ppxscal/embedding_network huggingface dataset:
Estimating the Gaze Point of a Student in a Driving Simulator
Authors: Wim Fikkert, Dirk Heylen, Betsy van Dijk, Anton Nijholt, Jorrit Kuipers, Arnd Brugman
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In this paper we discuss an approach towards passively observing students in a driving simulator. The goal is to enhance the learning experience for students taking lessons in this simulator. To this end, a virtual driving instructor is provided with added information consisting of the gaze behavior of its student. The gaze behavior is defined by estimated head locations and orientations. The learning experience for the student is enhanced by providing added feedback to the student based on his observed behavior.
cc{\rm T}: A Tool for Checking Advanced Correspondence Problems in Answer-Set Programming
Authors: Johannes Oetsch, Martina Seidl, Hans Tompits, Stefan Woltran
Venue: Proceedings of the 15th International Conference on Computing (2006)

In recent work, a general framework for specifying correspondences between logic programs under the answer-set semantics has been defined. The framework allows to define different notions of equivalence, including well-known notions like strong equivalence as well as refined ones based on the projection of answer sets, where not all parts of an answer set are of relevance. In this paper, we describe a system, called cc{\rm T}, to verify program correspondences in this general framework, relying on linear-time constructible reductions to quantified propositional logic using extant solvers for the latter language as back-end inference engines. We provide a preliminary performance evaluation which sheds light on some crucial design issues.
Who Comes First? The Role of the Prefrontal and Parietal Cortex in Cognitive Control
Authors: Marcel Brass, Markus Ullsperger, Thomas R. Knoesche, D. Yves Von Cramon, Natalie A. Phillips
Venue: Journal of Cognitive Neuroscience (2005)

Cognitive control processes enable us to adjust our behavior to changing environmental demands. Although neuropsychological studies suggest that the critical cortical region for cognitive control is the prefrontal cortex, neuro-imaging studies have emphasized the interplay of prefrontal and parietal cortices. This raises the fundamental question about the different contributions of prefrontal and parietal areas in cognitive control. It was assumed that the prefrontal cortex biases processing in posterior brain regions. This assumption leads to the hypothesis that neural activity in the prefrontal cortex should precede parietal activity in cognitive control. The present study tested this assumption by combining results from functional magnetic resonance imaging (fMRI) providing high spatial resolution and event-related potentials (ERPs) to gain high temporal resolution. We collected ERP data using a modified task-switching paradigm. In this paradigm, a situation where the same task was indicated by two different cues was compared with a situation where two cues indicated different tasks. Only the latter condition required updating of the task set. Task-set updating was associated with a midline negative ERP deflection peaking around 470 msec. We placed dipoles in regions activated in a previous fMRI study that used the same paradigm (left inferior frontal junction, right inferior frontal gyrus, right parietal cortex) and fitted their directions and magnitudes to the ERP effect. The frontal dipoles contributed to the ERP effect earlier than the parietal dipole, providing support for the view that the prefrontal cortex is involved in updating of general task representations and biases relevant stimulus&ndash;response associations in the parietal cortex.
Blind equalization of rapidly fading channels via exploitation of cyclostationarity and higher-order statistics
Authors: M. K. Tsatsanis, G. B. Giannakis
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

Basis expansion ideas are used for blind equalization of rapidly fading time-varying channels. Each time-varying coefficient is expanded onto a basis and the expansion parameters are estimated. It is shown that the mobile radio channel falls into this framework and its time-variation is well described by an exponential basis. Linear and nonlinear algorithms are derived to estimate the expansion parameters using time-varying cumulants. Identifiability and consistency are also established. Finally, a procedure for estimating the frequencies of the exponentials is delineated.
Explaining and eliminating latchup in a classical Wien oscillator via nonlinear design
Authors: A. S. Elwakil
Venue: Analog Integrated Circuits and Signal Processing (2006)

A classical Wien-type sinusoidal oscillator is analyzed to explain the origin of its latchup behavior. Only when a correct nonlinear model of the oscillator is derived and the stability of all equilibrium points associated with each region of operation of the fundamentally nonlinear amplifier characteristics is studied can this phenomena be predicted. It is further shown how latchup can be eliminated.
An Assertional Correctness Proof of a Self-Stabilizing - Exclusion Algorithm
Authors: Milos Besta, Frank Stomp
Venue: Proceedings of the 11th IEEE International Conference on Engineering of Complex Computer Systems (2006)

