OpenRaiser/Intern-Atlas huggingface dataset:
Rational Value of Information Estimation for Measurement Selection
Venue: arXiv cs.AI 2010
Year: 2010

Computing value of information (VOI) is a crucial task in various aspects of decision-making under uncertainty, such as in meta-reasoning for search; in selecting measurements to make, prior to choosing a course of action; and in managing the exploration vs. exploitation tradeoff. Since such applications typically require numerous VOI computations during a single run, it is essential that VOI be computed efficiently. We examine the issue of anytime estimation of VOI, as frequently it suffices to get a crude estimate of the VOI, thus saving considerable computational resources. As a case study, we examine VOI estimation in the measurement selection problem. Empirical evaluation of the proposed scheme in this domain shows that computational resources can indeed be significantly reduced, at little cost in expected rewards achieved in the overall decision problem.
Gossip Algorithms for Distributed Signal Processing
Venue: arXiv cs.DC 2010
Year: 2010

Gossip algorithms are attractive for in-network processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the computer science, control, signal processing, and information theory communities, developing faster and more robust gossip algorithms and deriving theoretical performance guarantees. This article presents an overview of recent work in the area. We describe convergence rate results, which are related to the number of transmitted messages and thus the amount of energy consumed in the network for gossiping. We discuss issues related to gossiping over wireless links, including the effects of quantization and noise, and we illustrate the use of gossip algorithms for canonical signal processing tasks including distributed estimation, source localization, and compression.
Agents, Bookmarks and Clicks: A topical model of Web traffic
Venue: arXiv cs.NI 2010
Year: 2010

Analysis of aggregate and individual Web traffic has shown that PageRank is a poor model of how people navigate the Web. Using the empirical traffic patterns generated by a thousand users, we characterize several properties of Web traffic that cannot be reproduced by Markovian models. We examine both aggregate statistics capturing collective behavior, such as page and link traffic, and individual statistics, such as entropy and session size. No model currently explains all of these empirical observations simultaneously. We show that all of these traffic patterns can be explained by an agent-based model that takes into account several realistic browsing behaviors. First, agents maintain individual lists of bookmarks (a non-Markovian memory mechanism) that are used as teleportation targets. Second, agents can retreat along visited links, a branching mechanism that also allows us to reproduce behaviors such as the use of a back button and tabbed browsing. Finally, agents are sustained by visiting novel pages of topical interest, with adjacent pages being more topically related to each other than distant ones. This modulates the probability that an agent continues to browse or starts a new session, allowing us to recreate heterogeneous session lengths. The resulting model is capable of reproducing the collective and individual behaviors we observe in the empirical data, reconciling the narrowly focused browsing patterns of individual users with the extreme heterogeneity of aggregate traffic measurements. This result allows us to identify a few salient features that are necessary and sufficient to interpret the browsing patterns observed in our data. In addition to the descriptive and explanatory power of such a model, our results may lead the way to more sophisticated, realistic, and effective ranking and crawling algorithms.
Protocol indepedence through disjoint encryption under Exclusive-OR
Venue: arXiv cs.CR 2010
Year: 2010

Multi-protocol attacks due to protocol interaction has been a notorious problem for security. Gutman-Thayer proved that they can be prevented by ensuring that encrypted messages are distinguishable across protocols, under a free algebra. In this paper, we prove that a similar suggestion prevents these attacks under commonly used operators such as Exclusive-OR, that induce equational theories, breaking the free algebra assumption.
Modeling Multi-Point Transport Protocol in P2P Networks
Venue: arXiv cs.NI 2010
Year: 2010

Traditional end-to-end congestion control mechanisms assume data transferring happens between each pair user. In contrast, in a P2P network, many peers may locally keep a copy of a specific data object. If the path between a pair of peers is congested, the requesting peer who wants to download data will switch to another peer in its neighbor peer list to fetch the data instead of decreasing the download rate from the current peer. Thus, it is critical to study the performance in multi-point-to-multi-point (M2M) transport protocol in a P2P network. In this paper, we build a mathematical model for identifying the key parameters for the M2M transport protocol and also the relationships among these parameters. Finally, we conduct simulation experiments to validate our model.
Improved Packet Forwarding Approach in Vehicular Ad Hoc Networks Using RDGR Algorithm
Venue: arXiv cs.NI 2010
Year: 2010

