ppxscal/embedding_network huggingface dataset:
Should we model dependence and nonstationarity, and if so how?
Authors: Shane G. Henderson
Venue: Proceedings of the 37th conference on Winter simulation (2005)

It can be difficult to develop, fit to data, and generate from, models that capture dependence and/or nonstationarity in simulation inputs. Should we bother? How should we go about it? I will discuss these issues, focusing on three examples: call center arrivals, ambulance travel speeds and wind modeling for America's Cup races.
A nonlinear analytical model for quantization effects in the LMS algorithm with power-of-two step size
Authors: J. C. M. Bermudez, N. J. Bershad
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The least mean squares (LMS) algorithm is one of the most popular algorithms for digital implementation of real-time high-speed adaptive filters. This paper presents a study of the quantization effects in the finite precision LMS algorithm with power-of-two step sizes. Nonlinear recursions are derived for the mean and second moment matrix of the weight vector about the Wiener weight for white Gaussian data models and small algorithm step size /spl mu/. The solutions of these recursions are shown to agree very closely with the Monte Carlo simulations during all phases of the adaptation process. A design curve is presented to demonstrate the use of the theory to select the number of quantizer bits and the adaptation step size /spl mu/ to yield desired transient and steady-state behaviors.
Vision from the Top
Authors: Kwang-Ting (Tim) Cheng
Venue: IEEE Design Test (2006)

A popular DATE keynote speaker and an award-winning author are among the contributors to this issue, which covers on-chip testing, the sociology of EDA, quiescent-signal analysis, and a survey of test vector compression techniques.
Structure and View Estimation for Tomographic Reconstruction: A Bayesian Approach
Authors: Satya P. Mallick, Sameer Agarwal, David J. Kriegman, Serge J. Belongie, Bridget Carragher, Clinton S. Potter
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

This paper addresses the problem of reconstructing the density of a scene from multiple projection images produced by modalities such as x-ray, electron microscopy, etc. where an image value is related to the integral of the scene density along a 3D line segment between a radiation source and a point on the image plane. While computed tomography (CT) addresses this problem when the absolute orientation of the image plane and radiation source directions are known, this paper addresses the problem when the orientations are unknown - it is akin to the structure-from-motion (SFM) problem when the extrinsic camera parameters are unknown. We study the problem within the context of reconstructing the density of protein macro-molecules in Cryogenic Electron Microscopy (cryo-EM), where images are very noisy and existing techniques use several thousands of images. In a non-degenerate configuration, the viewing planes corresponding to two projections, intersect in a line in 3D. Using the geometry of the imaging setup, it is possible to determine the projections of this 3D line on the two image planes. In turn, the problem can be formulated as a type of orthographic structure from motion from line correspondences where the line correspondences between two views are unreliable due to image noise. We formulate the task as the problem of denoising a correspondence matrix and present a Bayesian solution to it. Subsequently, the absolute orientation of each projection is determined followed by density reconstruction. We show results on cryo-EM images of proteins and compare our results to that of Electron Micrograph Analysis (EMAN) -a widely used reconstruction tool in cryo-EM.
Pattern puzzle: a metaphor for visualizing software complexity measures
Authors: Adam Ghandar, A. S. M. Sajeev, Xiaodi Huang
Venue: Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60 (2006)

