ppxscal/embedding_network huggingface dataset:
Secure Computability of Functions in the IT Setting with Dishonest Majority and Applications to Long-Term Security
Authors: Robin Künzler, Jörn Müller-Quade, Dominik Raub
Venue: Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography (2009)

While general secure function evaluation (SFE) with information-theoretical (IT) security is infeasible in presence of a corrupted majority in the standard model, there are SFE protocols (Goldreich et al. [STOC'87]) that are computationally secure (without fairness) in presence of an actively corrupted majority of the participants. Now, computational assumptions can usually be well justified at the time of protocol execution. The concern is rather a potential violation of the privacy of sensitive data by an attacker whose power increases over time. Therefore, we ask which functions can be computed with long-term security, where we admit computational assumptions for the duration of a computation, but require IT security (privacy) once the computation is concluded.Towards a combinatorial characterization of this class of functions, we also characterize the classes of functions that can be computed IT securely in the authenticated channels model in presence of passive, semi-honest, active, and quantum adversaries.
UML-F in the Design of an Agent-Oriented Software Framework
Authors: Daniel Cabrera-Paniagua, Claudio Cubillos
Venue: Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems (2008)

This paper presents a practical development of a study case regarding the utilization of a non-standard UML-F profile for the specification and documentation of an agent-oriented software framework devoted to the passenger transportation domain. UML-F profile does not pretend to replace the standard UML, but to use existing elements in it to represent in a better way the reality of a software framework through the adaptation of UML artifacts. The PASSI methodology has been used as base software engineering methodology for leveraging the multiagent architecture. As a way of ensuring proper development, it has been complemented with a general process for framework development.
Monotone Jacobi parameters and non-Szegő weights
Authors: Yury Kreimer, Yoram Last, Barry Simon
Venue: Journal of Approximation Theory (2009)

We relate asymptotics of Jacobi parameters to asymptotics of the spectral weights near the edges. Typical of our results is that for a"n=1, b"n=-Cn^-^@b (0
Proposed methodology for a data-driven simulation for estimating performance measures along signalized arterials in real-time
Authors: Dwayne Henclewood, Michael Hunter, Richard Fujimoto
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Congestion is one of the major issues facing today's transportation sector. Recent efforts have been geared toward providing traffic information to travelers, to facilitate better travel decisions, and transportation facility managers, to allow them to better manage traffic operations. Currently, real-time traffic information is primarily limited to freeways and a small subset of major arterials. This research effort explores the feasibility of an online data-driven simulation based methodology to address the lack of real-time arterial performance measures. The core of this methodology is the development of an online simulation tool that relies on commonly available arterial point sensor data, such as that from loop detectors or video cameras. Preliminary analysis indicates that the approach being considered is feasible as a model of the "real-world" was capable of reflecting performance measures with relatively high levels of accuracy. Limitations of the current research design and more immediate future directions are also presented.
Scalable Server and Storage Architectures for Video Streaming
Authors: David H. C. Du, Yen-Jen Lee
Venue: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2 (1999)

Ever since TV was introduced, visual communication has become our daily lives for some 50 years now. Wherever you go, large or small screens are there for news, drama, advertisement, shopping, travel guide, monitoring, games, or - you name it. However, the broadcast industry is undergone a second revolutionary change within a century.This wave of change is from analog to digital. It is by no means attributed to the advent of computer technology and high-speed network infrastructure. Digital format and transmission is advantageous in repeated use without losing quality of the content, advanced error correction over long-haul network, and easy integration with computerized office/home automation, etc. Traditional one-way visual communication gradually becomes more interactive and versatile. Over the last year or so, Internet-based video streaming has significantly picked up in the market place, followed almost a decade of intensive research and standard efforts. Not only we are interested in the current status of video streaming, but also the future that it is heading towards.Streaming21 is a company which developed several video streaming products for both education and entertainment industries. We shall offer some of field experiences too.
A leader-follower turn-taking model incorporating beat detection in musical human-robot interaction
Authors: Gil Weinberg, Brian Blosser
Venue: Proceedings of the 4th ACM/IEEE international conference on Human robot interaction (2009)

This paper describes the implementation of a leader-follower model in a musical HRI based on beat detection analysis and a novel turn taking scheme. The project enables Haile, a robotic percussionist, to fluidly interact with humans in the context of an improvisatory jam session. The long-term goal of this work is to facilitate dynamic interactions between humans and machines that will lead to novel and inspiring musical outcomes.
No-reference image quality assessment using modified extreme learning machine classifier
Authors: S. Suresh, R. Venkatesh Babu, H. J. Kim
Venue: Applied Soft Computing (2009)

