ppxscal/embedding_network huggingface dataset:
Modeling tool failures in semiconductor FAB simulation
Authors: Oliver Rose
Venue: Proceedings of the 36th conference on Winter simulation (2004)

In this research, we investigate how well Weibull, Gamma, and special bimodal distribution are suited as an alternative to the exponential distribution approach in the stochastic modeling of machine downtimes and times between failures. We also discuss the question whether sampling shop-floor data should not only include first order statistics, but also measures that allow to monitor and model the variability of the equipment and processes and even the correct distribution of the data.
A new call admission control scheme based on mobile position estimation in DS-CDMA systems
Authors: Tuna Tugcu, Cem Ersoy
Venue: Wireless Networks (2005)

Call dropping is considered more annoying than call blocking in wireless cellular networks. The cost of the classical method of employing guard channels to decrease the call dropping rate is the increase in call blocking rate. Since subscriber mobility changes in time, the number of handoff attempts in each cell is subject to fluctuations, making static assignments (or periodical update) of a given number of guard channels inefficient. In this paper, we propose an adaptive scheme that employs reservations, instead of static assignments, to adaptively adjust the number of guard channels in each cell according to the current requirements. Thus, unnecessary allocation of guard channels is avoided resulting in a lower cost in terms of call dropping. The reservation requests are made according to the recent mobility pattern of the subscriber. A likelihood value is associated with each reservation request so that fewer channels are reserved by benefiting from the statistical accumulation of the requests. The channels are reserved by considering the interference that would be created once they are in use. The proposed scheme is evaluated against the classical guard channel scheme with a realistic mobility model.
Kalman filtering in pairwise Markov trees
Authors: François Desbouvries, Jean Lecomte, Wojciech Pieczynski
Venue: Signal Processing (2006)

An important problem in multiresolution analysis of signals or images consists in estimating hidden random variables x={x"s}"s"@?"S from observed ones y={y"s}"s"@?"S. This is done classically in the context of hidden Markov trees (HMT). HMT have been extended recently to the more general context of pairwise Markov trees (PMT). In this note, we propose an adaptive filtering algorithm which is an extension to PMT of the Kalman filter (KF).
Projected clustering for categorical datasets
Authors: Minho Kim, R. S. Ramakrishna
Venue: Pattern Recognition Letters (2006)

This paper deals with the problem of clustering categorical datasets. Categorical data typically suffer from limited measuring levels and exhibit sparsity in a space of very high dimension. Conventional dissimilarity measures are, therefore, inadequate. We propose a new clustering algorithm based on projected clustering. The proposed algorithm, although hierarchical in essence, avoids the characteristic error propagation through reassignment and deletion of bad clusters. We also propose new indices for cluster validation in categorical datasets, an area that is almost unexplored. We present techniques for finding optimal number of clusters, and for initialization of centers of clusters. Experimental results demonstrate the effectiveness of the proposed clustering algorithm. The cluster validation for categorical datasets is also shown to be quite efficient.
Combining Multiple Clustering Methods Based on Core Group
Authors: Tian-yang Lv, Shao-bin Huang, Xi-zhe Zhang, Zheng-xuan Wang
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

As an unsupervised technique, clustering analysis has been widely applied in various fields. However, it is usually difficult to select an appropriate clustering method for an application, while no clustering method is suitable for all situations. This paper proposes a novel method to combine multiple clustering methods. First, the paper combines different agglomerative hierarchical methods in one clustering process to obtain core groups. Core group refers to the data that are always clustered together no matter what clustering method is applied. Then, it adopts other kind of clustering methods to refine the core groups and index database. In addition to conduct a series of experiments on the datasets from UCI, the paper applies the proposed method in a new research field, 3D model retrieval, to analyze and index the 3D model database.
Robust Statistical Estimation and Segmentation of Multiple Subspaces
Authors: Allen Y. Yang, Shankar R. Rao, Yi Ma
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We study the problem of estimating a mixed geometric model of multiple subspaces in the presence of a significant amount of outliers. The estimation of multiple subspaces is an important problem in computer vision, particularly for segmenting multiple motions in an image sequence. We first provide a comprehensive survey of robust statistical techniques in the literature, and identify three main approaches for detecting and rejecting outliers. Through a careful examination of these approaches, we propose and investigate three principled methods for robustly estimating mixed subspace models: random sample consensus, the influence function, and multivariate trimming. Using a benchmark synthetic experiment and a set of real image sequences, we conduct a thorough comparison of the three methods
Deconvolution of Event-Related fMRI Responses in Fast-Rate Experimental Designs: Tracking Amplitude Variations
Authors: Hermann Hinrichs, Michael Scholz, Claus Tempelmann, Martin G. Woldorff, Anders M. Dale, Hans-Jochen Heinze
Venue: Journal of Cognitive Neuroscience (2000)

