Scalable Probabilistic Databases with Factor Graphs and MCMC

Abstract: Probabilistic databases play a crucial role in the management and understanding of uncertain data. However, incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or restrict the class of relational algebra formula under which they are closed. We propose an alternative approach where the underlying relational database always represents a single world, and an external factor graph encodes a distribution over possible worlds; Markov chain Monte Carlo (MCMC) inference is then used to recover this uncertainty to a desired level of fidelity. Our approach allows the efficient evaluation of arbitrary queries over probabilistic databases with arbitrary dependencies expressed by graphical models with structure that changes during inference. MCMC sampling provides efficiency by hypothesizing {\em modifications} to possible worlds rather than generating entire worlds from scratch. Queries are then run over the portions of the world that change, avoiding the onerous cost of running full queries over each sampled world. A significant innovation of this work is the connection between MCMC sampling and materialized view maintenance techniques: we find empirically that using view maintenance techniques is several orders of magnitude faster than naively querying each sampled world. We also demonstrate our system's ability to answer relational queries with aggregation, and demonstrate additional scalability through the use of parallelization.


A Note On the Bounds for the Generalized Fibonacci-p-Sequence and its Application in Data-Hiding

Abstract: In this paper, we suggest a lower and an upper bound for the Generalized Fibonacci-p-Sequence, for different values of p. The Fibonacci-p-Sequence is a generalization of the Classical Fibonacci Sequence. We first show that the ratio of two consecutive terms in generalized Fibonacci sequence converges to a p-degree polynomial and then use this result to prove the bounds for generalized Fibonacci-p sequence, thereby generalizing the exponential bounds for classical Fibonacci Sequence. Then we show how these results can be used to prove efficiency for data hiding techniques using generalized Fibonacci sequence. These steganographic techniques use generalized Fibonacci-p-Sequence for increasing number available of bit-planes to hide data, so that more and more data can be hidden into the higher bit-planes of any pixel without causing much distortion of the cover image. This bound can be used as a theoretical proof for efficiency of those techniques, for instance it explains why more and more data can be hidden into the higher bit-planes of a pixel, without causing considerable decrease in PSNR.


Analyzing the Performance of Active Queue Management Algorithms

Abstract: Congestion is an important issue which researchers focus on in the Transmission Control Protocol (TCP) network environment. To keep the stability of the whole network, congestion control algorithms have been extensively studied. Queue management method employed by the routers is one of the important issues in the congestion control study. Active queue management (AQM) has been proposed as a router-based mechanism for early detection of congestion inside the network. In this paper we analyzed several active queue management algorithms with respect to their abilities of maintaining high resource utilization, identifying and restricting disproportionate bandwidth usage, and their deployment complexity. We compare the performance of FRED, BLUE, SFB, and CHOKe based on simulation results, using RED and Drop Tail as the evaluation baseline. The characteristics of different algorithms are also discussed and compared. Simulation is done by using Network Simulator(NS2) and the graphs are drawn using X- graph.


Random polynomials and expected complexity of bisection methods for real solving

Abstract: Our probabilistic analysis sheds light to the following questions: Why do random polynomials seem to have few, and well separated real roots, on the average? Why do exact algorithms for real root isolation may perform comparatively well or even better than numerical ones? We exploit results by Kac, and by Edelman and Kostlan in order to estimate the real root separation of degree $d$ polynomials with i.i.d.\ coefficients that follow two zero-mean normal distributions: for SO(2) polynomials, the $i$-th coefficient has variance ${d \choose i}$, whereas for Weyl polynomials its variance is ${1/i!}$. By applying results from statistical physics, we obtain the expected (bit) complexity of \func{sturm} solver, $\sOB(r d^2 \tau)$, where $r$ is the number of real roots and $\tau$ the maximum coefficient bitsize. Our bounds are two orders of magnitude tighter than the record worst case ones. We also derive an output-sensitive bound in the worst case. The second part of the paper shows that the expected number of real roots of a degree $d$ polynomial in the Bernstein basis is $\sqrt{2d}\pm\OO(1)$, when the coefficients are i.i.d.\ variables with moderate standard deviation. Our paper concludes with experimental results which corroborate our analysis.