In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.
An Architecture for Managing the Lifecycle of Business Goals for Partners in a Service Network
Authors: Marina Bitsaki, Ohla Danylevych, Willem-Jan Heuvel, George Koutras, Frank Leymann, Michele Mancioppi, Christos Nikolaou, Mike Papazoglou
Venue: Proceedings of the 1st European Conference on Towards a Service-Based Internet (2008)

Networks of interdependent organizations cooperate to produce goods or, nowadays, services that are of value to their markets as well as to the participating organizations. Such co-operations can be supported by corresponding business processes which are based on SOA technology. Developing and managing SOA-based business processes in such service networks necessitates a comprehensive architecture which is on the one hand grounded on solid design principles, and on the other hand capturing best-practices and experiences. Such an architecture is currently lacking. This paper outlines a first attempt to develop and validate an architecture for developing, monitoring, measuring and optimizing SOA-enabled business processes in service networks. A case study from the telecommunications industry is analyzed, and different aspects of service networks are addressed.
Dual Payoffs, Core and a Collaboration Mechanism Based on Capacity Exchange Prices in Multicommodity Flow Games
Authors: Luyi Gui, Özlem Ergun
Venue: Proceedings of the 4th International Workshop on Internet and Network Economics (2008)

Given a network in which the edge capacities and the commodities are owned by the players, a cooperative multicommodity flow (MCF) game (N,v) can be defined such that v(S), the value of a sub-coalition S, is the maximum profit achievable within S by shipping its commodities through the sub-network owned by its members. In this paper, we study MCF games under a partially decentralized setting where the players make their own routing and resource exchange decisions given a set of capacity prices determined by a central authority.
Large disjoint subgraphs with the same order and size
Authors: Y. Caro, R. Yuster
Venue: European Journal of Combinatorics (2009)

For a graph G let f(G) be the largest integer k such that there are two vertex-disjoint subgraphs of G, each with k vertices, and that induce the same number of edges. Clearly f(G)≤&lfloor;n/2&rfloor; but this is not always achievable. Our main result is that for any fixed &alpha;>0, if G has n vertices and at most n2-&alpha; edges, then f(G)=n/2-o(n), which is asymptotically optimal. The proof also yields a polynomial time randomized algorithm. More generally, let t be a fixed nonnegative integer and let H be a fixed graph. Let fH(G,t) be the largest integer k such that there are two k-vertex subgraphs of G having at most t vertices in common, that induce the same number of copies of H. We prove that if H has r vertices then fH(G,t)=Ω(n 1-(2r-1)/(2r+2t+1)). In particular, there are two subgraphs of the same order Ω(n1/2+1/(8r-2)) that induce the same number of copies of H and that have no copy of H in common.
Online learning strategies for classification of static data streams
Authors: M. Millán-Giraldo, J. S. Sánchez
Venue: Proceedings of the 8th WSEAS international conference on Distance learning and web engineering (2008)

This paper addresses the problem of online learning for static streaming data. The ultimate objective is to compare a number of very simple learning methods, mainly taken from the literature. We include a straightforward time-weighted strategy for forgetting obsolete objects from the reference set. Experiments are conducted on ten real data sets and using five different classifiers in order to identify which online learning model is the most suitable in terms of classifier performance.
Prediction of Time Series Data Using Multiresolution-based BiLinear Recurrent Neural Network
Authors: Dong Chul Park
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

A time series prediction scheme based on Multiresolution-based BiLinear Recurrent Neural Network (MBLRNN) is proposed in this paper. The proposed predictor is based on the BLRNN that has been proven to have robustabilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm for training the BLRNN so as to make it more robust for long-term prediction of the time series. The proposed MBLRNN-based predictor is applied to the long-term prediction of time series. Experiments and results on the Mackey-Glass Series data and Sunspot Series data show that the proposed MBLRNN outperforms both the traditional Multilayer Perceptron Type Neural Network (MLPNN) and the BLRNN in terms of the normalized mean square error (NMSE).
On user involvement in production of images used in visual authentication
Authors: Karen Renaud
Venue: Journal of Visual Languages and Computing (2009)

