ppxscal/embedding_network huggingface dataset:
Packet Processing on Stream Architecture- Emerging Network Applications
Authors: Yu-Kuen Lai
Venue:  (2007)

Emerging network applications are shifting from routing and traffic management to those requiring inspection and modification of packet contents. Such applications act on data streams, and the requirement to process every byte of a packet exceeds the already-substantial processing capabilities of high-speed networking equipment. Network processors are application-specific processors that are optimized to bridge the gap between the performance of ASIC and the programmability of general-purpose processors. Performance on traditional network applications is impressive, but we believe that these architectures are not well-suited for the emerging packet applications. Stream architectures are specifically designed to apply a consistent set of complex operations to each of a sequence of elements. Packet processing shares many of the same characteristics of media and image processing that motivate stream architectures: little global data reuse, abundant data parallelism, and high computational complexity. Therefore, stream architectures have been proposed as efficient and flexible platforms for network packet processing. 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
A Scale-Space Approach to Landmark Constrained Image Registration
Authors: Eldad Haber, Stefan Heldmann, Jan Modersitzki
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

Adding external knowledge improves the results for ill-posed problems. In this paper we present a new multi-level optimization framework for image registration when adding landmark constraints on the transformation. Previous approaches are based on a fixed discretization and lack of allowing for continuous landmark positions that are not on grid points. Our novel approach overcomes these problems such that we can apply multi-level methods which have been proven being crucial to avoid local minima in the course of optimization. Furthermore, for our numerical method we are able to use constraint elimination such that we trace back the landmark constrained problem to a unconstrained optimization leading to an efficient algorithm.
Mining wikipedia revision histories for improving sentence compression
Authors: Elif Yamangil, Rani Nelken
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

A well-recognized limitation of research on supervised sentence compression is the dearth of available training data. We propose a new and bountiful resource for such training data, which we obtain by mining the revision history of Wikipedia for sentence compressions and expansions. Using only a fraction of the available Wikipedia data, we have collected a training corpus of over 380,000 sentence pairs, two orders of magnitude larger than the standardly used Ziff-Davis corpus. Using this new-found data, we propose a novel lexicalized noisy channel model for sentence compression, achieving improved results in grammaticality and compression rate criteria with a slight decrease in importance.
You've got answers: towards personalized models for predicting success in community question answering
Authors: Yandong Liu, Eugene Agichtein
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Question answering communities such as Yahoo! Answers have emerged as a popular alternative to general-purpose web search. By directly interacting with other participants, information seekers can obtain specific answers to their questions. However, user success in obtaining satisfactory answers varies greatly. We hypothesize that satisfaction with the contributed answers is largely determined by the asker's prior experience, expectations, and personal preferences. Hence, we begin to develop personalized models of asker satisfaction to predict whether a particular question author will be satisfied with the answers contributed by the community participants. We formalize this problem, and explore a variety of content, structure, and interaction features for this task using standard machine learning techniques. Our experimental evaluation over thousands of real questions indicates that indeed it is beneficial to personalize satisfaction predictions when sufficient prior user history exists, significantly improving accuracy over a "one-size-fits-all" prediction model.
Random Measurement Bases, Quantum State Distinction and Applications to the Hidden Subgroup Problem
Authors: Jaikumar Radhakrishnan, Martin R&#x00f6;tteler, Pranab Sen
Venue: Algorithmica (2009)

We show that measuring any two low rank quantum states in a random orthonormal basis gives, with high probability, two probability distributions having total variation distance at least a universal constant times the Frobenius distance between the two states. This implies that for any finite ensemble of quantum states there is a single POVM that distinguishes between every pair of states from the ensemble by at least a constant times their Frobenius distance; in fact, with high probability a random POVM, under a suitable definition of randomness, suffices. There are examples of ensembles with constant pairwise trace distance where a single POVM cannot distinguish pairs of states by much better than their Frobenius distance, including the important ensemble of coset states of hidden subgroups of the symmetric group (Moore et&#x00a0;al., Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science, 2005). We next consider the random Fourier method for the hidden subgroup problem (HSP) which consists of Fourier sampling the coset state of the hidden subgroup using random orthonormal bases for the group representations. In cases where every representation of the group has polynomially bounded rank when averaged over the hidden subgroup, the random Fourier method gives a POVM for the HSP operating on one coset state at a time and using totally a polynomial number of coset states. In particular, we get such POVMs whenever the group and the hidden subgroup form a Gel&#x2019;fand pair, e.g., Abelian, dihedral and Heisenberg groups. This gives a positive counterpart to earlier negative results about random Fourier sampling when the above rank is exponentially large (Grigni et&#x00a0;al., Combinatorica 24(1):137&#x2013;154, 2004), which happens for example in the HSP in the symmetric group.
Brief Communication: ALIGN_MTX-An optimal pairwise textual sequence alignment program, adapted for using in sequence-structure alignment
Authors: Boris Vishnepolsky, Malak Pirtskhalava
Venue: Computational Biology and Chemistry (2009)

