ppxscal/embedding_network huggingface dataset:
An Automatic Speaker Recognition System
Authors: P. Chakraborty, F. Ahmed, Md. Monirul Kabir, Md. Shahjahan, Kazuyuki Murase
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Speaker Recognition is the process of identifying a speaker by analyzing spectral shape of the voice signal. This is done by extracting matching the feature of voice signal. Mel-frequency Cepstrum Co-efficient (MFCC) is the feature extraction technique in which we will get some coefficients named Mel-Frequency Cepstrum coefficient. This Cepstrum Co-efficient is extracted feature. This extracted feature is taken as the input of Vector Quantization process. Vector Quantization (VQ) is the typical feature matching technique in which VQ codebook is generated by providing pre-defined spectral vectors for each speaker to cluster the training vectors in a training session. Finally test data are provided for searching the nearest neighbor to match that data with the trained data. The result is to recognize correctly the speakers where music speech data (Both in English Bengali format) are taken for the recognition process. The correct recognition is almost ninety percent. It is comparatively better than Hidden Markov model (HMM) Artificial Neural network (ANN).
KLMLean 2.0: A Theorem Prover for KLM Logics of Nonmonotonic Reasoning
Authors: Laura Giordano, Valentina Gliozzi, Gian Luca Pozzato
Venue: Proceedings of the 16th international conference on Automated Reasoning with Analytic Tableaux and Related Methods (2007)

We present KLMLean 2.0, a theorem prover for propositional KLM logics of nonmonotonic reasoning. KLMLean 2.0 implements some analytic tableaux calculi for these logics recently introduced. KLMLean 2.0 is inspired by the "lean" methodology, it is implemented in SICStus Prolog and it also contains a graphical interface written in Java.
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach
Authors: Michelangelo Ceci, Annalisa Appice, Donato Malerba
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Spatial Data Mining (SDM) has great potential in supporting public policy and in underpinning society functioning. One task in SDM is the discovery of characterization and peculiarities of communities sharing socio-economic aspects in order to identify potentialities, needs and public intervention. Emerging patterns (EPs) are a special kind of pattern which contrast two classes. In this paper, we face the problem of extracting EPs from spatial data. At this aim, we resort to a multi-relational approach in order to deal with the degree of complexity of discovering EPs from spatial data (i.e., (i) the spatial dimension implicitly defines spatial properties and relations, (ii) spatial phenomena are affected by autocorrelation). Experiments on real datasets are described.
Multi-class Boosting with Color-Based Haar-Like Features
Authors: Wen-Chung Chang, Chih-Wei Cho
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

This paper presents a multi-class boosting algorithm employing color-based Haar-like features. Traditional multi-class boosting algorithms basically regard multi-class problems as extensions of two-class problems. In particular, additional strong classifiers must be parallelly extended once the number of target classes increases. The idea in the proposed approach is to develop a single strong classifier which is capable of resolving multi-class problems. To make the multi-class algorithm tractable, the proposed system is required to select a set of weak classifiers which could classify multiple types of targets correctly. In contrast to standard Haar-like features that compute feature values based on gray level images, the seemingly novel Haar-like features require computation based on color images. Since the mapping from color image space to gray level image space is an epimorphism, detection algorithms using standard Haarlike features inevitably disregard color information available in original color images. Strong classifiers adopting the proposed color-based Haar-like features typically appear to have comparable performance, in the aspects of detection and correct classification rates, with fewer weak classifiers when compared with the one employing standard Haar-like features. The proposed boosting algorithm can improve system efficiency and resolve multi-class problems by a single strong classifier, whereas existing approaches are more complicated and the number of two-class classifiers could be relatively large. Our approach has been successfully validated in real traffic environments by performing experiments with a CCD camera mounted onboard a highway vehicle, where the targets are defined as passenger cars and motorcycles.
A bound on the size of separating hash families
Authors: Simon R. Blackburn, Tuvi Etzion, Douglas R. Stinson, Gregory M. Zaverucha
Venue: Journal of Combinatorial Theory Series A (2008)

The paper provides an upper bound on the size of a (generalized) separating hash family, a notion introduced by Stinson, Wei and Chen. The upper bound generalizes and unifies several previously known bounds which apply in special cases, namely bounds on perfect hash families, frameproof codes, secure frameproof codes and separating hash families of small type.
An efficient architecture for designing reverse converters based on a general three-moduli set
Authors: Amir Sabbagh Molahosseini, Keivan Navi, Omid Hashemipour, Ali Jalali
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