A formal correctness proof of a self-stabilizing - exclusion algorithm (SLEX) is described. The analyzed algorithm is an improvement of the SLEX due to Abraham, Dolev, Herman, and Koll, since our version satisfies a stronger liveness property. The proof is formulated in Linear-Time Temporal Logic and utilizes a history variable to model access to regular registers. The proof consists of a safety part and a liveness part. Our analysis provides some new insight in the correctness of the algorithm: (1) Our proof is constructive. That is, we explicitly formulate auxiliary quantities required to establish some of the properties. This contrasts with the operational arguments of Abraham et al., where many quantities are not explicitly formulated and the validity of the above mentioned properties is established by disproving their non-existence. (2) We characterize processes (and their minimum number) identified by some process as attempting to enter the critical section. (3) A novel proof rule for reasoning about programs in the presence of disabled processes is presented to structure the liveness proof.
Broadcasting in all-output-port cube-connected cycles with distance-insensitive switching
Authors: Petr Salinger, Pavel Tvrdík
Venue: Journal of Parallel and Distributed Computing (2006)

In this paper, we consider the problem of one-to-all broadcast (OAB) in an interconnection network with the topology of the n-dimensional cube-connected cycles, CCCn, under the following conditions. Routers use distance insensitive switching, e.g., wormhole. A OAB proceeds in rounds that consist of message passing between pairs of nodes using disjoint paths. Routers also have all-output-port functionality, i.e., they can send a packet via all output ports simultaneously. In CCCn, this assumption implies that the lower bound on the number rounds of the OAB is log4(|V(CCCn)|). The main result of this paper is an algorithm for the OAB in CCCn whose number of rounds is greater than the lower bound by at most 1 for all n < 123. The algorithm is depth-contention-free and therefore, it works correctly even if nodes participating in the broadcast run asynchronously. We also show how to make the algorithm deadlock-free.
To Approach Minimum Losses of the Distribution Systems by Artificial Neural Networks
Authors: Yen-Ming Tzeng, Shu-Yao Ho
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Loss reduction of distribution system can perform the switching operation to make feeder reconfiguration. First, we get the feeder hourly loading by considering the weather information and feeder historical load data or by SCADA System. Second, we determine current flow of each feeder section according to the load composition of residential, commercial and industrial customers. Third, By Using the unsupervisory self-organize mapping Network (SOM) to classify the section current combination, the network can not through training process. Finally, the supervisory neural network of back-propagation (BP) is used to derive the optimal feeder reconfiguration to reduce feeder loss, and the network must be through by training process till the network converged. With the proposed neural network, it can be applied to the real time system, to reduce the feeder loss of power distribution system by quickly and efficiently to get the switching status.
MDPOP: faithful distributed implementation of efficient social choice problems
Authors: Adrian Petcu, Boi Faltings, David C. Parkes
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We model social choice problems in which self interested agents with private utility functions have to agree on values for a set of variables subject to side constraints. The goal is to implement the efficient solution, maximizing the total utility across all agents. Existing techniques for this problem fall into two groups. Distributed constraint optimization algorithms can find the solution without any central authority but are vulnerable to manipulation. Incentive compatible mechanisms can ensure that agents report truthful information about their utilities and prevent manipulation of the outcome but require centralized computation.Following the agenda of distributed implementation [16], we integrate these methods and introduce MDPOP, the first distributed optimization protocol that faithfully implements the VCG mechanism for this problem of efficient social choice. No agent can benefit by unilaterally deviating from any aspect of the protocol, neither information-revelation, computation, nor communication. The only central authority required is a bank that can extract payments from agents. In addition, we exploit structure in the problem and develop a faithful method to redistribute some of the VCG payments back to agents. Agents need only communicate with other agents that have an interest in the same variable, and provided that the distributed optimization itself scales the entire method scales to problems of unbounded size.
Learning Shape Correspondence for n-D curves
Authors: Alain Pitiot, Hervé Delingette, Paul M. Thompson
Venue: International Journal of Computer Vision (2007)

