ppxscal/embedding_network huggingface dataset:
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification
Authors: Pawan Lingras, Cory Butz
Venue: Information Sciences: an International Journal (2007)

Support vector machines (SVMs) are essentially binary classifiers. To improve their applicability, several methods have been suggested for extending SVMs for multi-classification, including one-versus-one (1-v-1), one-versus-rest (1-v-r) and DAGSVM. In this paper, we first describe how binary classification with SVMs can be interpreted using rough sets. A rough set approach to SVM classification removes the necessity of exact classification and is especially useful when dealing with noisy data. Next, by utilizing the boundary region in rough sets, we suggest two new approaches, extensions of 1-v-r and 1-v-1, to SVM multi-classification that allow for an error rate. We explicitly demonstrate how our extended 1-v-r may shorten the training time of the conventional 1-v-r approach. In addition, we show that our 1-v-1 approach may have reduced storage requirements compared to the conventional 1-v-1 and DAGSVM techniques. Our techniques also provide better semantic interpretations of the classification process. The theoretical conclusions are supported by experimental findings involving a synthetic dataset.
Application of ground penetrating radar for coal depth measurement
Authors: J. C. Ralston
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

This paper describes the development of a new ground penetrating radar system for measuring coal thickness in underground mining operations. Although subsurface radar exhibits significant potential for depth measurement, the raw signals are complicated and cannot be readily interpreted by mining personnel. We show how real-time digital signal processing plays a key role in transforming the raw radar signals into a form that can be readily understood. We also indicate some of the unique challenges encountered when implementing a radar processing system in a harsh underground mining environment.
Integration of concept-driven semantic interpretation with speech recognition
Authors: A. Nagai, I. Ishikawa, K. Nakajima
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

This paper discusses issues concerning incorporating speech recognition with semantic interpretation based on concept. In our approach, a concept is a unit of semantic interpretation and an utterance is regarded as a sequence of concepts with an intention to attain both linguistic robustness and constraints for speech recognition. First, we propose a basic search method for detecting concepts from a phrase lattice by island-driven search evaluating the linguistic likelihood of concept hypotheses. Second, an improved method to search efficiently for N-best meaning hypotheses is proposed. Experimental results show that the basic search method has achieved a 92% understanding rate, and that the improved search technique reduced search processing time to approximately one-tenth in comparison with the basic search method without reducing performance. A scheme of understanding complex sentences based on the proposed method is also described.
Input Validation for Semi-supervised Clustering
Authors: Kevin Y. Yip, Michael K. Ng, David W. Cheung
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

Semi-supervised clustering is practical in situations in which there exists some domain knowledge that could help the clustering process, but which is not suitable or not sufficient for supervised learning. There have been a number of studies on semi-supervised clustering, but almost all of them assume the input knowledge is correct or largely correct. In this paper we show that even a small proportion of incorrect input knowledge could make a semi-supervised clustering algorithm perform worse than having no inputs. This is a real concern since in real applications it is reasonable to have problematic "knowledge inputs" that are wrong or inappropriate for the clustering task. We propose a general methodology for detecting potentially incorrect inputs and performing verifications. Based on the methodology, we outline some methods for validating the inputs of the semi-supervised clustering algorithm MPCKMeans. Experimental results show that the input validation step is both critical and effective as the clustering accuracy of MPCK-Means was lowered by incorrect inputs, but the lost accuracy was resumed when validation was performed.
Dytan: a generic dynamic taint analysis framework
Authors: James Clause, Wanchun Li, Alessandro Orso
Venue: Proceedings of the 2007 international symposium on Software testing and analysis (2007)

Dynamic taint analysis is gaining momentum. Techniques based on dynamic tainting have been successfully used in the context of application security, and now their use is also being explored in different areas, such as program understanding, software testing, and debugging. Unfortunately, most existing approaches for dynamic tainting are defined in an ad-hoc manner, which makes it difficult to extend them, experiment with them, and adapt them to new contexts. Moreover, most existing approaches are focused on data-flow based tainting only and do not consider tainting due to control flow, which limits their applicability outside the security domain. To address these limitations and foster experimentation with dynamic tainting techniques, we defined and developed a general framework for dynamic tainting that (1) is highly flexible and customizable, (2) allows for performing both data-flow and control-flow based tainting conservatively, and (3) does not rely on any customized run-time system. We also present DYTAN, an implementation of our framework that works on x86 executables, and a set of preliminary studies that show how DYTAN can be used to implement different tainting-based approaches with limited effort. In the studies, we also show that DYTAN can be used on real software, by using FIREFOX as one of our subjects, and illustrate how the specific characteristics of the tainting approach used can affect efficiency and accuracy of the taint analysis, which further justifies the use of our framework to experiment with different variants of an approach.
Robust clustering of acoustic emission signals using the Kohonen network
Authors: V. Emamian
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