In this paper, a high-speed, low-cost and efficient design of reverse converter for the general three-moduli set {2^@a, 2^@b-1, 2^@b+1} where @a
A Multi-tier, Multimodal Wireless Sensor Network for Environmental Monitoring
Authors: Carlos Eduardo Lopes, Fernando D. Linhares, Michele M. Santos, Linnyer B. Ruiz
Venue: Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing (2007)

WSNs are distributed sensing tools with monitoring capabilities unavailable until now. Network elements (sensor nodes) are frequently pointed out as a new computer systems class due to its ubiquitous an analytical features. Wireless Sensor Networks have evolved quickly in recent years. Such evolution lead to specializations such as Wireless Visual Sensor Networks and Multi-tier, Multimodal Wireless Sensor Networks (M2 WSN). The desing, modeling and implementation development of a WSN M2 for environment monitoring is treated in this work. Simulations with such network shows that they present better usage of components and energy resources with little sacrifice to the application performance.
A new perspective to the keepaway soccer: the takers
Authors: Atil Iscen, Umut Erogul
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

Keepaway is a sub-problem of RoboCup Soccer Simulator in which 'the keepers' try to maintain the possession of the ball, while 'the takers' try to steal the ball or force it out of bounds. By using Reinforcement Learning as a learning method, a lot of research has been done in this domain. In these works, there has been a remarkable success for the intelligent keepers part, however most of these keepers are trained and tested against simple hand-coded takers. We tried to address this part of the problem by using Sarsa(&lambda;) as a Reinforcement Learning method with linear tile-coding as function approximation and used two different state spaces that we specially designed for the takers. As the results of the experiments confirm, we outperformed the hand-coded taker which results in creating a better trainer and tester for the keepers. Also when designing the new state space, we noticed that smaller state spaces can also be successful for this part of the problem.
Why service-orientation could make e-learning standards obsolete
Authors: Gottfried Vossen, Peter Westerkamp
Venue: International Journal of Technology Enhanced Learning (2008)

Standardisation in e-learning is characterised by the development of numerous specifications. Main efforts address the annotation of metadata, content aggregation, educational modelling languages, or the definition of interfaces for platforms and runtime systems to execute learning objects. Each of these fields comprises several competing activities that are generally not compatible to each other. In this paper, we discuss typical problems of common e-learning standards and contrast this with a service-oriented approach to deliver major functionalities of e-learning platforms and content. The approach is based on web services, which can be plugged together to build platforms that solve many of the compatibility problems inherent in present-day standards. It turns out that the consistent implementation of e-learning functionalities based on web services can make several e-learning standards obsolete.
Origins and Development of Nomography
Authors: H. A. Evesham
Venue: IEEE Annals of the History of Computing (1986)

Early developments that preceded nomography are cited, and the development of the subject is examined in outline. The special problem of nomograms in three variables is considered in a general way. Uses of nomography, both old and recent, are given. The tone is intended to be descriptive, not technical, but references are provided so that the interested reader can investigate the subject further. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Calling variadic functions from a strongly-typed language
Authors: Matthias Blume, Michael Rainey, John Reppy
Venue: Proceedings of the 2008 ACM SIGPLAN workshop on ML (2008)

The importance of providing a mechanism to call C functions from high-level languages has been understood for many years and, these days, almost all statically-typed high-level-language implementations provide such a mechanism. One glaring omission, however, has been support for calling variadic C functions, such as printf. Variadic functions have been ignored because it is not obvious how to give static types to them and because it is not clear how to generate calling sequence when the arguments to the function may not be known until runtime. In this paper, we address this longstanding omission with an extension to the NLFFI foreign-interface framework used by Standard ML of New Jersey (SML/NJ) and the MLton SML compiler. We describe two different ways of typing variadic functions in NLFFI and an implementation technique based on the idea of using state machines to describe calling conventions. Our implementation is easily retargeted to new architectures and ABIs, and can also be easily added to any HOT language implementation that supports calling C functions.
A Synthetic Instruction Mix for Evaluating Microprocessor Performance
Authors: John McCallum, Tat-seng Chua
Venue: IEEE Micro (1987)

Need to rate the performance of that new microprocessor you're interested in? Here's a simple, easy way to do just that.
Can We Win the Security Game?
Authors: Charles C. Palmer
Venue: IEEE Security and Privacy (2004)

Profile on S&P editorial board member Charles C. Palmer
Automatic Extending HowNet's Attribute Lexicon on the Web
Authors: Jinglei Zhao, Hui Liu, Ruzhan Lu
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