Software systems have become increasingly complex over the years. Complexity metrics measures software complexity using real numbers. It is, however, hard to gain insight into different complexities by looking at these numbers. In this paper, we present a software complexity metaphor that uses a jigsaw puzzle. In particular, each component of a software system is modelled as a piece of a jigsaw puzzle. The problem complexity is modelled as a pattern on the surface of the piece, and the interconnection complexity as connectors between puzzle pieces. We demonstrate the benefits of this approach using case studies of the complexity measures of a real software system.
How equitable is rational negotiation?
Authors: Sylvia Estivie, Yann Chevaleyre, Ulle Endriss, Nicolas Maudet
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Notions of fairness have recently received increased attention in the context of resource allocation problems, pushed by diverse applications where not only pure utilitarian efficiency is sought. In this paper, we study a framework where allocations of goods result from distributed negotiation conducted by autonomous agents implementing very simple deals. Assuming that these agents are strictly self-interested, we investigate how equitable the outcomes of such negotiation processes are. We first discuss a number of methodological issues raised by this study, pertaining in particular to the design of suitable payment functions as a means of distributing the social surplus generated by a deal amongst the participating agents. By running different experiments, we finally identify conditions favouring equitable outcomes.
Kriging interpolation in simulation: a survey
Authors: Wim C. M. van Beers, Jack P. C. Kleijnen
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Many simulation experiments require much computer time, so they necessitate interpolation for sensitivity analysis and optimization. The interpolating functions are 'metamodels' (or 'response surfaces') of the underlying simulation models. Classic methods combine low-order polynomial regression analysis with fractional factorial designs. Modern Kriging provides 'exact' interpolation, i.e., predicted output values at inputs already observed equal the simulated output values. Such interpolation is attractive in deterministic simulation, and is often applied in Computer Aided Engineering. In discrete-event simulation, however, Kriging has just started. Methodologically, a Kriging metamodel covers the whole experimental area; i.e., it is global (not local). Kriging often gives better global predictions than regression analysis. Technically, Kriging gives more weight to 'neighboring' observations. To estimate the Kriging metamodel, space filling designs are used; for example, Latin Hypercube Sampling (LHS). This paper also presents novel, customized (application driven) sequential designs based on cross-validation and bootstrapping.
Understandable models Of music collections based on exhaustive feature generation with temporal statistics
Authors: Fabian Moerchen, Ingo Mierswa, Alfred Ultsch
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Data mining in large collections of polyphonic music has recently received increasing interest by companies along with the advent of commercial online distribution of music. Important applications include the categorization of songs into genres and the recommendation of songs according to musical similarity and the customer's musical preferences. Modeling genre or timbre of polyphonic music is at the core of these tasks and has been recognized as a difficult problem. Many audio features have been proposed, but they do not provide easily understandable descriptions of music. They do not explain why a genre was chosen or in which way one song is similar to another. We present an approach that combines large scale feature generation with meta learning techniques to obtain meaningful features for musical similarity. We perform exhaustive feature generation based on temporal statistics and train regression models to summarize a subset of these features into a single descriptor of a particular notion of music. Using several such models we produce a concise semantic description of each song. Genre classification models based on these semantic features are shown to be better understandable and almost as accurate as traditional methods.
Audio-Visual Foreground Extraction for Event Characterization
Authors: Marco Cristani, Manuele Bicego, Vittorio Murino
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

This paper presents a new method able to integrate audio and visual information for scene analysis in a typical surveillance scenario, using only one camera and one monaural microphone. Visual information is analyzed by a standard visual background/foreground (BG/FG) modelling module, enhanced with a novelty detection stage, and coupled with an audio BG/FG modelling scheme. The audiovisual association is performed on-line, by exploiting the concept of synchrony. Experimental tests carrying out classification and clustering of events show all the potentialities of the proposed approach, also in comparison with the results obtained by using the single modalities.
Knowledge Awareness Map in Mobile Language-Learning
Authors: Hiroaki Ogata, Moushir M. El-Bishouty, Yoneo Yano
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The challenge in an information-rich world is not only to make information available to people at any time, at any place, and in any form, but specifically to say the right thing at the right time in the right way[1]. A ubiquitous and mobile computing environment enables people to learn at any time and any place. Nevertheless, the fundamental issue is how to provide learners with the right information at the right time in the right way. This paper tackles the issues of right time and right place learning (RTRPL) in a ubiquitous computing environment.
Integration of the FreeBSD TCP/IP-stack into the discrete event simulator OMNet++
Authors: Roland Bless, Mark Doll
Venue: Proceedings of the 36th conference on Winter simulation (2004)

The discrete event simulator OMNeT++, that is programmed in C++, shows a steady growing popularity. Due to its well-structured nature, it is easy to understand and easy to use. A shortcoming of it, however, is the limited number of available simulation models. Especially, for network simulations a validated TCP implementation was missing. In order to avoid a re-implementation of a full-featured TCP, including all potential implementation errors and costly validation tests, we integrated a TCP/IP stack of a real operating system into OMNeT++. In this paper we show that such a port is feasible with reasonable effort and we describe difficulties of the integration process as well as the applied solutions. We also present some evaluation results that outline memory and CPU usage.
Split-Second Sequential Selective Activation in Human Secondary Visual Cortex
Authors: J. Leon Kenemans, Marijn Lijffijt, Gert Camfferman, Marinus N. Verbaten
Venue: Journal of Cognitive Neuroscience (2002)