Acoustic emission-based techniques are promising for nondestructive inspection of mechanical systems. For reliable automatic fault monitoring, it is important to identify the transient crack-related signals in the presence of strong time-varying noise and other interference. In this paper we propose the application of the Kohonen network for this purpose. The principal components of the short-time Fourier transforms of the data were applied input of the network. The clustering results confirm the capability of the Kohonen network for reliable source identification of acoustic emission signals, assuming enough care has been taken in implementing the training algorithm of the network.
Detecting and countering system intrusions using software wrappers
Authors: Calvin Ko, Timothy Fraser, Lee Badger, Douglas Kilpatrick
Venue: Proceedings of the 9th conference on USENIX Security Symposium - Volume 9 (2000)

This paper introduces an approach that integrates intrusion detection (ID) techniques with software wrapping technology to enhance a system's ability to defend against intrusions. In particular, we employ the NAI Labs Generic Software Wrapper Toolkit to implement all or part of an intrusion detection system as ID wrappers. An ID wrapper is a software layer dynamically inserted into the kernel that can selectively intercept and analyze system calls performed by processes as well as respond to intrusive events. We have implemented several ID wrappers that employ three different major intrusion detection techniques. Also, we have combined different ID techniques by composing ID wrappers at run-time. We tested the individual and composed ID wrappers using several existing attacks and measured their impact on observed application performance. We conclude that intrusion detection algorithms can be easily encoded as wrappers that perform efficiently inside the kernel. Also, kernel-resident ID wrappers can be easily managed, allowing cooperation among multiple combined techniques to enforce a coherent global ID policy. In addition, intrusion detection algorithms can benefit from the extra data made accessible by wrappers.
Algorithm 868: Globally doubly adaptive quadrature&mdash;reliable Matlab codes
Authors: Terje O. Espelid
Venue: ACM Transactions on Mathematical Software (TOMS) (2007)

We discuss how to modify a recently published Matlab code, coteglob, so that the excellent performance this code demonstrates for low and intermediate accuracy requests is retained while the performance is improved for high accuracy requests. coteglob is a globally adaptive code using a 5 and 9 point pair of Newton-Cotes rules. Combining an extended sequence of rules using 5, 9, 17 and 33 points with a doubly adaptive bisection strategy is the main focus of the paper. We also discuss local versus global adaptivity and conclude that globally adaptive codes are to be preferred. Based on this we develop several new globally adaptive codes that all compare favorably both with coteglob, with Matlab's best currently available quadrature software quadl and the general purpose QUADPACK codes dqk15 and dqk21. We include the results from extensive testing using both a Lyness-Kaganove testing technique and a battery test.
A Computer-Aided Diagnostic System using a Global Data Grid Repository for the Evaluation of Ultrasound Carotid Images
Authors: Marco Antonio Gutierrez, Silvia Helena Gelas Lage, Jasper Lee, Zheng Zhou
Venue: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid (2007)

A computer-aided diagnostic (CAD) method of calculating lumen and wall thickness of carotid vessels is presented. The CAD is able to measure the geometry of the lumen and plaque surfaces in ultrasound carotid images using a least-square fitting of the active contours obtained automatically from the vessels border. To evaluate the approach, ultrasound image sequences from 30 patients were submitted to the procedure. The images were stored on an international data grid repository that consists of three international sites: IPI Laboratory at University of Southern California, USA; Heart Institute at University Sao Paulo, Brazil, and Hong Kong Polytechnic University, Hong Kong. The three chosen sites are connected with high speed international networks including the Internet2, and the Brazilian National Research and Education Network (RNP2). The Data Grid was used to store, backup, and share the ultrasound images and analysis results, which provided a large-scale and a virtual data system.
Remote windows NT administration using windows CE handheld devices
Authors: Craig Stacey
Venue: Proceedings of the 3rd conference on Large Installation System Administration of Windows NT - Volume 3 (2000)

As a systems administrator on call at any time of day, I want to explore ways to manage the environment and handle emergencies remotely. In this paper, I look at a number of options for remote administration using compact devices. While the most obvious form of remote administration is a laptop computer, not every organization has the budget to provide these to their systems administrators. Also, in some situations, even a laptop computer is too large to carry around conveniently. Therefore, I evaluated three devices to determine their usefulness for remote administration. While concentrating on Windows CE devices, I included a Palm Computing handheld for comparison purposes.
Generation of Synthetic Spike Trains with Defined Pairwise Correlations
Authors: Ernst Niebur
Venue: Neural Computation (2007)