Recognition-based visual authentication schemes use a variety of different kinds of images. These mechanisms have now matured sufficiently that we should start considering tailoring and fine-tuning them-looking at ways to make them more efficient. Since these mechanisms use images, the obvious starting point in this tailoring process is to consider the image type or genre being used by the mechanism. Images have a number of properties which are bound to influence the efficacy of the visual authentication mechanism. In this paper the notion of essential and tuning image properties is proposed. The former are those that an image must exhibit or possess in order to be used in visual authentication at all-failure to meet these metrics should disqualify the image from use. Tuning properties, on the other hand, are properties that will improve the efficiency of the mechanism. The tuning property which is the focus of this paper is the user's involvement in the production of his/her secret images. A longitudinal study was carried out with a visual authentication system in order to determine the effectivity of images with three levels of user involvement, using randomly issued images from an archive, a set of hand-drawn images called doodles, and user-provided photos. The hand-drawn doodles performed better than both system-issued images and personal photos. Furthermore, whereas doodles demonstrate viability, personal photos have many insuperable problems which make them unsuitable for use in a security setting.
Adaptive correlation analysis in stream time series with sliding windows
Authors: Tiancheng Zhang, Dejun Yue, Yu Gu, Yi Wang, Ge Yu
Venue: Computers Mathematics with Applications (2009)

Correlation analysis is a very useful technique for similarity search in the field of data stream mining. The traditional method is not suitable for real time processing especially when the amount of stream sequences is very large. In this paper, we propose HBR (Hierarchical Boolean Representation), a novel technique for correlation analysis in stream time series. The original stream sequences are transformed into the Macro-Boolean series and the Micro-Boolean series successively, and the candidate correlation set can be easily obtained by simple bit operations. With huge amount of stream series, this method can quickly get the correlation pairs of series efficiently by reducing complicated calculation in a little space. Meanwhile, this approach can update the Boolean series incrementally with very low cost and adjust some important coefficients adaptively by the stream feature. The experimental evaluations show that HBR has excellent computation complexity with high accuracy.
An Efficient Reversible Image Authentication Method
Authors: Seungwu Han, Masaaki Fujiyoshi, Hitoshi Kiya
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This paper proposes an image authentication method that detects tamper and localizes tampered areas efficiently. The efficiency of the proposed method is summarized as the following three points. 1) This method offers coarse-to-fine tamper localization by hierarchical data hiding so that further tamper detection is suppressed for blocks labeled as genuine in the uppper layer. 2) Since the image feature description in the top layer is hidden over an image, the proposed method enciphers the data in the top layer rather than enciphers all data in all layers. 3) The proposed method is based on the reversible data hiding scheme that does not use highly-costed compression technique. These three points makes the proposed method superior to the conventional methods using compression techniques and methods using multi-tiered data hiding that requires integrity verification in many blocks even the image is genuine. Simulation results show the effectiveness of the proposed method.
On the Complexity of Obtaining Optimal Watermarking Schemes
Authors: Julien Lafaye
Venue: Proceedings of the 6th International Workshop on Digital Watermarking (2008)

In this paper, we try to answer the question: is the task of obtaining optimal watermarking schemes computationally feasible ? We introduce a formalism to express watermarking algorithms over finite domains of contents and exploit it to study two aspects of watermarking: the relevance of the detection process and its robustness. We formulate the search for an optimal scheme as an optimisation problem. We prove that (1) finding the algorithm which has the highest relevance for a fixed robustness against a known attack is NEXP-complete relatively to the domain encoding size and that (2) finding the algorithm which has the highest robustness for a fixed relevance is NP-complete relatively to the cardinality of the application domain. 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
Simplifying the Rate Control Scheme for Distributed Video Coding by Flexible Slepian-Wolf Decoding
Authors: Ralph Hänsel, Erika Müller
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

Distributed video coding (DVC) is an important topic for emerging applications, for example visual sensor networks and mobile video streaming. However, the major handicap applying DVC for real world applications is still the mandatory feedback channel. In previous approaches, the rate allocation algorithm was relying on feedback channel data. Commonly bit plane by bit plane decoding is done in a turbo code-based Slepian-Wolf decoder. In this paper inter bit plane decoding replaces the conventional method. The proposed inter bit plane decoding facilitates the rate control, whereas only the sum data rate has to be estimated/requested but not the data rate for each bit plane. This is one step forward to distributed video coding systems free of feedback channels.
Enhancing Channel Estimation in Cognitive Radio Systems by means of Bayesian Networks
Authors: Panagiotis Demestichas, Apostolos Katidiotis, Kostas A. Tsagkaris, Evgenia F. Adamopoulou, Konstantinos P. Demestichas
Venue: Wireless Personal Communications: An International Journal (2009)