It is well known that lexical knowledge sources as WordNet, HowNet are very important to natural language processing applications in artificial intelligence. This paper proposes a new Web-mining algorithm to automatically extend HowNet’s attribute set. Seeded by the original attribute set in HowNet, the algorithm uses a conjunctive lexical pattern plus a validation mechanism called PES (position exchanging search) to extend the lexicon iteratively on the Web. Also, a Web-based attribute classifier is constructed which behaves as a filter to control the level of false positives during each iteration. The algorithm is evaluated using both standard human judgements and HowNet based evaluation. Some experimental results about the performance of the method are provided.
Experience-based learning of Japanese IT professionals: A qualitative research
Authors: Makoto Matsuo, Christina W. Y. Wong, Kee-hung Lai
Venue: The Journal of Strategic Information Systems (2008)

Grounded in the Experiential Learning Theory and expertise research, this study examines the processes of experience-based learning, i.e., acquisition of skills and knowledge from direct experience, at different career stages of different types of IT professionals. A qualitative research method was used to compile a series of case studies on the basis of theoretical replication to answer this research inquiry. Semi-structured interviews were conducted with 10 IT consultants and 14 project managers in six Japanese IT firms. Our findings indicate that these different IT professionals have acquired different skills and knowledge from their job experiences at their different career stages. Academic and managerial implications of this study are discussed.
Fusion methods for detecting neural and pupil responses to task-relevant visual stimuli using computer pattern analysis
Authors: Loren Nolte
Venue:  (2008)

A series of fusion techniques are developed and applied to EEG and pupillary recording analysis in a rapid serial visual presentation (RSVP) based image triage task, in order to improve the accuracy of capturing single-trial neural/pupillary signatures (patterns) associated with visual target detection. The brain response to visual stimuli is not a localized pulse, instead it reflects time-evolving neurophysiological activities distributed selectively in the brain. To capture the evolving spatio-temporal pattern, we divide an extended ("global") EEG data epoch, time-locked to each image stimulus onset, into multiple non-overlapping smaller ("local") temporal windows. While classifiers can be applied on EEG data located in multiple local temporal windows, outputs from local classifiers can be fused to enhance the overall detection performance. According to the concept of induced/evoked brain rhythms, the EEG response can be decomposed into different oscillatory components and the frequency characteristics for these oscillatory components can be evaluated separately from the temporal characteristics. While the temporal-based analysis achieves fairly accurate detection performance, the frequency-based analysis can improve the overall detection accuracy and robustness further if frequency-based and temporal-based results are fused at the decision level. Pupillary response provides another modality for a single-trial image triage task. We developed a pupillary response feature construction and selection procedure to extract/select the useful features that help to achieve the best classification performance. The classification results based on both modalities (pupillary and EEG) are further fused at the decision level. Here, the goal is to support increased classification confidence through inherent modality complementarities. The fusion results show significant improvement over classification results using any single modality. For crucial image triage tasks, multiple image analysts could be asked to evaluate the same set of images to improve the probability of detection and reduce the probability of false positive. We observe significant performance gain by fusing the decisions drawn by multiple analysts. To develop a practical real-time EEG-based application system, sometimes we have to work with an EEG system that has a limited number of electrodes. We present methods of ranking the channels, identifying a reduced set of EEG channels that can deliver robust classification performance.
VC Dimension Bounds for Analytic Algebraic Computations
Authors: José Luis Montaña, Luis Miguel Pardo, Mar Callau
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

We study the Vapnik-Chervonenkis dimension of concept classes that are defined by computer programs using analytic algebraic functionals (Nash operators) as primitives. Such bounds are of interest in learning theory because of the fundamental role the Vapnik-Chervonenkis dimension plays in characterizing the sample complexity required to learn concept classes. We strengthen previous results by Goldberg and Jerrum giving upper bounds on the VC dimension of concept classes in which the membership test for whether an input belongs to a concept in the class can be performed either by an algebraic computation tree or by an algebraic circuit containing analytic algebraic gates. These new bounds are polynomial both in the height of the tree and in the depth of the circuit. This means in particular that VC dimension of computer programs using Nash operators is polynomial not only in the sequential complexity but also in the parallel complexity what ensures polynomial VC dimension for classes of concepts whose membership test can be defined by well-parallelizable sequential exponential time algorithms using analytic algebraic operators.
Appearance-Based Robot Discrimination Using Eigenimages
Authors: Sascha Lange, Martin Riedmiller
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Transformation of high-dimensional images to a low-dimensional feature space using Eigenimages is a well known technique in the field of face recognition. In this paper, we investigate the applicability of this method to the task of discriminating several types of robots by their appearance only. After calculating suitable Eigenimages for Middle Size robots and selecting the most useful ones, a Support Vector Machine is trained on the feature vectors to reliably recognize several types of robots. The computational demands and the integration into a real-time vision system have an important role throughout the discussion.
Implementation of wireless VoIP system based on VPN
Authors: Dae-Hyun Ryu, Seung-Hoon Nam
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

