shaking and eye blinking.
Understanding functional dependencies via constraint handling rules
Authors: Martin Sulzmann, Gregory J. Duck, Simon Peyton-Jones, Peter J. Stuckey
Venue: Journal of Functional Programming (2007)

Functional dependencies are a popular and useful extension to Haskell style type classes. We give a reformulation of functional dependencies in terms of Constraint Handling Rules (CHRs). In previous work, CHRs have been employed for describing user-programmable type extensions in the context of Haskell style type classes. Here, we make use of CHRs to provide for the first time a concise result that under some sufficient conditions, functional dependencies allow for sound, complete and decidable type inference. The sufficient conditions imposed on functional dependencies can be very limiting. We show how to safely relax these conditions and suggest several sound extensions of functional dependencies. Our results allow for a better understanding of functional dependencies and open up the opportunity for new applications.
Integration of Genetic Algorithm and Neural Network for Financial Early Warning System: An Example of Taiwanese Banking Industry
Authors: Jih-Chang Hsieh, Pei-Chann Chang, Shih-Hsin Chen
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

The applications of genetic algorithms and neural networks to financial early warning systems seem potential in the past works. Therefore genetic algorithm and neural network (GNN) are integrated to build a financial early warning system. An example of Taiwanese banking industry is discussed and the financial ratios of each bank were collected from 1998 to 2002. The performance of GNN is compared with other four early warning systems, namely, case-based reasoning (CBR), backpropagation neural network (BPN), logistic regression analysis (LR), and quadratic discriminant analysis (QDA). The result indicates that the GNN proposed in this research is a little superior to the two soft computing early warning systems (CBR and BPN). The GNN outperforms the statistical early warning systems (LR and QDA) at least 13%.
Nurses' informal argument: learning to justify the claim and reach agreement
Authors: Debra Hagler, Sarah Brem
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Nurses convince their peers of the need for ongoing action and monitoring during change-of-shift discourse about patient health issues. Twenty pairs of critical-care nurses participated in a qualitative study of authentic everyday argument at the bedside. The process of providing and evaluating evidence for claims and justifying decisions during nursing shift report included pragmatic and structural aspects of persuasive argument in the context of a high-stress, high-stakes, time-pressured environment.
Implications of Web 2.0 for the Semantic Grid
Authors: Geoffrey Fox
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Web 2.0 is characterized by blogs, wikis, mashups and hundreds of websites supporting social exchanges including tagged bookmarks, pictures and personal profiles. This supports universal simple approaches to publication, composition of services and a rich metadata system for adorning URL's and people. The Semantic Grid has related goals but is typically implemented with tools and capabilities of much greater sophistication but with less elegant and robust implementations. It appears interesting to base Semantic Grids on Web2.0 technology as this will facilitate adoption and support. We explore this idea.
Supramodal Effects of Covert Spatial Orienting Triggered by Visual or Tactile Events
Authors: E. Macaluso, C. D. Frith, J. Driver
Venue: Journal of Cognitive Neuroscience (2002)

Event-related functional magnetic resonance imaging was used to identify brain areas involved in spatial attention and determine whether these operate unimodally or supramodally for vision and touch. On a trial-by-trial basis, a symbolic auditory cue indicated the most likely side for the subsequent target, thus directing covert attention to one side. A subsequent target appeared in vision or touch on the cued or uncued side. Invalidly cued trials (as compared with valid trials) activated the temporo-parietal junction and regions of inferior frontal cortex, regardless of target modality. These brain areas have been associated with multimodal spatial coding in physiological studies of the monkey brain and were linked to a change in the location that must be attended to in the present study. The intraparietal sulcus and superior frontal cortex were also activated in our task, again, regardless of target modality, but did not show any specificity for invalidly cued trials. These results identify a supramodal network for spatial attention and reveal differential activity for inferior circuits involving the temporo-parietal junction and inferior frontal cortex (specific to invalid trials) versus more superior intraparietal-frontal circuits (common to valid and invalid trials).
Connectivity of wireless multihop networks in a shadow fading environment
Authors: Christian Bettstetter, Christian Hartmann
Venue: Wireless Networks (2005)

This article analyzes the connectivity of multihop radio networks in a log-normal shadow fading environment. Assuming the nodes have equal transmission capabilities and are randomly distributed according to a homogeneous Poisson process, we give a tight lower bound for the minimum node density that is necessary to obtain an almost surely connected subnetwork on a bounded area of given size. We derive an explicit expression for this bound, compute it in a variety of scenarios, and verify its tightness by simulation. The numerical results can be used for the practical design and simulation of wireless sensor and ad hoc networks. In addition, they give insight into how fading affects the topology of multihop networks. It is explained why a high fading variance helps the network to become connected.
Do map drawing styles of novice programmers predict success in programming?: a multi-national, multi-institutional study
Authors: Denise Tolhurst, Bob Baker, John Hamer, Ilona Box, Raymond Lister, Quintin Cutts, Marian Petre, Michael de Raadt, Anthony Robins, Sally Fincher, Simon, Patricia Haden, Ken Sutton, Margaret Hamilton, Jodi Tutty
Venue: Proceedings of the 8th Austalian conference on Computing education - Volume 52 (2006)