This work addressed early selection based on nonspatial visual features, using event-related potentials (ERPs) with high temporal resolution and dipole-source modeling. Subjects were presented rapid sequences of gratings varying in spatial frequency and orientation, and were instructed to attend to gratings with one spatial frequency and ignore those with another. Attention effects started at 120-msec latency as anterior positivity and proceeded as posterior negativity (200 msec) and anterior negativity (265 msec). Dipole-source modeling suggested that these effects reflect the sequential selective activation of, on average, posterior dorsal-medial, posterior ventral-lateral, and anterior medial cortical areas. In contrast, stimulus-specific activity was observed well before 100-msec latency and characterized by dipoles with locations significantly posterior to those of the attention-modulated activity. These results indicate that even with highly discriminable spatial frequencies, selection is not as early as before the 100-msec latency, unlike what is often found for location selection. It is also separated in time and anatomically from the earliest stimulus-specific cortical activity. Reducing discriminability of the selection feature resulted in longer selection latencies, becoming manifest only at 175 msec as an apparent combination of posterior and anterior negativities, and in an elevated criterion for overt responding.
Face Detection Based on Complexional Segmentation and Feature Extraction
Authors: Qian Zhang, Zhi-Jing Liu
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

Face Detection is one of the most pop researches in image processing and pattern recognition. It is the foundation of human face recognition. It also has very important values in practice application such as video surveillance, intelligence human-computer interaction and circumstance security. In this paper, we discuss the face detection method using complexional segmentation algorithm to separate a human face from background and finally extract the feature in the possible facial regions to accurately locate human face. This method is not only fit for single- face images but also the multiface images under complex environment. The experimental result efficiently demonstrates the success of this method in face detection.
Exact linearization and sliding mode observer for a quadrotor unmanned aerial vehicle
Authors: A. Mokhtari, A. Benallegue, Y. Orlov
Venue: International Journal of Robotics and Automation (2006)

In this paper, a feedback linearization-based controller with a sliding mode observer running parallel is applied to a quadrotor unmanned aerial vehicle. An adaptive estimator is added to the overall system to estimate the effect of external disturbances such as wind. The whole observer-estimator-control law constitutes an original approach to vehicle regulation with minimal number of sensors. Performance issues of the controller are illustrated in a simulation study that takes into account parameter uncertainties and external disturbances as well as measurement noise.
Image Matching Using Photometric Information
Authors: Michael Kolomenkin, Ilan Shimshoni
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Image matching is an essential task in many computer vision applications. It is obvious that thorough utilization of all available information is critical for the success of matching algorithms. However most popular matching methods do not incorporate effectively photometric data. Some algorithms are based on geometric, color invariant features, thus completely neglecting available photometric information. Others assume that color does not differ significantly in the two images; that assumption may be wrong when the images are not taken at the same time, for example when a recently taken image is compared with a database. This paper introduces a method for using color information in image matching tasks. Initially the images are segmented using an off-the-shelf segmentation process (EDISON). No assumptions are made on the quality of the segmentation. Then the algorithm employs a model for natural illumination change to define the probability of two segments to originate from the same surface. When additional information is supplied (for example suspected corresponding point features in both images), the probabilities are updated. We show that the probabilities can easily be utilized in any existing image matching system. We propose a technique to make use of them in a SIFT-based algorithm. The technique's capabilities are demonstrated on real images, where it causes a significant improvement in comparison with the original SIFT results in the percentage of correct matches found.
Business Service Network Design: From Business Model to an Integrated Multi-Partner Business Transaction.
Authors: Bertrand Gregoire, Michael Schmitt
Venue: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (2006)

This article presents a framework to design a business service network (BSN) in-line with a given business model. Particular emphasis is on the use of industry specific standards, existing business process components and best practices. Based on a sample business model for a brokerage service in the tourism sector, a multi-partner business transaction is designed. At each stage, the various factors that guide the decision-making are discussed.
Bluetooth content distribution stations on public transit
Authors: Jason LeBrun, Chen-Nee Chuah
Venue: Proceedings of the 1st international workshop on Decentralized resource sharing in mobile computing and networking (2006)

In this poster, we introduce our Bluespots project, in which a small computer on a bus serves as a Bluetooth Content Distribution (BCD) station in a university public transit scenario.
Learning a manifold-constrained map between image sets: applications to matching and pose estimation
Authors: Jihun Ham, Ikkjin Ahn, Daniel Lee
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