This paper proposes enhancements to the channel(-state) estimation phase of a cognitive radio system. Cognitive radio devices have the ability to dynamically select their operating configurations, based on environment aspects, goals, profiles, preferences etc. The proposed method aims at evaluating the various candidate configurations that a cognitive transmitter may operate in, by associating a capability e.g., achievable bit-rate, with each of these configurations. It takes into account calculations of channel capacity provided by channel-state estimation information (CSI) and the sensed environment, and at the same time increases the certainty about the configuration evaluations by considering past experience and knowledge through the use of Bayesian networks. Results from comprehensive scenarios show the impact of our method on the behaviour of cognitive radio systems, whereas potential application and future work are identified.
ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO System (TRMS) with Less Memory and Time Usage
Authors: Thair Sh. Mahmoud, Mohammed H. Marhaban, Tang S. Hong, Sokchoo Ng
Venue: Proceedings of the 2009 International Conference on Advanced Computer Control (2009)

In this paper, Adaptive Neural Fuzzy Inference System (ANFIS) and Fuzzy Subtractive Clustering Method (FSCM) were used to solve non-linearity, trajectory, and interaction problems of Twin Rotor MIMO system (TRMS). Basically, four Fuzzy Logic Controllers (FLC) have been proposed to match the control objectives on TRMS. The four FLCs are considered as high consumers of memory and processing time relatively. New developed controllers are extracted to cope with these problems with less memory and time. Learning data were extracted from training the used conventional FLCs. Simulation results under MATLAB/Simulink® proved the improvement of response and simplicity of controller.
Transparent TCP acceleration
Authors: Sameer Ladiwala, Ramaswamy Ramaswamy, Tilman Wolf
Venue: Computer Communications (2009)

Transparent transmission control protocol (TCP) acceleration is a technique to increase TCP throughput without requiring any changes in end-system TCP implementations. By intercepting and relaying TCP connections inside the network, long end-to-end feedback control loops can be broken into several smaller control loops. This decrease in feedback delay allows accelerated TCP flows to react more quickly to packet loss and thus achieve higher throughput performance. Such TCP acceleration can be implemented on network processors, which are increasingly deployed in modern router systems. In our paper, we describe the functionality of transparent TCP acceleration in detail. Through simulation experiments, we quantify the benefits of TCP acceleration in a broad range of scenarios including flow-control bound and congestion-control bound connections. We study accelerator performance issues on an implementation based on the Intel IXP2350 network processor. Finally, we discuss a number of practical deployment issues and show that TCP acceleration can lead to higher system-wide utilization of link bandwidth.
Application of information-theoretic tests for the analysis of DNA sequences based on Markov chain models
Authors: N. Usotskaya, B. Ryabko
Venue: Computational Statistics Data Analysis (2009)

The statistical structure of DNA sequences is of great interest to molecular biology, genetics and the theory of evolution. One popular approach is sequence modeling using Markov processes of different orders, and further statistical estimation of their parameters. To continue the investigations according to this approach, tests for hypothesis testing are used to estimate the ''memory'' (or connectivity) of genetic texts and to solve the DNA-based problem relating to the phylogenetic system of various groups of organisms.
Embedded electronics in playful products
Authors: Dean Brown
Venue: Proceedings of the 3rd International Conference on Tangible and Embedded Interaction (2009)

This paper explores an approach to digital product design [1] through two prototype products, an augmented bedside table and a portable loud speaker. We discuss our design motivations, user case studies and common themes of simplicity, playfulness and ludic engagement [2].
The Average Solution of a Stochastic Nonlinear Schrodinger Equation under Stochastic Complex Non-homogeneity and Complex Initial Conditions
Authors: Magdy A. El-Tawil
Venue: Transactions on Computational Science III (2009)

In this paper, a stochastic nonlinear Schrodinger equation is studied under stochastic complex non-homogeneity in a limited time interval through homogeneous boundary conditions and complex initial conditions. The analytical solution for the linear case is introduced. The Wiener-Hermite expansion together with the perturbation method, the WHEP technique, is used to get approximate ensemble average of the stochastic solution process. Using Mathematica, the solution algorithm is tested through computing the first order approximation of the solution ensemble average. The method is illustrated through case studies which demonstrate the effects of the initial conditions as well as the input non-homogeneities.