In this paper, we present the results of one aspect of a multinational, multi-institutional study of computer programming students. Specifically, this paper reports on an exploration of relationships between novice programmers' map-drawing styles (landmark, route or survey) and success in a first programming course at tertiary level. Relationships were found between map-drawing style and success of students in introductory programming' courses, but there were mediating factors that resulted in some mixed findings between the countries in which data was collected. The results of this study identify some rich areas for further exploration, and suggests how this line of research might progress.
It's a long way to Monte Carlo: probabilistic display in GPS navigation
Authors: John Williamson, Steven Strachan, Roderick Murray-Smith
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

We present a mobile, GPS-based multimodal navigation system, equipped with inertial control that allows users to explore and navigate through an augmented physical space, incorporating and displaying the uncertainty resulting from inaccurate sensing and unknown user intentions. The system propagates uncertainty appropriately via Monte Carlo sampling and predicts at a user-controllable time horizon. Control of the Monte Carlo exploration is entirely tilt-based. The system output is displayed both visually and in audio. Audio is rendered via granular synthesis to accurately display the probability of the user reaching targets in the space. We also demonstrate the use of uncertain prediction in a trajectory following task, where a section of music is modulated according to the changing predictions of user position with respect to the target trajectory. We show that appropriate display of the full distribution of potential future users positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data.
Video Coding Based on Low Level Spatial Description of the Frames Sequence and on Human Visual System Perceptual Characteristics
Authors: Luca Leschiutta
Venue: Proceedings of the conference on Information Visualization (2006)

Aim of this work is to envisage a video coding technique capable to exploit low level plots between nearby pixels inside the video sequence. The coding technique is first developed for images via the decomposition into small rectangular regions and then is extended to the video case utilizing a motion compensation technique to find replicas of the rectangles found on the first frame into the following ones. The results of these techniques are discussed in terms of obtained compression ratios and in terms of optimization of the results varying several parameters in the rules that lead to the composition of the shapes identified inside the video sequence.
A Strongly Minimal Axiomatisation of Multivalued Dependencies in Incomplete Database Relations
Authors: Sebastian Link
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

We study inference rules for multivalued dependencies in relational databases with null values (NMVDs). The definition of NMVDs is dependent on the underlying relation schema and this is reflected syntactically by the - complementation rule which is present in all previous axiomatisation of NMVDs. The main result is a sound and complete set of inference rules in which the -axiom is the only inference rule dependent on . This result extends work of Biskup who has provided such an axiomatisation in the absence of null values. It is proven that the set is minimal in a very strong sense. In fact, none of its rules can be omitted without losing the ability to infer all trivial NMVDs.
Increasing the capacity of RAID5 by online gradual assimilation
Authors: Jose Luis Gonzalez, Toni Cortes
Venue: Proceedings of the international workshop on Storage network architecture and parallel I/Os (2004)

Disk arrays level 5 (RAID5) are very commonly used in many environments. This kind of arrays has the advantage of parallel access, fault tolerance and little waste of space for redundancy issues. Nevertheless, this kind of storage architecture has a problem when more disks have to be added to the array. Currently, there is no simple, efficient and on-line mechanism to add any number of new disks (not replacing them), and this is an important drawback in systems that cannot be stopped when the storage capacity needs to be increased. We propose an algorithm to add N disks to an array while it continues running. The proposed algorithm for a gradual assimilation of disks has three major advantages: it has an easily controlled overhead, it allows the user to benefit from the higher parallelism achieved by the part of the array that has already been converted, and finally, it can be used in 7/24 systems.
WiMax: The Emergence of Wireless Broadband
Authors: Zakhia Abichar, Yanlin Peng, J. Morris Chang
Venue: IT Professional (2006)