Recent developments towards event-related functional magnetic resonance imaging has greatly extended the range of experimental designs. If the events occur in rapid succession, the corresponding time-locked responses overlap significantly and need to be deconvolved in order to separate the contributions of different events. Here we present a deconvolution approach, which is especially aimed at the analysis of fMRI data where sequence- or context-related responses are expected. For this purpose, we make the assumption of a hemodynamic response function (HDR) with constant yet not predefined shape but with possibly variable amplitudes. This approach reduces the number of variables to be estimated but still keeps the solutions flexible with respect to the shape. Consequently, statistical efficiency is improved. Temporal variations of the HDR strength are directly indicated by the amplitudes derived by the algorithm. Both the estimation efficiency and statistical inference are further supported by an improved estimation of the noise covariance. Using synthesized data sets, both differently shaped HDRs and varying amplitude factors were correctly identified. The gain in statistical sensitivity led to improved ratios of false- and true-positive detection rates for synthetic activations in these data. In an event-related fMRI experiment with a human subject, different HDR amplitudes could be derived corresponding to stimulation at different visual stimulus contrasts. Finally, in a visual spatial attention experiment we obtained different fMRI response amplitudes depending on the sequences of attention conditions.
A Directed Graph-Based Authentication Protocol Model and Its Security Analysis
Authors: Hong-bo Xie, Yuan-chen Wu, Ming-tian Zhou
Venue: Proceedings of the Japan-China Joint Workshop on Frontier of Computer Science and Technology (2006)

The formal description of authentication protocol and its security analysis is one of the important issues in the protocol analysis. In order to solve the problem in the formal description of cryptographic protocol, a method based on directed graph is presented to formally depict the authentication protocol specification. Meanwhile, a converse-searching algorithm based on directed graph is also presented to construct the protocol messages. When this method is used to analyze WOO-LAM authentication, a new flow and its attacking trace have been founded.
Robust recursive estimation for linear systems with non-Gaussian state and measurement noises
Authors: P. M. Djuric, Byung-Gook Lee, Souguil Ann, Iickho Song
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

In many applications we have to deal with densities which are highly non-Gaussian or which may have Gaussian shape in the middle but have potent deviations in the tails. To fight against this deviation, we consider Bayesian estimation in the case of non-Gaussian state and measurement noises. The robust estimation problem for linear discrete-time systems is considered here. The non-Gaussian noises are modeled as a mixture. We present a robust recursive estimation model that is an approximate minimum variance estimator with a maximum a posteriori (MAP) decision rule for determining the noise sequence distribution.
Resolving small-scale structures in Boussinesq convection by adaptive grid methods
Authors: Zhengru Zhang, Tao Tang
Venue: Journal of Computational and Applied Mathematics (2006)

Inviscid Boussinesq convection is a challenging problem both analytically and numerically. Due to the complex dynamic development of small scales and the rapid loss of solution regularity, the Boussinesq convection pushes any numerical strategy to the limit. In E and Shu (Phys. Fluids 6 (1994) 49), a detailed numerical study of the Boussinesq convection in the absence of viscous effects is carried out using filtered pseudospectral method and a high-order accurate ENO schemes. In their computations, very fine grids have to be used in order to resolve the small-structures of the Boussinesq fluid. In this work, we will develop an efficient adaptive grid method for solving the inviscid incompressible flows, which can be useful in resolving extremely small-structures with reasonably small number of grid points. To demonstrate the effectiveness of the proposed method, the Boussinesq convection problem will be computed using the adaptive grid method.
A Generic Camera Model and Calibration Method for Conventional, Wide-Angle, and Fish-Eye Lenses
Authors: Juho Kannala, Sami S. Brandt
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

Fish-eye lenses are convenient in such applications where a very wide angle of view is needed, but their use for measurement purposes has been limited by the lack of an accurate, generic, and easy-to-use calibration procedure. We hence propose a generic camera model, which is suitable for fish-eye lens cameras as well as for conventional and wide-angle lens cameras, and a calibration method for estimating the parameters of the model. The achieved level of calibration accuracy is comparable to the previously reported state-of-the-art.
From HTML documents to web tables and rules
Authors: Kai Simon, Georg Lausen, Harold Boley
Venue: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet (2006)

