ppxscal/embedding_network huggingface dataset:
An Incremental Technique for Automata-Based Decision Procedures
Authors: Gulay Unel, David Toman
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

Automata-based decision procedures commonly achieve optimal complexity bounds. However, in practice, they are often outperformed by sub-optimal (but more local-search based) techniques, such as tableaux, on many practical reasoning problems. This discrepancy is often the result of automata-style techniques global approach to the problem and the consequent need for constructing an extremely large automaton. This is in particular the case when reasoning in theories consisting of large number of relatively simple formulas, such as descriptions of database schemes, is required. In this paper, we propose techniques that allow us to approach a μ-calculus satisfiability problem in an incremental fashion and without the need for re-computation. In addition, we also propose heuristics that guide the problem partitioning in a way that is likely to reduce the size of the problems that need to be solved.
Composable Formal Security Analysis: Juggling Soundness, Simplicity and Efficiency
Authors: Ran Canetti
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

A security property of a protocol is composable if it remains intact even when the protocol runs alongside other protocols in the same system. We describe a method for asserting composable security properties, and demonstrate its usefulness. In particular, we show how this method can be used to provide security analysis that is formal, relatively simple, and still does not make unjustified abstractions of the underlying cryptographic algorithms in use. It can also greatly enhance the feasibility of automated security analysis of systems of realistic size.
Epiflow Based Stereo Fusion
Authors: Hongsheng Zhang, Shahriar Negahdaripour
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

3-D reconstruction from images sequences has been the center topic of computer vision. Real-time applications call for causal processing of stereo sequences, as they are acquired, covering different regions of the scene. The first step is to compute the current stereo disparity, and recursive map building often requires fusing with the previous estimate. In this paper, the epiflow framework [1], originally proposed for establishing matches among stereo feature pairs is generalized to devise an iterative causal algorithm for stereo disparity map fusion. In the context of disparity fusion, quadruplet correspondence of the epiflow tracking algorithm becomes reminiscent of the "closest point" of the 3-D ICP algorithm. Unlike ICP, the 2-D epiflow framework permits incorporating both photometric and geometrical constraints, estimation of the stereo rig motion as supplementary information, as well as identifying local inconsistencies between the two disparity maps. Experiments with real data validate the proposed approach, and improved converge compared to the ICP algorithm.
Interference and Congestion Aware Reservations in Wireless Multi-hop Networks
Authors: Stéphane Rousseau, Laure Lebrun, Hervé Aïache, Vania Conan
Venue: Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks (2008)

Multi-hop wireless networks are dynamically forming networks of radio equipped nodes. Most of the early work has been motivated by scenarios where nodes are mobile, leading to both theoretical results for the capacity of the network [1] and to practical proposals for routing protocols [2]. With the recent deployment of community wireless networks, more specific attention has been given to multi-hop wireless networks composed of both mobile mesh clients and more static mesh routers which form the backbone of the wireless mesh and provide the clients with access to the Internet [3].
Spatio-temporal Road Condition Forecasting with Markov Chains and Artificial Neural Networks
Authors: Konsta Sirvio, Jaakko Hollmén
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Preservation of the road assets value in an efficient manner is an important aim for developed road administrations. The task requires accurate road maintenance that is planned in advance. Forecasting road condition in the future is a prerequisite for optimisation of maintenance treatments. In this study two hybrid methods are introduced for forecasting road roughness and rutting. Markovian models outperform artificial neural network models and roughness can be forecast more accurately than rutting.
Successful joint venture strategies based on data mining
Authors: Jin Hyung Kim, So Young Sohn
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

The purpose of this study is to propose types of joint ventures that can increase the competiti veness of a company in the marketplace. We examine the characteristics of individual venture enterprises based on technology. We considered sixteen Technology Evaluation Attributes (TEA) in order to categori ze companies into four groups. Next, we used a multinomial logistic regression model to identify the sig nificant characteristics of a venture company that successfully predicts group membership. Based on this information, we propose various forms of joint venture which compliment each other and produce higher overall competence. The results of this study can provide important feedback information to academics, p olicy-makers, and venture capitalists.
On the State Complexity of Complements, Stars, and Reversals of Regular Languages
Authors: Galina Jirásková
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