MLET: A Power Efficient Approach for TCAM Based, IP Lookup Engines in Internet Routers

Abstract: Routers are one of the important entities in computer networks specially the Internet. Forwarding IP packets is a valuable and vital function in Internet routers. Routers extract destination IP address from packets and lookup those addresses in their own routing table. This task is called IP lookup. Internet address lookup is a challenging problem due to the increasing routing table sizes. Ternary Content-Addressable Memories (TCAMs) are becoming very popular for designing high-throughput address lookup-engines on routers: they are fast, cost-effective and simple to manage. Despite the TCAMs speed, their high power consumption is their major drawback. In this paper, Multilevel Enabling Technique (MLET), a power efficient TCAM based hardware architecture has been proposed. This scheme is employed after an Espresso-II minimization algorithm to achieve lower power consumption. The performance evaluation of the proposed approach shows that it can save considerable amount of routing table's power consumption.


A Multi-agent Framework for Performance Tuning in Distributed Environment

Abstract: This paper presents the overall design of a multi-agent framework for tuning the performance of an application executing in a distributed environment. The multi-agent framework provides services like resource brokering, analyzing performance monitoring data, local tuning and also rescheduling in case of any performance problem on a specific resource provider. The paper also briefly describes the implementation of some part of the framework. In particular, job migration on the basis of performance monitoring data is particularly highlighted in this paper.


An Integrated Framework for Performance Analysis and Tuning in Grid Environment

Abstract: In a heterogeneous, dynamic environment, like Grid, post-mortem analysis is of no use and data needs to be collected and analysed in real time. Novel techniques are also required for dynamically tuning the application's performance and resource brokering in order to maintain the desired QoS. The objective of this paper is to propose an integrated framework for performance analysis and tuning of the application, and rescheduling the application, if necessary, to some other resources in order to adapt to the changing resource usage scenario in a dynamic environment.


Probabilistic verification and evaluation of Backoff procedure of the WSN ECo-MAC protocol

Abstract: Communication protocols and techniques are often evaluated using simulation techniques. However, the use of formal modeling and analysis techniques for verification and evaluation in particular for Wireless Sensor Networks (WSN) becomes a necessity. In this paper we present a formal analysis of the backoff procedure integrated in the medium access control protocol named ECo-MAC designed for WSN. We describe this backoff procedure in terms of discrete time Markov chains (DTMCs) and evaluated using the well known probabilistic model checker PRISM. After checking the different invariants of the proposed model, we study the effect of contention window length (in number of time contention unit) on the acceptable number of simultaneous senders in a neighborhood of a given receiver. The obtained quantitative results confirm those provided by the simulation using OPNET tool and justify the validity of the adopted value for the time contention unit TCU.


A UI Design Case Study and a Prototype of a Travel Search Engine

Abstract: We review a case study of a UI design project for a complete travel search engine system prototype for regular and corporate users. We discuss various usage scenarios, guidelines, and so for, and put them into a web-based prototype with screenshots and the like. We combined into our prototype the best features found at the time (2002) on most travel-like sites and added more to them as a part of our research. We conducted feasibility studies, review common design guidelines and Nelson's heuristics while constructing this work. The prototype is itself open-source, but has no backend functionality, as the focus is the user-centered design of such a system. While the prototype is mostly static, some dynamic activity is present through the use of PHP.


Simulations of Weighted Tree Automata

Abstract: Simulations of weighted tree automata (wta) are considered. It is shown how such simulations can be decomposed into simpler functional and dual functional simulations also called forward and backward simulations. In addition, it is shown in several cases (fields, commutative rings, Noetherian semirings, semiring of natural numbers) that all equivalent wta M and N can be joined by a finite chain of simulations. More precisely, in all mentioned cases there exists a single wta that simulates both M and N. Those results immediately yield decidability of equivalence provided that the semiring is finitely (and effectively) presented.