VoIP isn't secure since it uses the Internet to which many people connect simultaneously. In this paper, we designed and implemented a Wireless VoIP + VPN system with which secure telephone calls are possible using the open project SIP VoIP Gateway, 'Asterisk' and 'OpenVPN'.
Tool Condition Monitoring Using the TSK Fuzzy Approach Based on Subtractive Clustering Method
Authors: Qun Ren, Marek Balazinski, Luc Baron, Krzysztof Jemielniak
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This paper presents a tool condition monitoring approach using Takagi-Sugeno-Kang (TSK) fuzzy logic incorporating a subtractive cluste- ring method. The experimental results show its effectiveness and satisfactory comparisons with several other artificial intelligence methods.
On the Decidability of Bounded Valuedness for Transducers
Authors: Jacques Sakarovitch, Rodrigo Souza
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

We give a new and conceptually different proof for the decidability of k-valuedness of transducers (a result due to Gurari and Ibarra), without resorting to any other kind of machines than transducers. In contrast with the previous proof, our algorithm takes into account the structure of the analysed transducers and yields better complexity bounds. With the same techniques, we also present a new proof, hopefully more easily understandable, for the decidability of bounded valuedness (a result due to Weber).
GREC 2007 Arc Segmentation Contest: Evaluation of Four Participating Algorithms
Authors: Faisal Shafait, Daniel Keysers, Thomas M. Breuel
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

Automatic conversion of line drawings from paper to electronic form requires the recognition of geometric primitives like lines, arcs, circles etc. in scanned documents. Many algorithms have been proposed over the years to extract lines and arcs from document images. To compare different state-of-the-art systems, an arc segmentation contest was held in the seventh IAPR International Workshop on Graphics Recognition - GREC 2007. Four methods participated in the contest, three of which were commercial systems and one was a research algorithm. This paper presents the results of the contest by giving an overview of the dataset used in the contest, evaluation methodology, participating methods and the segmentation accuracy achieved by the participating methods.
Multi-scale Modelling of the Two-Dimensional Flow Dynamics in a Stationary Supersonic Hot Gas Expansion
Authors: Giannandrea Abbate, Barend J. Thijsse, Chris R. Kleijn
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

A stationary hot gas jet supersonically expanding into a low pressure environment is studied through multi-scale numerical simulations.A hybrid continuum-molecular approach is used to model the flow. Due to the low pressure and high thermodynamic gradients, the accuracy of continuum mechanics results are doubtful, while, because of its excessive time expenses, a full molecular method is not feasible. The results of the proposed hybrid continuum-molecular approach have been successfully validated against experimental data.An important question for the full understanding of the processes governing the flow is addressed: the demonstration of an invasion of the supersonic part of the flow by background particles. Through the tracking of particles and collisions in the supersonic region it could be definitively proven that background particles are present in this region. We present a complete two dimensional picture of how the invading background particles distribute and collide with local particles into the supersonic region.
The Polynomial and Linear Hierarchies in V0
Authors: Leszek Aleksander Kołodziejczyk, Neil Thapen
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We show that the bounded arithmetic theory V0 does not prove that the polynomial time hierarchy collapses to the linear time hierarchy (without parameters). This result follows from a lower bound for bounded depth circuits computing prefix parity, where the circuits are allowed some auxiliary input.This is a continuation of earlier work by the authors which showed that this collapse is not provable in ${\mbox{\rm{PV}}}$ under a cryptographic assumption.
Nature---Inspired Synthesis of Rational Protocols
Authors: Almudena Alcaide, Juan M. Tapiador, Julio C. Hernandez-Castro, Arturo Ribagorda
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

Rational cryptography is an emerging field which combines aspects traditionally related to security with concepts described in economic theoretical frameworks. For example, it applies game theory concepts to address security problems arising when executing cryptographic protocols. The aim is to replace the assumption of a worst---case attacker by the notion of rational agents that try to maximize their payoffs. In this work, we define a formal framework and a meta---heuristic technique for the automated synthesis of multi---party rational exchange security (M---RES) protocols. We provide experimental results for a simple scenario where a 3---party rational exchange protocol is automatically designed.