VANETs (Vehicular Ad hoc Networks) are highly mobile wireless ad hoc networks and will play an important role in public safety communications and commercial applications. Routing of data in VANETs is a challenging task due to rapidly changing topology and high speed mobility of vehicles. Position based routing protocols are becoming popular due to advancement and availability of GPS devices. One of the critical issues of VANETs are frequent path disruptions caused by high speed mobility of vehicle that leads to broken links which results in low throughput and high overhead . This paper argues the use of information on vehicles' movement information (e.g., position, direction, speed of vehicles) to predict a possible link-breakage event prior to its occurrence. So in this paper we propose a Reliable Directional Greedy routing (RDGR), a reliable position based routing approach which obtains position, speed and direction of its neighboring nodes from GPS. This approach incorporates potential score based strategy, which calculates link stability between neighbor nodes in distributed fashion for reliable forwarding of data packet.
On a family of cubic graphs containing the flower snarks
Venue: arXiv cs.DM 2010
Year: 2010

We consider cubic graphs formed with $k \geq 2$ disjoint claws $C_i \sim K_{1, 3}$ ($0 \leq i \leq k-1$) such that for every integer $i$ modulo $k$ the three vertices of degree 1 of $\ C_i$ are joined to the three vertices of degree 1 of $C_{i-1}$ and joined to the three vertices of degree 1 of $C_{i+1}$. Denote by $t_i$ the vertex of degree 3 of $C_i$ and by $T$ the set $\{t_1, t_2,..., t_{k-1}\}$. In such a way we construct three distinct graphs, namely $FS(1,k)$, $FS(2,k)$ and $FS(3,k)$. The graph $FS(j,k)$ ($j \in \{1, 2, 3\}$) is the graph where the set of vertices $\cup_{i=0}^{i=k-1}V(C_i) \setminus T$ induce $j$ cycles (note that the graphs $FS(2,2p+1)$, $p\geq2$, are the flower snarks defined by Isaacs \cite{Isa75}). We determine the number of perfect matchings of every $FS(j,k)$. A cubic graph $G$ is said to be {\em 2-factor hamiltonian} if every 2-factor of $G$ is a hamiltonian cycle. We characterize the graphs $FS(j,k)$ that are 2-factor hamiltonian (note that FS(1,3) is the "Triplex Graph" of Robertson, Seymour and Thomas \cite{RobSey}). A {\em strong matching} $M$ in a graph $G$ is a matching $M$ such that there is no edge of $E(G)$ connecting any two edges of $M$. A cubic graph having a perfect matching union of two strong matchings is said to be a {\em\Jaev}. We characterize the graphs $FS(j,k)$ that are \Jaesv.
Wavelet-Based Mel-Frequency Cepstral Coefficients for Speaker Identification using Hidden Markov Models
Venue: arXiv cs.SD 2010
Year: 2010

To improve the performance of speaker identification systems, an effective and robust method is proposed to extract speech features, capable of operating in noisy environment. Based on the time-frequency multi-resolution property of wavelet transform, the input speech signal is decomposed into various frequency channels. For capturing the characteristic of the signal, the Mel-Frequency Cepstral Coefficients (MFCCs) of the wavelet channels are calculated. Hidden Markov Models (HMMs) were used for the recognition stage as they give better recognition for the speaker's features than Dynamic Time Warping (DTW). Comparison of the proposed approach with the MFCCs conventional feature extraction method shows that the proposed method not only effectively reduces the influence of noise, but also improves recognition. A recognition rate of 99.3% was obtained using the proposed feature extraction technique compared to 98.7% using the MFCCs. When the test patterns were corrupted by additive white Gaussian noise with 20 dB S/N ratio, the recognition rate was 97.3% using the proposed method compared to 93.3% using the MFCCs.
Bit Error Rate Performance Analysis on Modulation Techniques of Wideband Code Division Multiple Access
Venue: arXiv cs.OH 2010
Year: 2010