The presented program ALIGN_MTX makes alignment of two textual sequences with an opportunity to use any several characters for the designation of sequence elements and arbitrary user substitution matrices. It can be used not only for the alignment of amino acid and nucleotide sequences but also for sequence-structure alignment used in threading, amino acid sequence alignment, using preliminary known PSSM matrix, and in other cases when alignment of biological or non-biological textual sequences is required. This distinguishes it from the majority of similar alignment programs that make, as a rule, alignment only of amino acid or nucleotide sequences represented as a sequence of single alphabetic characters. ALIGN_MTX is presented as downloadable zip archive at http://www.imbbp.org/software/ALIGN_MTX/ and available for free use. As application of using the program, the results of comparison of different types of substitution matrix for alignment quality in distantly related protein pair sets were presented. Threading matrix SORDIS, based on side-chain orientation in relation to hydrophobic core centers with evolutionary change-based substitution matrix BLOSUM and using multiple sequence alignment information position-specific score matrices (PSSM) were taken for test alignment accuracy. The best performance shows PSSM matrix, but in the reduced set with lower sequence similarity threading matrix SORDIS shows the same performance and it was shown that combined potential with SORDIS and PSSM can improve alignment quality in evolutionary distantly related protein pairs.
Student Motivation and Performance in Scientific Problem Solving Simulations
Authors: Carole R. Beal, Ronald H. Stevens
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Students do not always use efficient strategies to solve scientific problems. Students' motivation beliefs were assessed through an on-line survey instrument, along with performance on easy and challenging multimedia science problem sets. Results indicated that female students reported lower self-efficacy and higher concerns about their performance than male students. Students' initial strategies predicted overall performance on the harder problem sets. In addition, although there was no difference in initial strategy, students' motivational beliefs predicted overall performance. Results suggest that both cognitive and motivational factors influence students' strategic efficacy.
Accessing the content of Greek historical documents
Authors: Anastasios Kesidis, Eleni Galiotou, Basilis Gatos, Aristomenis Lampropoulos, Ioannis Pratikakis, Ioanna Manolessou, Angela Ralli
Venue: Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data (2009)

In this paper, we propose an alternative method for accessing the content of Greek historical documents printed during the 17th and 18th centuries by searching words directly in digitized documents based on word spotting, without the use of an optical character recognition engine. We describe a methodology according to which synthetic word images are created from keywords. These images are compared to all the words in the digitized documents while user feedback is used in order to refine the search procedure. In order to improve the efficiency of accessing and searching, we have used natural language processing techniques that comprise (i) a morphological generator for early Modern Greek which provides the users with the ability to search documents using only a word stem and locate all the corresponding inflected word forms and (ii) a synonym dictionary which facilitates access to the semantic context of documents and enriches the results of the search process.
Event matching using the transitive closure of dependency relations
Authors: Daniel M. Bikel, Vittorio Castelli
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper describes a novel event-matching strategy using features obtained from the transitive closure of dependency relations. The method yields a model capable of matching events with an F-measure of 66.5%.
Second order duality for nondifferentiable minimax programming problems with generalized convexity
Authors: Z. Husain, Anurag Jayswal, I. Ahmad
Venue: Journal of Global Optimization (2009)

In this paper, we are concerned with a class of nondifferentiable minimax programming problem and its two types of second order dual models. Weak, strong and strict converse duality theorems from a view point of generalized convexity are established. Our study naturally unifies and extends some previously known results on minimax programming.
Chaos Control of Lorenz System Using Small Gain Theorem
Authors: Lei Wang, Jian-Hao Xu, Ti-Biao Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper studies the problem of controlling chaos in Lorenz system. By dividing Lorenz system into two subsystems, the small gain theorem is used to design linear feedback controllers to make the equilibrium points of the controlled system globally asymptotically stable. Thus chaos in Lorenz system disappears under the controller.
Randomness And Complexity, from Leibniz To Chaitin
Authors: Cristian S. Calude, Cristian S. Calude
Venue:  (2007)