On the Finite Time Convergence of Cyclic Coordinate Descent Methods

Abstract: Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in machine learning. Reasons for this include its simplicity, speed and stability, as well as its competitive performance on $\ell_1$ regularized smooth optimization problems. Surprisingly, very little is known about its finite time convergence behavior on these problems. Most existing results either just prove convergence or provide asymptotic rates. We fill this gap in the literature by proving $O(1/k)$ convergence rates (where $k$ is the iteration counter) for two variants of cyclic coordinate descent under an isotonicity assumption. Our analysis proceeds by comparing the objective values attained by the two variants with each other, as well as with the gradient descent algorithm. We show that the iterates generated by the cyclic coordinate descent methods remain better than those of gradient descent uniformly over time.


Detecting Blackholes and Volcanoes in Directed Networks

Abstract: In this paper, we formulate a novel problem for finding blackhole and volcano patterns in a large directed graph. Specifically, a blackhole pattern is a group which is made of a set of nodes in a way such that there are only inlinks to this group from the rest nodes in the graph. In contrast, a volcano pattern is a group which only has outlinks to the rest nodes in the graph. Both patterns can be observed in real world. For instance, in a trading network, a blackhole pattern may represent a group of traders who are manipulating the market. In the paper, we first prove that the blackhole mining problem is a dual problem of finding volcanoes. Therefore, we focus on finding the blackhole patterns. Along this line, we design two pruning schemes to guide the blackhole finding process. In the first pruning scheme, we strategically prune the search space based on a set of pattern-size-independent pruning rules and develop an iBlackhole algorithm. The second pruning scheme follows a divide-and-conquer strategy to further exploit the pruning results from the first pruning scheme. Indeed, a target directed graphs can be divided into several disconnected subgraphs by the first pruning scheme, and thus the blackhole finding can be conducted in each disconnected subgraph rather than in a large graph. Based on these two pruning schemes, we also develop an iBlackhole-DC algorithm. Finally, experimental results on real-world data show that the iBlackhole-DC algorithm can be several orders of magnitude faster than the iBlackhole algorithm, which has a huge computational advantage over a brute-force method.


Arboricity, h-Index, and Dynamic Algorithms

Abstract: In this paper we present a modification of a technique by Chiba and Nishizeki [Chiba and Nishizeki: Arboricity and Subgraph Listing Algorithms, SIAM J. Comput. 14(1), pp. 210--223 (1985)]. Based on it, we design a data structure suitable for dynamic graph algorithms. We employ the data structure to formulate new algorithms for several problems, including counting subgraphs of four vertices, recognition of diamond-free graphs, cop-win graphs and strongly chordal graphs, among others. We improve the time complexity for graphs with low arboricity or h-index.


Opaque sets

Abstract: The problem of finding "small" sets that meet every straight-line which intersects a given convex region was initiated by Mazurkiewicz in 1916. We call such a set an {\em opaque set} or a {\em barrier} for that region. We consider the problem of computing the shortest barrier for a given convex polygon with $n$ vertices. No exact algorithm is currently known even for the simplest instances such as a square or an equilateral triangle. For general barriers, we present an approximation algorithm with ratio $1/2 + \frac{2 +\sqrt{2}}{\pi}=1.5867...$. For connected barriers we achieve the approximation ratio 1.5716, while for single-arc barriers we achieve the approximation ratio $\frac{\pi+5}{\pi+2} = 1.5834...$. All three algorithms run in O(n) time. We also show that if the barrier is restricted to the (interior and the boundary of the) input polygon, then the problem admits a fully polynomial-time approximation scheme for the connected case and a quadratic-time exact algorithm for the single-arc case.


Robustness and Generalization

Abstract: We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the testing error is close to the training error. This provides a novel approach, different from the complexity or stability arguments, to study generalization of learning algorithms. We further show that a weak notion of robustness is both sufficient and necessary for generalizability, which implies that robustness is a fundamental property for learning algorithms to work.