In the beginning of 21st century there has been a dramatic shift in the market dynamics of telecommunication services. The transmission from base station to mobile or downlink transmission using M-ary Quadrature Amplitude modulation (QAM) and Quadrature phase shift keying (QPSK) modulation schemes are considered in Wideband-Code Division Multiple Access (W-CDMA) system. We have done the performance analysis of these modulation techniques when the system is subjected to Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading are considered in the channel. The research has been performed by using MATLAB 7.6 for simulation and evaluation of Bit Error Rate (BER) and Signal-To-Noise Ratio (SNR) for W-CDMA system models. It is shows that the analysis of Quadrature phases shift key and 16-ary Quadrature Amplitude modulations which are being used in wideband code division multiple access system, Therefore, the system could go for more suitable modulation technique to suit the channel quality, thus we can deliver the optimum and efficient data rate to mobile terminal.
Performance Analysis of Best suited Adaptive Equalization Algorithm for Optical Communication
Venue: arXiv cs.OH 2010
Year: 2010

Fiber optics is one of the highest bandwidth communication channel types in the current communication industry. The paper is to analyze a typical optical channel and perform channel equalization using an adaptive modified DFE with Activity Detection Guidance and Tap Decoupling algorithm. Evaluation can be made on the employment of the DFE algorithm and with enhancements, like Fractionally-Spaced equalization and Activity Detection Guidance, to improve its stability, steady-state error performance and convergence rate. The successful implementation of the Adaptive FS-DFE with ADG and TD technique offers an excellent alternative to linear equalization, which is known to be of little benefit for optical channels because of exorbitant noise enhancement. The FSE technique, when combined with the DFE, would offer improved effectiveness to amplitude distortion. As the impulse response of a typical optical link would have regions that are essentially zero, the employment of the activity detection scheme with Tap Decoupling would further enhance the steady-state error performance and convergence rate.
A secured Cryptographic Hashing Algorithm
Venue: arXiv cs.CR 2010
Year: 2010

Cryptographic hash functions for calculating the message digest of a message has been in practical use as an effective measure to maintain message integrity since a few decades. This message digest is unique, irreversible and avoids all types of collisions for any given input string. The message digest calculated from this algorithm is propagated in the communication medium along with the original message from the sender side and on the receiver side integrity of the message can be verified by recalculating the message digest of the received message and comparing the two digest values. In this paper we have designed and developed a new algorithm for calculating the message digest of any message and implemented t using a high level programming language. An experimental analysis and comparison with the existing MD5 hashing algorithm, which is predominantly being used as a cryptographic hashing tool, shows this algorithm to provide more randomness and greater strength from intrusion attacks. In this algorithm the plaintext message string is converted into binary string and fragmented into blocks of 128 bits after being padded with user defined padding bits. Then using a pseudo random number generator a key is generated for each block and operated with the respective block by a bitwise operator. This process is terated for the whole message and finally a fixed length message digest is obtained.
Scalable Group Management in Large-Scale Virtualized Clusters
Venue: arXiv cs.DC 2010
Year: 2010

To save cost, recently more and more users choose to provision virtual machine resources in cluster systems, especially in data centres. Maintaining a consistent member view is the foundation of reliable cluster managements, and it also raises several challenge issues for large scale cluster systems deployed with virtual machines (which we call virtualized clusters). In this paper, we introduce our experiences in design and implementation of scalable member view management on large-scale virtual clusters. Our research contributions are three-fold: 1) we propose a scalable and reliable management infrastructure that combines a peer-to-peer structure and a hierarchy structure to maintain a consistent member view in virtual clusters; 2) we present a light-weighted group membership algorithm that can reach the consistent member view within a single round of message exchange; and 3) we design and implement a scalable membership service that can provision virtual machines and maintain a consistent member view in virtual clusters. Our work is verified on Dawning 5000A, which ranked No.10 of Top 500 super computers in November, 2008.
Tuning CLD Maps
Venue: arXiv cs.CV 2010
Year: 2010

The Coherence Length Diagram and the related maps have been shown to represent a useful tool for image analysis. Setting threshold parameters is one of the most important issues when dealing with such applications, as they affect both the computability, which is outlined by the support map, and the appearance of the coherence length diagram itself and of defect maps. A coupled optimization analysis, returning a range for the basic (saturation) threshold, and a histogram based method, yielding suitable values for a desired map appearance, are proposed for an effective control of the analysis process.
Recognition of handwritten Roman Numerals using Tesseract open source OCR engine
Venue: arXiv cs.CV 2010
Year: 2010

The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with data samples of different persons to generate one user-independent language model, representing the handwritten Roman digit-set. The system is trained with 1226 digit samples collected form the different users. The performance is tested on two different datasets, one consisting of samples collected from the known users (those who prepared the training data samples) and the other consisting of handwritten data samples of unknown users. The overall recognition accuracy is obtained as 92.1% and 86.59% on these test datasets respectively.
Importance of Explicit Vectorization for CPU and GPU Software Performance
Venue: arXiv cs.DC 2010
Year: 2010