The book is a collection of papers written by a selection of eminent authors from around the world in honour of Gregory Chaitin s 60th birthday. This is a unique volume including technical contributions, philosophical papers and essays.
Quasi-quadratic elliptic curve point counting using rigid cohomology
Authors: Hendrik Hubrechts
Venue: Journal of Symbolic Computation (2009)

Let E be a nonsupersingular elliptic curve over the finite field with p^n elements. We present a deterministic algorithm that computes the zeta function and hence the number of points of such a curve E in time quasi-quadratic in n. An older algorithm having the same time complexity uses the canonical lift of E, whereas our algorithm uses rigid cohomology combined with a deformation approach. An implementation in small odd characteristic turns out to give very good results.
Dynamic Hedging Under Jump Diffusion with Transaction Costs
Authors: J. S. Kennedy, P. A. Forsyth, K. R. Vetzal
Venue: Operations Research (2009)

If the price of an asset follows a jump diffusion process, the market is in general incomplete. In this case, hedging a contingent claim written on the asset is not a trivial matter, and other instruments besides the underlying must be used to hedge in order to provide adequate protection against jump risk. We devise a dynamic hedging strategy that uses a hedge portfolio consisting of the underlying asset and liquidly traded options, where transaction costs are assumed present due to a relative bid-ask spread. At each rebalance time, the hedge weights are chosen to simultaneously (i) eliminate the instantaneous diffusion risk by imposing delta neutrality, and (ii) minimize an objective that is a linear combination of a jump risk and transaction cost penalty function. Because reducing the jump risk is a competing goal vis-à-vis controlling for transaction cost, the respective components in the objective must be appropriately weighted. Hedging simulations of this procedure are carried out, and our results indicate that the proposed dynamic hedging strategy provides sufficient protection against the diffusion and jump risk while not incurring large transaction costs.
Role and channel assignments for wireless mesh networks using hybrid approach
Authors: Andy An-Kai Jeng, Rong-Hong Jan
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

The wireless mesh network has been considered one of the most promising techniques to extend the broadband access to the last mile. To utilize multiple channels on more than one interface, a number of approaches have been proposed. In particular, the hybrid strategy that combines the benefits of high channel diversity and low coordination cost has seen growing interest in recent studies. In this paper, we define two optimization problems, named the role assignment and the semi-fixed channel assignment, to characterize the unique feature in the hybrid strategy. We proved that the two problems are NP-hard even if the transmission ranges of interfaces are equal. In order to solve our problems in reasonable time, we design efficient algorithms. For the role assignment problem, we give an 1/2-approximate algorithm to find a nearly optimal solution. For the semi-fixed channel assignment problem, a heuristic algorithm, based on transferring from a coloring-based problem, is proposed. Experimental results show that optimizing the defined problems is indeed beneficial to improve the network throughput, and the proposed algorithms are significantly superior to existing methods.
Utilizing domain models for application design and validation
Authors: Iris Reinhartz-Berger, Arnon Sturm
Venue: Information and Software Technology (2009)

Domain analysis enables identifying families of applications and capturing their terminology in order to assist and guide system developers to design valid applications in the domain. One major way of carrying out the domain analysis is modeling. Several studies suggest using metamodeling techniques, feature-oriented approaches, or architectural-based methods for modeling domains and specifying applications in those domains. However, these methods mainly focus on representing the domain knowledge, providing insufficient guidelines (if any) for creating application models that satisfy the domain rules and constraints. In particular, validation of the application models which include application-specific knowledge is insufficiently dealt. In order to fill these lacks, we propose a general approach, called Application-based DOmain Modeling (ADOM), which enables specifying domains and applications similarly, (re)using domain knowledge in application models, and validating the application models against the relevant domain models. In this paper we present the ADOM approach, demonstrating its application to UML 2.0 class and sequence diagrams.
Novel direct digital frequency synthesis with direct analog output architecture based on artificial neural networks
Authors: Khosro Rajabpour Moghaddam
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

This paper presents a new architecture for direct digital frequency synthesis (DDS), which employs artificial neural networks for phase to sine amplitude conversion with direct analog output without using DAC and ROM. Also, as a contribution to electronic implementation of neural networks, a quasi-sigmoid non-linearity circuit is proposed.
Fighting Phishing with Discriminative Keypoint Features
Authors: Kuan-Ta Chen, Jau-Yuan Chen, Chun-Rong Huang, Chu-Song Chen
Venue: IEEE Internet Computing (2009)