We present a browser-extending Semantic Web extraction system that maps HTML documents to tables and, where possible, to rules. First, the basic data extractor ViPER distills and reorganizes semi-structured information into a tabular data structure, which can again be browsed and/or submitted to further machine processing. Second, exemplifying the latter, the extended knowledge extractor Rex ViPER mines the resulting tables for structural properties and functional dependencies. Rules are generated to obtain a more compact and manageable, often also enriched, knowledge representation. The resulting fully structured information, RuleML-serialized facts and rules, can be stored along with the orginal documents, queried by rule engines such as OO jDREW and FLORID, and interchanged between Web Services. Thus Rex ViPER contributes to automating the construction of a machine-processable Semantic Web.
Proceedings of the 1999 conference on Computer support for collaborative learning
Authors: Christopher M. Hoadley, Jeremy Roschelle
Venue: Computer Support for Collaborative Learning (1999)

You are cordially invited to participate in and attend Computer Support for Collaborative Learning '99, to be held at the Stanford University, Stanford California USA on December 12-15, 1999. CSCL '99 is the third international conference devoted to the exploration of the roles for technology in collaborative forms of learning and teaching. Participation in this conference is invited from designers, educators, researchers, and students in a diverse set of disciplines including: education, cognitive and educational psychology, didactics, computer science, anthropology, sociology, s peech communication, semiotics, technology design, linguistics, engineering, ergonomics, and subject matter specialties.
Mapping of image processing systems to FPGA computer based on temporal partitioning and design space exploration
Authors: Paulo Sérgio B. do Nascimento, Manoel E. de Lima, Stelita M. da Silva, Jordana L. Seixas
Venue: Proceedings of the 19th annual symposium on Integrated circuits and systems design (2006)

High parallelism degree is fundamental for high speed image processing systems. Modern FPGA devices can provide such parallelism plus flexibility. Temporal partitioning techniques can be used to implement large systems, splitting them into partitions (called contexts), multiplexed in a FPGA. This approach can increase the effective FPGA area, allowing high parallelism in the application tasks. However, the context reconfigurations can cause performance decrease. Intensive parallelism exploration of massive image data application compensates this overhead and can improve global performance. In this work, one reconfigurable computer platform and design space exploration techniques are proposed for mapping of image processing applications into FPGA slices. A library with different hardware implementation for different parallelism degree is used to better adjust space/time for each task. Experiments demonstrate the efficiency of the approach when compared to the optimal mapping reached by exhaustive timing search in the complete design space exploration.
Structural issues in cascade-form adaptive IIR filters
Authors: G. A. Williamson, J. P. Ashley, M. Nayeri
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

Adaptive IIR filters implemented in cascade-form are attractive due to the ease with which their stability may be monitored. Four cascade-form structures are compared for use in adaptive filtering with respect to complexity of implementation, error surface geometry, and adaptation speed. The four structures include a cascade of second order pole/zero sections, a cascade of second order all-pole sections followed by a tapped delay line, and two new structures. The latter pair includes a tapped cascade, which is a cascade of second order all-pole sections whose output is constructed as a weighted combination of signals tapped from the cascade. The second new structure is a modification of the tapped cascade that yields orthogonal signals at the taps of the cascade. It is shown that the tapped cascade provides the best overall performance in the respects noted above.
An Impulse Noise Reduction Method By Adaptive Pixel-Correlation
Authors: Thou-Ho (Chao-Ho) Chen, Chao-Yu Chen, Tsong-Yi Chen
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, we propose an adaptive decisionbased median filtering algorithm, called adaptive pixel-correlation filter (APCF), with an adaptive threshold for removal of impulse noise. By exploiting the correlations between a pixel and its neighbors, an adaptive threshold can be designed based on the global statistical properties. Due to the fact that both horizontal and vertical correlations for a pixel more significant than that of other orientation, such a characteristic is used to design a filter with a novel adaptive working window and weighted function for detecting impulse noise and preserving noise-free pixels. Numerical simulations show that APCF is more robust and effective than many other well-known median filtering algorithms
Using Ontologies in Context-Aware Applications
Authors: Damiao Ribeiro de Almeida, Claudio de Souza Baptista, Fabio Gomes de Andrade
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