Much of the current focus in high-performance computing is on multi-threading, multi-computing, and graphics processing unit (GPU) computing. However, vectorization and non-parallel optimization techniques, which can often be employed additionally, are less frequently discussed. In this paper, we present an analysis of several optimizations done on both central processing unit (CPU) and GPU implementations of a particular computationally intensive Metropolis Monte Carlo algorithm. Explicit vectorization on the CPU and the equivalent, explicit memory coalescing, on the GPU are found to be critical to achieving good performance of this algorithm in both environments. The fully-optimized CPU version achieves a 9x to 12x speedup over the original CPU version, in addition to speedup from multi-threading. This is 2x faster than the fully-optimized GPU version.
Anonimos: An LP based Approach for Anonymizing Weighted Social Network Graphs
Venue: arXiv cs.DB 2010
Year: 2010

The increasing popularity of social networks has initiated a fertile research area in information extraction and data mining. Anonymization of these social graphs is important to facilitate publishing these data sets for analysis by external entities. Prior work has concentrated mostly on node identity anonymization and structural anonymization. But with the growing interest in analyzing social networks as a weighted network, edge weight anonymization is also gaining importance. We present Anónimos, a Linear Programming based technique for anonymization of edge weights that preserves linear properties of graphs. Such properties form the foundation of many important graph-theoretic algorithms such as shortest paths problem, k-nearest neighbors, minimum cost spanning tree, and maximizing information spread. As a proof of concept, we apply Anónimos to the shortest paths problem and its extensions, prove the correctness, analyze complexity, and experimentally evaluate it using real social network data sets. Our experiments demonstrate that Anónimos anonymizes the weights, improves k-anonymity of the weights, and also scrambles the relative ordering of the edges sorted by weights, thereby providing robust and effective anonymization of the sensitive edge-weights. Additionally, we demonstrate the composability of different models generated using Anónimos, a property that allows a single anonymized graph to preserve multiple linear properties.
A stochastic model of human visual attention with a dynamic Bayesian network
Venue: arXiv cs.CV 2010
Year: 2010

Recent studies in the field of human vision science suggest that the human responses to the stimuli on a visual display are non-deterministic. People may attend to different locations on the same visual input at the same time. Based on this knowledge, we propose a new stochastic model of visual attention by introducing a dynamic Bayesian network to predict the likelihood of where humans typically focus on a video scene. The proposed model is composed of a dynamic Bayesian network with 4 layers. Our model provides a framework that simulates and combines the visual saliency response and the cognitive state of a person to estimate the most probable attended regions. Sample-based inference with Markov chain Monte-Carlo based particle filter and stream processing with multi-core processors enable us to estimate human visual attention in near real time. Experimental results have demonstrated that our model performs significantly better in predicting human visual attention compared to the previous deterministic models.
Interval Slopes as Numerical Abstract Domain for Floating-Point Variables
Venue: arXiv cs.PL 2010
Year: 2010

The design of embedded control systems is mainly done with model-based tools such as Matlab/Simulink. Numerical simulation is the central technique of development and verification of such tools. Floating-point arithmetic, that is well-known to only provide approximated results, is omnipresent in this activity. In order to validate the behaviors of numerical simulations using abstract interpretation-based static analysis, we present, theoretically and with experiments, a new partially relational abstract domain dedicated to floating-point variables. It comes from interval expansion of non-linear functions using slopes and it is able to mimic all the behaviors of the floating-point arithmetic. Hence it is adapted to prove the absence of run-time errors or to analyze the numerical precision of embedded control systems.
A Spatial Crypto Technique for Secure Data Transmission
Venue: arXiv cs.CR 2010
Year: 2010

This paper presents a spatial encryption technique for secured transmission of data in networks. The algorithm is designed to break the ciphered data packets into multiple data which are to be packaged into a spatial template. A secure and efficient mechanism is provided to convey the information that is necessary for obtaining the original data at the receiver-end from its parts in the packets. An authentication code (MAC) is also used to ensure authenticity of every packet.
Gossip and Distributed Kalman Filtering: Weak Consensus under Weak Detectability
Venue: arXiv cs.IT 2010
Year: 2010

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.