Recent technological advances as well as progress in theoretical understanding of neural systems have created a need for synthetic spike trains with controlled mean rate and pairwise cross-correlation. This report introduces and analyzes a novel algorithm for the generation of discretized spike trains with arbitrary mean rates and controlled cross correlation. Pairs of spike trains with any pairwise correlation can be generated, and higher-order correlations are compatible with common synaptic input. Relations between allowable mean rates and correlations within a population are discussed. The algorithm is highly efficient, its complexity increasing linearly with the number of spike trains generated and therefore inversely with the number of cross-correlated pairs.
Prosodic word boundary detection using statistical modeling of moraic fundamental frequency contours and its use for continuous speech recognition
Authors: K. Iwano
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

A new method for prosodic word boundary detection in continuous speech was developed based on the statistical modeling of moraic transitions of fundamental frequency (F/sub 0/) contours, formerly proposed by the authors. In the developed method, F/sub 0/ contours of prosodic words were modeled separately according to the accent types. An input utterance was matched against the models and was divided into constituent prosodic words. By doing so, prosodic word boundaries can be obtained. The method was first applied to the boundary detection experiments of the ATR continuous speech corpus. With mora boundary locations given in the corpus, total detection rate reached 91.5%. Then the method was integrated into a continuous speech recognition scheme with unlimited vocabulary. A few percentage improvement was observed in mora recognition for the above corpus. Although all the experiments were done in closed conditions due to the corpus availability, the results indicated the usefulness of the proposed method.
Parallel repetition: simplifications and the no-signaling case
Authors: Thomas Holenstein
Venue: Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (2007)

Consider a game where a refereed chooses (x,y) according to a publiclyknown distribution PXY, sends x to Alice, and y to Bob. Withoutcommunicating with each other, Alice responds with a value "a" and Bobresponds with a value "b". Alice and Bob jointly win if a publiclyknown predicate Q(x,y,a,b) holds. Let such a game be given and assume that the maximum probabilitythat Alice and Bob can win is v<1. Raz (SIAM J. Comput. 27, 1998)shows that if the game is repeated n times in parallel, then the probability that Alice and Bob win all games simultaneously is at most v'(n/log(s)), where s is the maximal number of possible responses from Alice and Bob in the initial game, and v' is a constant depending only on v. In this work, we simplify Raz's proof in various ways and thus shorten it significantly. Further we study the case where Alice and Bob are not restricted to local computations and can use any strategy which does not imply communication among them.
MACEDON: methodology for automatically creating, evaluating, and designing overlay networks
Authors: Adolfo Rodriguez, Charles Killian, Sooraj Bhat, Dejan Kostić, Amin Vahdat
Venue: Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1 (2004)

Currently, researchers designing and implementing large-scale overlay services employ disparate techniques at each stage in the production cycle: design, implementation, experimentation, and evaluation. As a result, complex and tedious tasks are often duplicated leading to ineffective resource use and difficulty in fairly comparing competing algorithms. In this paper, we present MACEDON, an infrastructure that provides facilities to: i) specify distributed algorithms in a concise domain-specific language; ii) generate code that executes in popular evaluation infrastructures and in live networks; iii) leverage an overlay-generic API to simplify the interoperability of algorithm implementations and applications; and iv) enable consistent experimental evaluation. We have used MACEDON to implement and evaluate a number of algorithms, including AMMO, Bullet, Chord, NICE, Overcast, Pastry, Scribe, and SplitStream, typically with only a few hundred lines of MACEDON code. Using our infrastructure, we are able to accurately reproduce or exceed published results and behavior demonstrated by current publicly available implementations.
On an approximation method for pricing a high-dimensional basket option on assets with mean-reverting prices
Authors: Xun Li, Zhenyu Wu
Venue: Computers and Operations Research (2008)

This study presents a simple but powerful approximation approach that is both accurate and computationally efficient for valuing basket options on multiple assets with mean-reverting prices. It accomplishes this by solving technical problems involved in reducing the dimensionality of basket options. The approach is readily applicable to multi-factor situations where traditional techniques do not work and contributes to the fields of option pricing, computational finance, and energy industry risk management. Numerical examples, including applications to the energy commodity market, illustrate the computational efficiency and accuracy of the approach when compared with results from Monte Carlo (MC) simulations and extant methods in the literature.
Improved spelling recognition using a tree-based fast lexical match
Authors: C. D. Mitchell
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