WiMax has changed the scene of wireless broadband from proprietary solutions to a standards-based industry. Authors discuss WiMax evolution, applications, spectrum issues, standards, and developments.
Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks
Authors: Nishith Pathak, Sandeep Mane, Jaideep Srivastava
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Interpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be tapped to facilitate various organizational processes. However, the approaches of collecting data about them using surveys/interviews are fraught with problems of scalability, logistics and reporting biases, especially since such surveys may be perceived to be intrusive. Widespread use of computer networks for organizational communication provides a unique opportunity to overcome these difficulties and automatically map the organizational networks with a high degree of detail and accuracy. This paper describes an effective and scalable approach for modeling organizational networks by tapping into an organization's email communication. The approach models communication between actors as non-stationary Bernoulli trials and Bayesian inference is used for estimating model parameters over time. This approach is useful for sociocognitive analysis (who knows who knows who) of organizational communication networks. Using this approach, novel measures for analysis of (i) closeness between actors' perceptions about such organizational networks (agreement), (ii) divergence of an actor's perceptions about organizational network from reality (misperception) are explained. Using the Enron email data, we show that these techniques provide sociologists with a new tool to understand organizational networks.
State-of-the-art in protocol research for underwater acoustic sensor networks
Authors: Ian F. Akyildiz, Dario Pompili, Tommaso Melodia
Venue: Proceedings of the 1st ACM international workshop on Underwater networks (2006)

In this paper, architectures for two-dimensional and three-dimensional underwater sensor networks are discussed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols are given and open research issues are discussed.
Recent Developments in the Modeling, Analysis, and Numerics of Ferromagnetism
Authors: Martin Kruzík, Andreas Prohl
Venue: SIAM Review (2006)

Micromagnetics is a continuum variational theory describing magnetization patterns in ferromagnetic media. Its multiscale nature due to different inherent spatiotemporal physical and geometric scales, together with nonlocal phenomena and a nonconvex side-constraint, leads to rich behavior and pattern formation. This variety of effects is also the reason for severe problems in analysis, model validation, reductions, and numerics, which have only recently been accessed and are reviewed in this work.
Finding and counting cliques and independent sets in r-uniform hypergraphs
Authors: Raphael Yuster
Venue: Information Processing Letters (2006)

We present a matrix multiplication based algorithm for counting the number of (induced) occurrences of a fixed r-uniform hypergraph in a larger hypergraph. In many cases, the running time is better than that of the naïve algorithm. We also present several useful applications of the algorithm, such as determining the dominant color among monochromatic simplices in a red-blue edge-colored hypergraph, approximating the number of independent simplices in a random hypergraph, and counting induced occurrences of a given 3-uniform k-vertex hypergraph in a larger k-clique free hypergraph.
Sequential sampling techniques for algorithmic learning theory
Authors: Osamu Watanabe
Venue: Theoretical Computer Science (2005)

A sequential sampling algorithm or adaptive sampling algorithm is a sampling algorithm that obtains instances sequentially one by one and determines from these instances whether it has already seen enough number of instances for achieving a given task. In this paper, we present two typical sequential sampling algorithms. By using simple estimation problems for our example, we explain when and how to use such sampling algorithms for designing adaptive learning algorithms.
Design research for the living curriculum
Authors: Gregory W. Shrader, Louis M. Gomez
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

This paper reports on design research for an on-line performance support system that provides case-based support for teaching project-based science curricula. The goal of the system is to provide teachers using PBS curricula with access to help in the form of examples of the enacted curriculum, answer common questions, and support for key teaching tasks.
Linear-phase M-band wavelets with application to image coding
Authors: P. N. Heller, T. Q. Nguyen, H. Singh, W. K. Carey
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

This paper investigates the design of M-band linear phase wavelet filter banks (M>2), and explores their application to image coding. The generalized LOT description of M-band linear-phase paraunitary filter banks is used to parametrize the M-band linear-phase orthogonal wavelets. It is proven that an M-band linear-phase orthogonal wavelet of even length cannot have more than one vanishing moment. Since this limits the effectiveness of the resulting wavelet filters, we next suggest methods for the construction of linear-phase biorthogonal M-band wavelet lowpass filters, generalizing prior 2-band constructions. However, one cannot guarantee that an arbitrary lowpass filter pair can be completed to a full perfect-reconstruction filter bank. Finally, the new linear-phase orthogonal wavelet filter banks are compared with known wavelet filters with regard to their performance in a transform-based image coder.
Signal Based Node Activation in Wireless Sensor Networks
Authors: Richard Tynan, G. M. P. O'Hare, Antonio Ruzzelli
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

The emerging technology of Wireless Sensor Networks offers the potential for a new and unparalleled level of surveillance for events occurring in an environment. The quality of surveillance will be directly related to the quantity and density of sensors that can be deployed, and that are actively participating in the monitoring at any given instant. In opposition to this is the requirement for judicious power management of the network in order to prolong its operational lifespan by minimizing node activity. In this paper we explore the effect on surveillance quality when using interpolation error as a mechanism for deciding node activations. More specifically we examine the effect of using this signal based hibernation technique on target localization error and node activity.