Likelihood that a pseudorandom sequence generator has optimal properties

Abstract: The authors prove that the probability of choosing a nonlinear filter of m-sequences with optimal properties, that is, maximum period and maximum linear complexity, tends assymptotically to 1 as the linear feedback shift register length increases.


A Simple Computational Model for Acceptance/Rejection of Binary Sequence Generators

Abstract: A simple binary model to compute the degree of balancedness in the output sequence of LFSR-combinational generators has been developed. The computational method is based exclusively on the handling of binary strings by means of logic operations. The proposed model can serve as a deterministic alternative to existing probabilistic methods for checking balancedness in binary sequence generators. The procedure here described can be devised as a first selective criterium for acceptance/rejection of this type of generators.


Modelling Nonlinear Sequence Generators in terms of Linear Cellular Automata

Abstract: In this work, a wide family of LFSR-based sequence generators, the so-called Clock-Controlled Shrinking Generators (CCSGs), has been analyzed and identified with a subset of linear Cellular Automata (CA). In fact, a pair of linear models describing the behavior of the CCSGs can be derived. The algorithm that converts a given CCSG into a CA-based linear model is very simple and can be applied to CCSGs in a range of practical interest. The linearity of these cellular models can be advantageously used in two different ways: (a) for the analysis and/or cryptanalysis of the CCSGs and (b) for the reconstruction of the output sequence obtained from this kind of generators.


A new algebraic technique for polynomial-time computing the number modulo 2 of Hamiltonian decompositions and similar partitions of a graph's edge set

Abstract: In Graph Theory a number of results were devoted to studying the computational complexity of the number modulo 2 of a graph's edge set decompositions of various kinds, first of all including its Hamiltonian decompositions, as well as the number modulo 2 of, say, Hamiltonian cycles/paths etc. While the problems of finding a Hamiltonian decomposition and Hamiltonian cycle are NP-complete, counting these objects modulo 2 in polynomial time is yet possible for certain types of regular undirected graphs. Some of the most known examples are the theorems about the existence of an even number of Hamiltonian decompositions in a 4-regular graph and an even number of such decompositions where two given edges e and g belong to different cycles (Thomason, 1978), as well as an even number of Hamiltonian cycles passing through any given edge in a regular odd-degreed graph (Smith's theorem). The present article introduces a new algebraic technique which generalizes the notion of counting modulo 2 via applying fields of Characteristic 2 and determinants and, for instance, allows to receive a polynomial-time formula for the number modulo 2 of a 4-regular bipartite graph's Hamiltonian decompositions such that a given edge and a given path of length 2 belong to different Hamiltonian cycles - hence refining/extending (in a computational sense) Thomason's result for bipartite graphs. This technique also provides a polynomial-time calculation of the number modulo 2 of a graph's edge set decompositions into simple cycles each containing at least one element of a given set of its edges what is a similar kind of extension of Thomason's theorem as well.


Online Learning of Noisy Data with Kernels

Abstract: We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with no restriction other than having zero mean and bounded variance. Our technique relies on a family of unbiased estimators for non-linear functions, which may be of independent interest. We show that a variant of online gradient descent can learn functions in any dot-product (e.g., polynomial) or Gaussian kernel space with any analytic convex loss function. Our variant uses randomized estimates that need to query a random number of noisy copies of each instance, where with high probability this number is upper bounded by a constant. Allowing such multiple queries cannot be avoided: Indeed, we show that online learning is in general impossible when only one noisy copy of each instance can be accessed.


Incorporating prediction models in the SelfLet framework: a plugin approach

Abstract: A complex pervasive system is typically composed of many cooperating \emph{nodes}, running on machines with different capabilities, and pervasively distributed across the environment. These systems pose several new challenges such as the need for the nodes to manage autonomously and dynamically in order to adapt to changes detected in the environment. To address the above issue, a number of autonomic frameworks has been proposed. These usually offer either predefined self-management policies or programmatic mechanisms for creating new policies at design time. From a more theoretical perspective, some works propose the adoption of prediction models as a way to anticipate the evolution of the system and to make timely decisions. In this context, our aim is to experiment with the integration of prediction models within a specific autonomic framework in order to assess the feasibility of such integration in a setting where the characteristics of dynamicity, decentralization, and cooperation among nodes are important. We extend an existing infrastructure called \emph{SelfLets} in order to make it ready to host various prediction models that can be dynamically plugged and unplugged in the various component nodes, thus enabling a wide range of predictions to be performed. Also, we show in a simple example how the system works when adopting a specific prediction model from the literature.