This paper proposes a method for matching two sets of images given a small number of training examples by exploiting the underlying structure of the image manifolds. A nonlinear map from one manifold to another is constructed by combining linear maps locally defined on the tangent spaces of the manifolds. This construction imposes strong constraints on the choice of the maps, and makes possible good generalization of correspondences between all of the image sets. This map is flexible enough to approximate an arbitrary diffeomorphism between manifolds and can serve many purposes for applications. The underlying algorithm is a non-iterative efficient procedure whose complexity mainly depends on the number of matched training examples and the dimensionality of the manifold, and not on the number of samples nor on the dimensionality of the images. Several experiments were performed to demonstrate the potential of our method in image analysis and pose estimation. The first example demonstrates how images from a rotating camera can be mapped to the underlying pose manifold. Second, computer generated images from articulating toy figures are matched using the underlying 4 dimensional manifold to generate image-driven animations. Finally, two sets of actual lip images during speech are matched by their appearance manifold. In all these cases, our algorithm is able to obtain reasonable matches between thousands of large-dimensional images, with a minimum of computation.
Character repertoires, ordering and assignment to the 12-key keypad supporting European cultural diversity
Authors: Martin Böcker, Karl Ivar Larsson, Bruno von Niman
Venue: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services (2006)

ETSI, the European Telecommunications Standards Institute, has published a standard (ES 202 130) in 2003 that specifies the character repertoires and assignment of characters to the 12-key telephone keypad for a range of European languages. The standard for letters, digits and special characters (such as the Euro symbol and punctuation marks) covered the official languages of the EU and EFTA members, Russia, as well as countries with applicant status for the EU at that time. This paper describes the further development of the standard to cover other major languages spoken in Europe including official languages, minority languages and immigrants' languages.
Intrusion Detection based on Grid
Authors: Fang-Yie Leu, Ming-Chang Li, Jia-Chun Lin
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

In this article, we propose a fault-tolerant and grid-based IDS, named Fault-tolerant Grid Intrusion Detection System (FGIDS) which exploits grid's dynamic and abundant computing resources to detect malicious behaviors from a massive amount of network packets. In FGIDS, a detector can dynamically leave or join FGIDS anytime. A newly joined one is tested to obtain its key features' performance curves, which are used to balance detection workload among detectors. When a detector due to some reasons can not continue its detection leaving an unfinished task, FGIDS allocates another available one to take over. Therefore the drawbacks ordinary security systems have experienced can be then eliminated.
A TVD-type method for 2D scalar Hamilton-Jacobi equations on unstructured meshes
Authors: Lingyan Tang, Songhe Song
Venue: Journal of Computational and Applied Mathematics (2006)

In this paper, a TVD-type difference scheme which satisfies maximum principle is developed for 2D scalar Hamilton-Jacobi equations on unstructured triangular meshes. The main ideas are node-based approximations and derivative-limited reconstruction with quadratic interpolation polynomial. The solution's slope satisfies maximum principle. Numerical experiments are performed to demonstrate high-order accuracy in smooth fields and good resolution of derivative singularities. The new method is simpler than WENO.
Gaussian elimination: a case study in efficient genericity with MetaOCaml
Authors: Jacques Carette
Venue: Science of Computer Programming (2006)

The Gaussian Elimination algorithm is in fact an algorithm family -- common implementations contain at least six (mostly independent) "design choices". A generic implementation can easily be parametrized by all these design choices, but this usually leads to slow and bloated code. Using MetaOCaml's staging facilities, we show how we can produce a natural and type-safe implementation of Gaussian Elimination which exposes its design choices at code-generation time, so that these choices can effectively be specialized away, and where the resulting code is quite efficient.
Auctioning transformable goods
Authors: Andrea Giovannucci, Juan A. Rodríguez-Aguilar, Jesúus Cerquides
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper we explore whether an auctioneer/buyer may benefit from introducing his transformability relationships (some goods can be transformed into others at a transformation cost) into multi-unit combinatorial reverse auctions. Thus, we quantitatively assess the potential savings the auctioneer/buyer may obtain with respect to combinatorial reverse auctions that do not consider tranformability relationships.
Competing sellers in online markets: reserve prices, shill bidding, and auction fees
Authors: Enrico H. Gerding, Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we consider competition between sellers offering similar items in concurrent online auctions, where each seller must set its individual auction parameters (such as the reserve price) in such a way as to attract buyers. We show that there exists a pure Nash equilibrium in the case of two sellers with asymmetric production costs. In addition, we show that, rather than setting a reserve price, a seller can further improve its utility by shill bidding (i.e., pretending to be a buyer in order to bid in its own auction). But, using an evolutionary simulation, we show that this shill bidding introduces inefficiences within the market. However, we then go on to show that these inefficiences can be reduced when the mediating auction institution uses appropriate auction fees that deter sellers from submitting shill bids.