We examine the deterministic and nondeterministic state complexity of complements, stars, and reversals of regular languages. Our results are as follows: 1 The nondeterministic state complexity of the complement of an n-state NFA language over a five-letter alphabet may reach each value in the range from logn to 2 n . 1 The state complexity of the star (reversal) of an n-state DFA language over a growing alphabet may reach each value in the range from 1 to $\frac{3}{4}2^n$ (from logn to 2 n , respectively). 1 The nondeterministic state complexity of the star (reversal) of an n-state NFA binary language may reach each value in the range from 1 to n + 1 (from n ¿ 1 to n + 1, respectively). We also obtain some partial results on the nondeterministic state complexity of the complements of binary regular languages. As a bonus, we get an exponential number of values that are non-magic, which improves a similar result of Geffert (Proc. 7th DCFS, Como, Italy, 23---37).
Comparative studies of the model evaluation criterions mmre and pred in software cost estimation research
Authors: Dan Port, Marcel Korte
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Software cost model research results depend on model accuracy criteria such as MMRE and PRED. Despite criticism, MMRE has emerged as the de facto standard criterion. Many alternatives have been proposed and studied, surprisingly however PRED, the second most popular criterion, has not been extensively studied. This work attempts to fill this gap in the literature and expand the understanding and use of evaluation criterion in general. The majority of this work is empirically based, applying MMRE and PRED to a number of COCOMO model variations with respect to a simulated data set and four publicly available cost estimation data sets. We replicate a number of results based on MMRE and extend them to PRED. We study qualities of MMRE and PRED as sample estimator statistics for parameters of a cost model error distribution. Standard error is used to ensure greater confidence in replicated and new results based on sample data.
Noncausal Optimal Tracking of Linear Switched Systems
Authors: Gou Nakura
Venue: Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control (2008)

In this paper we consider the noncausal optimal tracking problem on the finite time interval for linear switched systems. We consider the problem to obtain the solution of both optimal switching sequences and optimal control inputs such that the tracking error is minimized. In this paper we assume that information of reference signals is known a priori for the whole time interval and utilize its information so that the tracking performace becomes better. We study a computation method of the optimal performance including some information of tracking errors and present an iterative algorithm to determine the optimal timing and optimal tracking performance numerically.
Harold Locke Hazen, 1901-1980
Authors: Gordon S. Brown
Venue: IEEE Annals of the History of Computing (1981)

Harold L. Hazen, Dean Emeritus of the Graduate School at the Massachusetts Institute of Technology, who died in Belmont, Massachusetts, on February 21, 1980, was one of this country's early pioneers in the field of machine computation and automatic control. 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
Coordination in Multi-Agent Systems: Towards a Technology of Agreement
Authors: Sascha Ossowski
Venue: Proceedings of the 6th German conference on Multiagent System Technologies (2008)

It is commonly accepted that coordination is a key characteristic of multi-agent systems and that, in turn, the capability of coordinating with others constitutes a centrepiece of agenthood. However, the key elements of coordination models, mechanisms, and languages for multi-agent systems are still subject to considerable debate. This paper provides a brief overview of different approaches to coordination in multi-agent systems. It will then show how these approaches relate to current efforts working towards a paradigm for smart, next-generation distributed systems, where coordination is based on the concept of agreement between computational agents.
A constrained regression technique for cocomo calibration
Authors: Vu Nguyen, Bert Steece, Barry Boehm
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Building cost estimation models is often considered a search problem in which the solver should return an optimal solution satisfying an objective function. This solution also needs to meet certain constraints. For example, a solution for the estimates coefficients of COCOMO models must be non-negative. In this research, we introduce a constrained regression technique that uses objective functions and constraints to estimate the coefficients of the COCOMO models. To access the performance of the proposed technique, we run a cross-validation procedure and compare the prediction accuracy from different approaches such as least squares, stepwise, Lasso, and Ridge regression. Our result suggests that the regression model that minimizes the sum of relative errors and imposes non-negative coefficients is a favorable technique for calibrating the COCOMO model parameters.
A framework for generating some discrete sets with disjoint components by using uniform distributions
Authors: Péter Balázs
Venue: Theoretical Computer Science (2008)

Discrete tomography deals with the reconstruction of discrete sets from few projections. Assuming that the set to be reconstructed belongs to a certain class of discrete sets with some geometrical properties is a commonly used technique to reduce the number of possibly many different solutions of the same reconstruction problem. The average performance of reconstruction algorithms are often tested on such classes by choosing elements of a given class from uniform random distributions. This paper presents a general framework for generating discrete sets with disjoint connected components using uniform distributions. Especially, the uniform random generation of hv-convex discrete sets and Q-convex discrete sets according to the size of the minimal bounding rectangle are discussed.
Analysis of Human Motion, Based on the Reduction of Multidimensional Captured Data --- Application to Hand Gesture Compression, Segmentation and Synthesis
Authors: Sylvie Gibet, Pierre-François Marteau
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