Generalized roof duality and bisubmodular functions

Abstract: Consider a convex relaxation $\hat f$ of a pseudo-boolean function $f$. We say that the relaxation is {\em totally half-integral} if $\hat f(x)$ is a polyhedral function with half-integral extreme points $x$, and this property is preserved after adding an arbitrary combination of constraints of the form $x_i=x_j$, $x_i=1-x_j$, and $x_i=\gamma$ where $\gamma\in\{0, 1, 1/2}$ is a constant. A well-known example is the {\em roof duality} relaxation for quadratic pseudo-boolean functions $f$. We argue that total half-integrality is a natural requirement for generalizations of roof duality to arbitrary pseudo-boolean functions. Our contributions are as follows. First, we provide a complete characterization of totally half-integral relaxations $\hat f$ by establishing a one-to-one correspondence with {\em bisubmodular functions}. Second, we give a new characterization of bisubmodular functions. Finally, we show some relationships between general totally half-integral relaxations and relaxations based on the roof duality.


Finding Your Literature Match -- A Recommender System

Abstract: The universe of potentially interesting, searchable literature is expanding continuously. Besides the normal expansion, there is an additional influx of literature because of interdisciplinary boundaries becoming more and more diffuse. Hence, the need for accurate, efficient and intelligent search tools is bigger than ever. Even with a sophisticated search engine, looking for information can still result in overwhelming results. An overload of information has the intrinsic danger of scaring visitors away, and any organization, for-profit or not-for-profit, in the business of providing scholarly information wants to capture and keep the attention of its target audience. Publishers and search engine engineers alike will benefit from a service that is able to provide visitors with recommendations that closely meet their interests. Providing visitors with special deals, new options and highlights may be interesting to a certain degree, but what makes more sense (especially from a commercial point of view) than to let visitors do most of the work by the mere action of making choices? Hiring psychics is not an option, so a technological solution is needed to recommend items that a visitor is likely to be looking for. In this presentation we will introduce such a solution and argue that it is practically feasible to incorporate this approach into a useful addition to any information retrieval system with enough usage.


A Note on Ordinal DFAs

Abstract: We prove the following theorem. Suppose that $M$ is a trim DFA on the Boolean alphabet $0,1$. The language $\L(M)$ is well-ordered by the lexicographic order $\slex$ iff whenever the non sink states $q,q.0$ are in the same strong component, then $q.1$ is a sink. It is easy to see that this property is sufficient. In order to show the necessity, we analyze the behavior of a $\slex$-descending sequence of words. This property is used to obtain a polynomial time algorithm to determine, given a DFA $M$, whether $\L(M)$ is well-ordered by the lexicographic order. Last, we apply an argument in \cite{BE,BEa} to give a proof that the least nonregular ordinal is $\omega^\omega $.


Classical BI: Its Semantics and Proof Theory

Abstract: We present Classical BI (CBI), a new addition to the family of bunched logics which originates in O'Hearn and Pym's logic of bunched implications BI. CBI differs from existing bunched logics in that its multiplicative connectives behave classically rather than intuitionistically (including in particular a multiplicative version of classical negation). At the semantic level, CBI-formulas have the normal bunched logic reading as declarative statements about resources, but its resource models necessarily feature more structure than those for other bunched logics; principally, they satisfy the requirement that every resource has a unique dual. At the proof-theoretic level, a very natural formalism for CBI is provided by a display calculus \`a la Belnap, which can be seen as a generalisation of the bunched sequent calculus for BI. In this paper we formulate the aforementioned model theory and proof theory for CBI, and prove some fundamental results about the logic, most notably completeness of the proof theory with respect to the semantics.