Current mobile devices enable the use of information systems while the user is on the move. Hence, it is necessary to deal with space and time continuously. Yet, mobile applications need to be aware and adapt themselves to highly dynamic environments. Contextaware applications use mobile computing in order to provide information to users according to their context anywhere at anytime. Modeling context implies modeling user behavior, movements and necessities. Ontologies seem to be a good candidate for modeling context-aware applications, as rich semantic relationships can be implemented. In this paper, we present an ontology-based approach to deal with context-aware systems.
Data Migration for aWidely Distributed Storage System Using Autonomous Disks
Authors: Tsutomu Fujiwara, Jun Miyazaki, Shunsuke Uemura
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

We propose a data migration method for widely distributed autonomous disks, in which user's frequently accessed and important data are automatically transferred to the nearest disk and/or duplicated to others by using ECA rules, according to the properties of the data. Recently, a mobile user can handle a large amount of data because mobile disks are installed on many gadgets. However, data required by a user are not always on his mobile disk. Even if they are on it, the reliability is low due to the possibility of a disk crash. The proposed system makes use of multiple sets of ECA rules on autonomous disks and chooses an appropriate rule set in response to the changes of system states, so that optimal data accesses can be performed by migrating and/or duplicating the data to other disks. This system could bring comfortable and reliable data accesses to mobile users.
A maximum entropy approach for blind deconvolution
Authors: Monika Pinchas, Ben Zion Bobrovsky
Venue: Signal Processing (2006)

In this paper we propose a new closed approximated formed expression for the conditional expectation based on the Maximum Entropy principle and Laplace integral method. Our proposed expression does not impose any restrictions (except of even symmetric) on the probability distribution of the (unobserved) input sequence, thus it is suitable for a wider range of source probability density function compared with Bellini's, Fiori's or Haykin's expression. In addition, we propose a new, efficient and noniterative approximation for the Lagrange multipliers related to the blind deconvolution problem. Our proposed Lagrange multipliers are based on our new proposed expression for the conditional expectation and on the mean square error (MSE) criteria. Based on our new derivations, a new blind deconvolution algorithm is proposed with improved equalization performance compared with Godard's, reduced constellation algorithm (RCA), Fiori's and the sign reduced constellation algorithm (SRCA). In addition, a theoretical analysis shows that our algorithm achieves perfect equalization in the real valued and two independent quadrature carrier case. These results imply a significant improvement over Godard's algorithm in the 16 quadrature amplitude modulation (QAM) case.
Normative autonomy and normative co-ordination: declarative power, representation, and mandate
Authors: Jonathan Gelati, Antonino Rotolo, Giovanni Sartor, Guido Governatori
Venue: Artificial Intelligence and Law (2004)

In this paper we provide a formal analysis of the idea of normative co-ordination. We argue that this idea is based on the assumption that agents can achieve flexible co-ordination by conferring normative positions to other agents. These positions include duties, permissions, and powers. In particular, we explain the idea of declarative power, which consists in the capacity of the power-holder of creating normative positions, involving other agents, simply by "proclaiming" such positions. In addition, we account also for the concepts of representation, namely the representative's capacity of acting in the name of his principal, and of mandate, which is the mandatee's duty to act as the mandator has requested. Finally, we show how the framework can be applied to represent the contract-net protocol. Some brief remarks on future research and applications conclude this contribution.
Technology clusters: Using multidimensional scaling to evaluate and structure technology clusters: Research Articles
Authors: Arun Vishwanath, Hao Chen
Venue: Journal of the American Society for Information Science and Technology (2006)

Empirical evidence suggests that the ownership of related products that form a technology cluster is significantly better than the attributes of an innovation at predicting adoption. The treatment of technology clusters, however, has been ad hoc and study specific: Researchers often make a priori assumptions about the relationships between technologies and measure ownership using lists of functionally related technology, without any systematic reasoning. Hence, the authors set out to examine empirically the composition of technology clusters and the differences, if any, in clusters of technologies formed by adopters and nonadopters. Using the Galileo system of multidimensional scaling and the associational diffusion framework, the dissimilarities between 30 technology concepts were scored by adopters and nonadopters. Results indicate clear differences in conceptualization of clusters: Adopters tend to relate technologies based on their functional similarity; here, innovations are perceived to be complementary, and hence, adoption of one technology spurs the adoption of related technologies. On the other hand, nonadopters tend to relate technologies using a stricter ascendancy of association where the adoption of an innovation makes subsequent innovations redundant. The results question the measurement approaches and present an alternative methodology. &copy; 2006 Wiley Periodicals, Inc.