We present a learning method that introduces explicit knowledge into the shape correspondence problem. Given two input curves to be matched, our approach establishes a dense correspondence field between them, where the characteristics of the matching field closely resemble those in an a priori learning set. We build a shape distance matrix from the values of a shape descriptor computed at every point along the curves. This matrix embeds the correspondence problem in a highly expressive and redundant construct and provides the basis for a pattern matching strategy for curve matching. We selected the previously introduced observed transport measure as a shape descriptor, as its properties make it particularly amenable to the matching problem. Synthetic and real examples are presented along with discussions of the robustness and applications of the technique.
Detecting outliers using transduction and statistical testing
Authors: Daniel Barbará, Carlotta Domeniconi, James P. Rogers
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, most of the algorithms proposed in the literature are based on a particular definition of outliers (e.g., density-based), and use ad-hoc thresholds to detect them. In this paper we present a novel technique to detect outliers with respect to an existing clustering model. However, the test can also be successfully utilized to recognize outliers when the clustering information is not available. Our method is based on Transductive Confidence Machines, which have been previously proposed as a mechanism to provide individual confidence measures on classification decisions. The test uses hypothesis testing to prove or disprove whether a point is fit to be in each of the clusters of the model. We experimentally demonstrate that the test is highly robust, and produces very few misdiagnosed points, even when no clustering information is available. Furthermore, our experiments demonstrate the robustness of our method under the circumstances of data contaminated by outliers. We finally show that our technique can be successfully applied to identify outliers in a noisy data set for which no information is available (e.g., ground truth, clustering structure, etc.). As such our proposed methodology is capable of bootstrapping from a noisy data set a clean one that can be used to identify future outliers.
IRKC: an IMEX solver for stiff diffusion-reaction PDEs
Authors: L. F. Shampine, B. P. Sommeijer, J. G. Verwer
Venue: Journal of Computational and Applied Mathematics (2006)

The Fortran 90 code IRKC is intended for the time integration of systems of partial differential equations (PDEs) of diffusion-reaction type for which the reaction Jacobian has real (negative) eigenvalues. It is based on a family of implicit-explicit Runge-Kutta-Chebyshev methods which are unconditionally stable for reaction terms and which impose a stability constraint associated with the diffusion terms that is quadratic in the number of stages. Special properties of the family make it possible for the code to select at each step the most efficient stable method as well as the most efficient step size. Moreover, they make it possible to apply the methods using just a few vectors of storage. A further step towards minimal storage requirements and optimal efficiency is achieved by exploiting the fact that the implicit terms, originating from the stiff reactions, are not coupled over the spatial grid points. Hence, the systems to be solved have a small dimension (viz., equal to the number of PDEs). These characteristics of the code make it especially attractive for problems in several spatial variables. IRKC is a successor to the RKC code [B.P. Sommeijer, L.F. Shampine, J.G. Verwer, RKC: an explicit solver for parabolic PDEs, J. Comput. Appl. Math. 88 (1997) 315-326] that solves similar problems without stiff reaction terms.
Integration Testing of Components Guided by Incremental State Machine Learning
Authors: Keqin Li, Roland Groz, Muzammil Shahbaz
Venue: Proceedings of the Testing: Academic & Industrial Conference on Practice And Research Techniques (2006)

The design of complex systems, e.g., telecom services, is nowadays usually based on the integration of components (COTS), loosely coupled in distributed architectures. When components come from third party sources, their internal structure is usually unknown and the documentation is insufficient. Therefore, the system integrator faces the problem of providing a required system assembling COTS whose behaviour is barely specified and for which no model is usually available. In this paper, we address the problem of integration testing of COTS. It combines test generation techniques with machine learning algorithms. Statebased models of components are built from observed behaviours. The models are alternatively used to generate tests and extended to take into account observed behaviour. This process is iterated until a satisfactory level of confidence in testing is achieved.
Relating the bilinear distributions and the evolutionary spectrum
Authors: C. S. Detka, A. El-Jaroudi, L. F. Chaparro
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

The authors present the theoretical relationship connecting the short time Fourier transform (STFT), the class of bilinear distributions (BDs) and the evolutionary periodogram to the Wold-Cramer evolutionary spectrum. They show that the STFT and the BD can be viewed as estimators of the evolutionary spectrum, thereby allowing comparison of the various estimators. A further comparison of the estimators is achieved by means of measures such as window bandwidth and computational complexity. An example is given to illustrate the performance of the differences estimators, and some of the advantages of the evolutionary periodogram over the other estimators.
Bayesian Stopping Rules for Greedy Randomized Procedures
Authors: Carlotta Orsenigo, Carlo Vercellis
Venue: Journal of Global Optimization (2006)

A greedy randomized adaptive search procedure (GRASP) is proposed for the approximate solution of general mixed binary programming problems (MBP). Examples are provided of practical applications that can be formulated as MBP requiring the solution of a large number of problem instances. This justifies, from both a practical and a theoretical perspective, the development of stopping rules aimed at controlling the number of iterations in a GRASP. To this end, a bayesian framework is laid down, two different prior distributions are proposed and stopping conditions are explicitly derived in analytical form. Numerical evidence shows that the stopping rules lead to an optimal trade-off between accuracy and computational effort, saving from unneeded iterations and still achieving good approximations.
Analog Data Acquisition for Obtaining I-V Characteristics Using Sound Cards
Authors: Aasim Azooz
Venue: Computing in Science and Engineering (2006)