Phishing is a form of online identity theft associated with both social engineering and technical subterfuge and is a major threat to information security and personal privacy. Here, the authors present an effective image-based antiphishing scheme based on discriminative keypoint features in Web pages. Their invariant content descriptor, the Contrast Context Histogram (CCH), computes the similarity degree between suspicious and authentic pages. The results show that the proposed scheme achieves high accuracy and low error rates.
A nonlinear perturbative scheme to solve weight optimization problem of high dimensional model representation (HDMR)
Authors: Burcu Tunga, Metin Demiralp
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

One way to increase the approximating quality of the High Dimensional Model Representation (HDMR) truncations is to increase the truncation order. However this is not generally desired for practical reasons if the order climbs to the multivariances beyond the bivariance. In these circumstances the other alternative is preferred. It is to change the structure of HDMR. This can be done either by using a different but again orthogonal geometry or by changing the structure of the weight function. Weight optimization is based on the constancy maximization and in fact gives different importances to the function values at different points of the HDMR domain. Weight function is considered as the square of a linear combination of certain basis functions and the linear combination coefficients are determined to maximize the constancy. The resulting equations are nonlinear. This work attempts to solve these equations by expanding unknowns around their certain nominal values.
A Neural Based WSN Mote Trajectory Reconstruction for Mining Periodic Patterns
Authors: Alfredo Petrosino, Antonino Staiano
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

The problem of reconstruction and mining object trajectories is of interest in the applications of mining transport enterprise data concerning with the route followed by its delivery vans in order to optimize time and space deliveries. The paper investigates the case of Wireless Sensor Network (WSN) technology, not primarily designed for localization, and reports a technique based on recurrent neural networks to reconstruct the trajectory shape of a moving object (a sensor on a Lego train) from the sensor accelerometer data and to recover its localization. The obtained patterns are thus mined to detecting periodic or frequent patterns, exploiting a recently proposed technique based on clustering algorithms and associative rules to assert the ability of the proposed approach to track WSN mote localizations.
Hometown websites: continuous maintenance of cross-border connections
Authors: Luis A. Castro, Victor M. Gonzalez
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

Information and Communication Technologies (ICT) become particularly relevant in contexts where place-based communities get dispersed and migrants look for ways to keep strong connections to the homeland. This paper presents the case of a website currently being used by migrants and non-migrants of a dispersed community to keep in touch with each other as well as to keep connected with daily life in their hometown. In particular, this work aims to understand the main types of information conveyed as well as temporal patterns of community exchanges as afforded by the website. This work analyses and classifies Guestbook entries, Photos and News notes suggesting that people use the site to reconnect, strengthen their local identity and be part of community life. We found out that user-generated content tend to increase during periods when there are fewer visits to the website. Results presented here are relevant towards understanding the nature and role played by ICTs in maintaining cross-border connections.
Rank-Based Transformation in Measuring Semantic Relatedness
Authors: Bartosz Broda, Maciej Piasecki, Stan Szpakowicz
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

Rank weight functions had been shown to increase the accuracy of measures of semantic relatedness for Polish. We present a generalised ranking principle and demonstrate its effect on a range of established measures of semantic relatedness, and on a different language. The results confirm that the generalised transformation method based on ranking brings an improvement over several well-known measures.
Neurodynamics of Cognition and Consciousness, 1st edition
Authors: Leonid I. Perlovsky, Robert Kozma
Venue: Understanding Complex Systems (2007)

This book addresses dynamical aspects of brain functions and cognition. Experimental evidence in humans and other mammalians indicates that complex neurodynamics is crucial for the emergence of higher-level intelligence. Dynamical neural systems with encoding in limit cycle and non-convergent attractors have gained increasing popularity in the past decade. The role of synchronization, desynchronization, and intermittent synchronization on cognition has been studied extensively by various authors, in particular by authors contributing to the present volume. This volume gives an overview of recent advances in this interdisciplinary field of cognitive science related to dynamics of cognition, including experimental studies, dynamical modelling and interpretation of cognitive experiments, and theoretical approaches. The following topics are covered in this book: spatio-temporal dynamics of neural correlates of higher-level cognition; dynamical neural memories, including continuous and discrete approaches; mathematical and physical models of cognition; experiments on dynamical aspects of cognition; interpretation of normal and abnormal cognitive behaviours.