This paper addresses the problem of selecting a name from a very large list using spelling recognition. In order to greatly reduce the computational resources required, we propose a tree-based lexical fast match scheme to select a short list of candidate names. Our system consists of a free letter recognizer, a fast matcher, and a rescoring stage. The letter recognizer uses n-grams to generate an n-best list of letter hypotheses. The fast matcher is a tree that is based on confusion classes, where a confusion class is a group of acoustically similar letters such as the e-set. The fast matcher reduces over 100,000 unique last names to tens or hundreds of candidates. Then the rescoring stage picks the best name using either letter alignment or a constrained grammar. The fast matcher retained the correct name 99.6% of the time and the system retrieved the correct name 97.6% of the time.
The Optimal Convergence of the $h$-$p$ Version of the Finite Element Method with Quasi-Uniform Meshes
Authors: Benqi Guo, Weiwei Sun
Venue: SIAM Journal on Numerical Analysis (2007)

In the framework of the Jacobi-weighted Besov spaces, we analyze the convergence of the $h$-$p$ version of finite element solutions on quasi-uniform meshes and the lower and upper bounds of errors for elliptic problems on polygons. Both lower and upper bounds are proved to be optimal in $h$ and $p$, which leads to the optimal convergence of the $h$-$p$ version of the finite element method with quasi-uniform meshes for elliptic problems on polygons. The results proved for the $h$-$p$ version include the $h$-version with quasi-uniform meshes and the $p$-version with quasi-uniform degrees as two special cases.
Easy, fast, and flexible algorithm animation generation
Authors: Guido Rößling, Simon Kulessa, Silke Schneider
Venue: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007)

A common reason for not using algorithm animation in class or exercises is the amount of time needed to locate, adapt, or generate content. We present several components that try to improve this situation by providing easy, fast and flexible content generation. The different scope of the approaches makes it likely that they offer "something for almost everyone".
Correlating multi-session attacks via replay
Authors: Fareha Shafique, Kenneth Po, Ashvin Goel
Venue: Proceedings of the 2nd conference on Hot Topics in System Dependability - Volume 2 (2006)

Intrusion analysis is a manual and time-consuming operation today. It is especially challenging because attacks often span multiple sessions which makes it is hard to diagnose all the damage caused by an attack. One approach for determining dependencies between the sessions of an attack is system-call taint analysis, but this method can generate large numbers of false dependencies due to shared objects such as a password file. In this paper, we propose a novel solution to this problem that replays sessions with tainted and untainted inputs and reasons about multisession dependencies by comparing the session's outputs in the two cases. We present some initial experiments that show that this approach is promising and may allow building powerful intrusion analysis and recovery systems.
Constructing non-computable Julia sets
Authors: Mark Braverman, Michael Yampolsky
Venue: Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (2007)

While most polynomial Julia sets are computable, it has been recently shown [12] that there exist non-computable Julia sets. The proof was non-constructive, and indeed there were doubts as to whether specific examples of parameters with non-computable Julia sets could be constructed. It was also unknown whether the non-computability proof can be extended to the filled Julia sets. In this paper we give an answer to both of these questions, which were the main open problems concerning the computability of polynomial Julia sets. We show how to construct a specific polynomial with a non-computable Julia set. In fact, in the case of Julia sets of quadratic polynomials we give a precise characterization of Juliasets with computable parameters. Moreover, assuming a widely believed conjecture in Complex Dynamics, we give a poly-time algorithm forcomputing a number c such that the Julia set Jz2+c z is non-computable. In contrast with these results, we show that the filled Julia set of a polynomial is always computable.
Wavelet analysis of the timing of individual components of the ECG signal
Authors: M. J. Burke
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

ECG recordings were obtained from 21 healthy subjects aged between 13 and 65 years, over a range of heart rate extending from 46 to 184 beats/min (bpm). A wavelet transform method, based on the Mexican Hat wavelet was then used to precisely locate the positions of the onset, peak and termination of individual components in the ECG signal. These times were then classified according to the heart rate associated with the cardiac cycle to which the component belonged. Second order equations in the square root of the cardiac cycle time, T/sub R-R/ of the form A./spl radic/T/sub R-R/+B.T/sub R-R/+C were fitted to the data obtained for each component to characterize its timing variation.
A New Hardware Module for Stereo Matching Using Zernike Moments
Authors: Paschalis Gonidis, Leonidas Kotoulas, Ioannis Andreadis
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

This paper presents a new hardware module suitable for matching point features between two uncalibrated images of a scene with real-time response. A robust matching is established under a mixed geometric and moment-based correspondence strength function. In order to provide rotation invariance and low noise sensitivity, Zernike moments are utilized. The proposed system is capable of extracting correspondences between stereo pairs at a rate of over 25 pairs per second, for VGA images.