The author describes a method to obtain voltage and current data to plot the I-V characteristics of a semiconductor diode and a plasma Langmuir probe glow discharge using Matlab's data-acquisition feature and a computer sound card.
A Change of Landscape and a Broadened Scope
Authors: Norman Chonacky
Venue: Computing in Science and Engineering (2006)

I've promised you that CiSE would be broadening its scope during my term as editor in chief, and this issue marks the start of a new chapter in this effort. Sometimes, in seeking the new, we re-encounter the old in the course of our exploration and are surprised by what we've learned.
Formative assessment: reducing math phobia and related test anxiety in a geology class for non-science majors
Authors: Vanessa Svihla
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Math and test anxiety are common in science classes for non-science majors. Formative assessment was used to prepare such students for exams. This included weekly quizzes that were challenging, graded harshly, and completely correctable (corrected grade completely replaced original grade). By the midterm, 100% of the students mastered rate calculations, and when retested at the final, 80% of the students retained the ability to solve the rate calculations. Students also reported feeling less math phobic.
Standardized Virtual Reality, Are We There Yet?
Authors: Mario A. Gutierrez A., Frederic Vexo, Daniel Thalmann
Venue: Proceedings of the 2006 International Conference on Cyberworlds (2006)

Despite its history of several decades and impressive achievements, developing a VR application is still a complex task. Setting-up a Virtual Environment requires choosing a suitable combination of elements from a large amount of technologies, software frameworks, animation/modeling formats and many other components. In this paper we present an overview of the efforts focused on defining a commonly accepted set of specifications -standards- for the multiple "ingredients" of a VR application. Our analysis of current and previous initiatives provides elements to answer the question about whether or not we can talk about "standard VR".
Fully Automatic Facial Action Unit Detection and Temporal Analysis
Authors: Michel Valstar, Maja Pantic
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this work we report on the progress of building a system that enables fully automated fast and robust facial expression recognition from face video. We analyse subtle changes in facial expression by recognizing facial muscle action units (AUs) and analysing their temporal behavior. By detecting AUs from face video we enable the analysis of various facial communicative signals including facial expressions of emotion, attitude and mood. For an input video picturing a facial expression we detect per frame whether any of 15 different AUs is activated, whether that facial action is in the onset, apex, or offset phase, and what the total duration of the activation in question is. We base this process upon a set of spatio-temporal features calculated from tracking data for 20 facial fiducial points. To detect these 20 points of interest in the first frame of an input face video, we utilize a fully automatic, facial point localization method that uses individual feature GentleBoost templates built from Gabor wavelet features. Then, we exploit a particle filtering scheme that uses factorized likelihoods and a novel observation model that combines a rigid and a morphological model to track the facial points. The AUs displayed in the input video and their temporal segments are recognized finally by Support Vector Machines trained on a subset of most informative spatio-temporal features selected by AdaBoost. For Cohn-Kanade andMMI databases, the proposed system classifies 15 AUs occurring alone or in combination with other AUs with a mean agreement rate of 90.2% with human FACS coders.
Distribution of path durations in mobile ad-hoc networks: Palm's theorem to the rescue
Authors: Yijie Han, Richard J. La, Armand M. Makowski, Seungjoon Lee
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2006)

We first study the distribution of path duration in multi-hop wireless networks. We show that as the number of hops along a path increases, the path duration distribution can be accurately approximated by an exponential distribution under a set of mild conditions, even when the link duration distributions are not identical. Then, we develop an approximate model for computing the distribution of link duration under a Random Waypoint (RWP) mobility model, and demonstrate that the path duration distribution converges to an exponential distribution with increasing number of hops. Simulation results obtained using ns-2 simulator are provided to validate the analysis.
A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics
Authors: Kamal E. Melkemi, Mohamed Batouche, Sebti Foufou
Venue: Pattern Recognition Letters (2006)

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.
A Sampling Method Focusing on Practicality
Authors: Daniel Gracia Perez, Hugues Berry, Olivier Temam
Venue: IEEE Micro (2006)

This sampling technique, which is hardware-independent and almost entirely transparent to the user, employs a budget-based approach that jointly considers warm-up and sampling costs, presents them as a single parameter to the user, and distributes simulated instructions between warm-up and sampling based on region partitioning and clustering information. Although it focuses on practicality, the technique delivers nearly state-of-the-art speed and accuracy.