This paper describes a method to analyze human motion, based on the reduction of multidimensional captured motion data. A Dynamic Programming Piecewise Linear Approximation model is used to automatically extract in an optimal way key-postures distributed along the motion data. This non uniform sub-sampling can be exploited for motion compression, segmentation, or re-synthesis. It has been applied on arm end-point motion for 3D or 6D trajectories. The analysis method is then evaluated, using an approximation of the curvature and the tangential velocity, which turns out to be robust to noise and can be calculated on multidimensional data.
Making Classical Honest Verifier Zero Knowledge Protocols Secure against Quantum Attacks
Authors: Sean Hallgren, Alexandra Kolla, Pranab Sen, Shengyu Zhang
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

We show that any problem that has a classical zero-knowledge protocol against the honest verifier also has, under a reasonable condition, a classical zero-knowledge protocol which is secure against all classical and quantum polynomial time verifiers, even cheating ones. Here we refer to the generalized notion of zero-knowledge with classical and quantum auxiliary inputs respectively.Our condition on the original protocol is that, for positive instances of the problem, the simulated message transcript should be quantum computationally indistinguishable from the actual message transcript. This is a natural strengthening of the notion of honest verifier computational zero-knowledge, and includes in particular, the complexity class of honest verifier statistical zero-knowledge. Our result answers an open question of Watrous [Wat06], and generalizes classical results by Goldreich, Sahai and Vadhan [GSV98], and Vadhan [Vad06] who showed that honest verifier statistical, respectively computational, zero knowledge is equal to general statistical, respectively computational, zero knowledge.
Models of successful adoption and implementation for it projects in the public sector
Authors: Charles Nichols
Venue:  (2008)

Improper adoption and implementation of information technology (IT) can negatively affect organizational effectiveness, including the waste of resources and errant delivery of services. However, the problem of which factors affect IT projects, alignment against IT adoption models, technologies, and which knowledge management tools are utilized in the public (PU) and private (PR) sectors remains unclear. The purpose of the present study was to delineate IT differences between the public and private sectors. This was done under such theoretical frameworks as the technology acceptance model (TAM) and the theory of reasoned action (TRA). The study used the descriptive quantitative research method. This cross-sectional survey of PU and PR IT professionals was analyzed using ANOVA, Binomial, and MANOVA statistics. Senior leadership, funding, and IT methodologies were among those identified as key factors that affect IT projects. Findings suggest that the public sector is behind the private sector in IT governance, funding, and IT implementation. The data also suggests the public sector may be unnecessarily inefficient specifically because of these IT deficits. The findings show that TAM is most appropriate to align with the public sector. These findings have strong implications for social change. By building IT into public policy programs at the design stage, rather than implementing IT as an afterthought, and by focusing senior leadership on IT technologies, it is possible that public sector organizations can deliver services to the people more efficiently and more quickly with fewer errors, resulting in a healthier, safer, and more prosperous society.
The Zurich Trusted Information Channel --- An Efficient Defence Against Man-in-the-Middle and Malicious Software Attacks
Authors: Thomas Weigold, Thorsten Kramp, Reto Hermann, Frank Höring, Peter Buhler, Michael Baentsch
Venue: Proceedings of the 1st international conference on Trusted Computing and Trust in Information Technologies: Trusted Computing - Challenges and Applications (2008)

This paper introduces the Zurich Trusted Information Channel (ZTIC, for short), a cost-efficient and easy-to-use approach to defend online services from man-in-the-middle and malicious software attacks. A small, cheap to manufacture and zero-installation USB device with a display runs a highly efficient security software stack providing the communications endpoint between server and customer. The insecure user PC is used solely to relay IP packets and display non-critical transaction information. All critical information is parsed out of the mutually-authenticated SSL/TLS connections that the ZTIC establishes to the server and shown on the display for explicit user approval.
Frame Based Features
Authors: Stefan Schacht, Jacques Koreman, Christoph Lauer, Andrew Morris, Dalei Wu, Dietrich Klakow
Venue: Speaker Classification I: Fundamentals, Features, and Methods (2007)

In this chapter we will discuss feature extraction methods for speaker classification. We introduce linear predictive coding, mel frequency cepstral coefficients and wavelets and perform experimental studies on AURORA and TIMIT data. For the speaker identification task, we can show that wavelets are beneficial.
Towards Agent-Oriented Relevant Information
Authors: Laurence Cholvy, Stéphanie Roussel
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

In this paper, we give some elements about agent-oriented relevance. For that, we define a new modal operator $R_a^Q $ so that $R_a^Q \varphi $ means that φ is relevant for agent a concerning the request Q. We discuss properties of this new operator, as well as its extensions and limits.
Compatibility of Scalapack with the Discrete Wavelet Transform
Authors: Liesner Acevedo, Victor M. Garcia, Antonio M. Vidal
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Parallelization of the Discrete Wavelet Transform (DWT) oriented to linear algebra applications, specially the solution of large linear systems, is studied in this paper. We propose that for parallel applications using linear algebra and wavelets, it can be advantageous to use directly the two-dimensional block cyclic distribution (2DBC), used in ScaLAPACK [1]. Although the parallel computation of the DWT may be faster with other data distributions, the efficiency of the 2DBC distribution for some linear algebra applications can make it more appropriate. We have tested this approach implementing a preconditioner for iterative solution of linear systems, which uses wavelets and was proposed in [2]. The results using the 2DBC Distribution are better than those obtained with a popular parallel data distribution for computing wavelets, the "Communication-Efficient" scheme proposed in [3].
A New Proactive Defense Model Based on Intrusion Deception and Traceback
Authors: Junfeng Tian, Ning Li
Venue: Information Security and Cryptology: Third SKLOIS Conference, Inscrypt 2007, Xining, China, August 31 - September 5, 2007, Revised Selected Papers (2007)

Along with the fast development of the Internet, the traditional passive defense measures have shortcomings and can not deal with the increasingly serious network security problems better. In this paper, a proactive network defense scheme is presented. And a new model of DTPM (Intrusion Deception and Traceback-based Proactive Defense Model) is established, which protects the precious network resources with the cooperation of intrusion deception and traceback. In the traceback module of DTPM, an improved approach APPM based on the PPM (Probabilistic Packet Marking) is developed, which makes up for the deficiency of the PPM in real-time capability and flexibility. By way of analyzing and comparing with other methods, this approach can decrease the overloads of many aspects and make traceback more efficient. The simulation experiment indicates the high performance and efficiency of this scheme.
Pheromone Based Dynamic Vaccination for Immune Algorithms
Authors: Yutao Qi, Fang Liu, Licheng Jiao
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The vaccination which is a most effective protection against the virus is also a helpful part of the artificial immune systems (AIS). A vaccination in AIS means modifying some genes of an antibody in accordance with priori knowledge so as to gain higher affinity with greater probability. Since vaccination is problem specific, what can we do if we have no idea about the problem? To address this, we propose a pheromone based dynamic vaccination for real coded immune algorithms in this paper. The pheromone which is a term of the ant colony system is used as a carrier of knowledge learned from population's evolution and acts as a producer of dynamic vaccines. Experiments on numerical optimization problems indicate that the pheromone based vaccination operator has the ability of acquiring useful information about the objective functions and developing effective vaccines dynamically.
Hybrid Control for an Autonomous Wheeled Mobile Robot Under Perturbed Torques
Authors: Leslie Astudillo, Oscar Castillo, Luis T. Aguilar, Ricardo Martínez
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

This paper focuses on the control of wheeled mobile robot under bounded torque disturbances. Hybrid tracking controller for the mobile robot was developed by considering its kinematic model and Euler-Lagrange dynamics. The procedure consist in minimizing the stabilization error of the kinematic model through genetic algorithm approach while attenuation to perturbed torques is made through type-2 Fuzzy Logic Control (FLC) via backstepping methodology. Type-2 fuzzy logic is proposed to synthesize the controller for the overall system which is claimed to be a robust tool for related applications. The theoretical results are illustrated through computer simulations of the closed-loop system.
Distance Learning of Graphically Intensive Material for Visually Impaired Students
Authors: Donal Fitzpatrick, Declan Mcmullen
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Historically the conveying of graphical materials to visually impaired students has been difficult to achieve. Various methods have evolved that aim to solve the problem, ranging from those based on technology to the construction of models which the learner, relying on tactile representations, can employ. The various methods used to depict graphically intensive data assume the presence of a teacher, or the inclusion of Braille labels. If a learner is operating in a distance-learning environment, or cannot read Braille there is little to no access to graphical material.This paper highlights the various methods used to convey diagrams to blind people. It outlines the perceived problems with applying these techniques to a distance-learning environment, and describes solutions which have been devised as part of the EU-sponsored project AHVITED (Audio Haptics for Visually Impaired Training and Education at a Distance) [1].