A Short Introduction to Model Selection, Kolmogorov Complexity and Minimum Description Length (MDL)

Abstract: The concept of overfitting in model selection is explained and demonstrated with an example. After providing some background information on information theory and Kolmogorov complexity, we provide a short explanation of Minimum Description Length and error minimization. We conclude with a discussion of the typical features of overfitting in model selection.


Mosaic: Policy Homomorphic Network Extension

Abstract: With the advent of large-scale cloud computing infrastructure, network extension and migration has emerged as a major challenge in the management of modern enterprise networks. Many enterprises are considering extending or relocating their network components, in whole or in part, to remote, private and public data centers, in order to attain scalability, failure resilience, and cost savings for their network applications. In this paper, we conduct a first rigorous study on the extension and migration of an enterprise network while preserving its performance and security requirements, such as layer 2/layer 3 reachability, and middle-box traversal through load balancer, intrusion detection and ACLs. We formulate this increasingly important problem, present preliminary designs, and conduct experiments to validate the feasibility of our designs.


Realizability algebras: a program to well order R

Abstract: The theory of classical realizability is a framework in which we can develop the proof-program correspondence. Using this framework, we show how to transform into programs the proofs in classical analysis with dependent choice and the existence of a well ordering of the real line. The principal tools are: The notion of realizability algebra, which is a three-sorted variant of the well known combinatory algebra of Curry. An adaptation of the method of forcing used in set theory to prove consistency results. Here, it is used in another way, to obtain programs associated with a well ordering of R and the existence of a non trivial ultrafilter on N.


A Short Introduction to Kolmogorov Complexity

Abstract: This is a short introduction to Kolmogorov Complexity. The interested reader is referred to the text books by Cover & Thomas as well as Li & V\'itanyi, which cover the fields of information theory and Kolmogorov complexity in depth and with all the necessary rigor.


Dichotic harmony for the musical practice

Abstract: The dichotic method of hearing sound adapts in the region of musical harmony. The algorithm of the separation of the being dissonant voices into several separate groups is proposed. For an increase in the pleasantness of chords the different groups of voices are heard out through the different channels of headphones. Is created two demonstration program for PC. Keywords: music, harmony, chord, dichotic listening, dissonance, consonance, headphones, pleasantness, midi.


A Trustworthy and well-organized data disseminating scheme for ad-hoc wsns

Abstract: Wireless Sensor Networks (WSNs) generate massive amount of live data and events sensed through dispersedly deployed tiny sensors. This generated data needed to be disseminate to the sink with slight consumption of network resources. One of the ways to efficiently transmit this bulk data is gossiping. An important consideration in gossip-based dissemination protocols is to keep routing table up to date. Considering the inherent resource constrained nature of adhoc wireless sensor networks, we propose a gossip based protocol that consumes little resources. Our proposed scheme aims to keep the routing table size R as low as possible yet it ensures that the diameter is small too. We learned the performance of our proposed protocol through simulations. Results show that our proposed protocol attains major improvement in network reachability and connectivity.


Defuzzification Method for a Faster and More Accurate Control

Abstract: Today manufacturers are using fuzzy logic in everything from cameras to industrial process control. Fuzzy logic controllers are easier to design and so are cheaper to produce. Fuzzy logic captures the impreciseness inherent in most input data. Electromechanical controllers respond better to imprecise input if their behavior was modeled on spontaneous human reasoning. In a conventional PID controller, what is modeled is the system or process being controlled, whereas in the Fuzzy logic controller, the focus is the human operator behavior. In the first case, the system is modeled analytically by a set of differential equations and their solutions tells the PID controllers how to adjust the system's control parameters for each type of behavior required 3. In the Fuzzy controller these adjustments are handled by a Fuzzy rule based expert system. A logical model of the thinking process a person might go through in the course of manipulating the system. This shift in focus from process to person involved changes the entire approach to automatic control problems.


A Discussion of Thin Client Technology for Computer Labs

Abstract: Computer literacy is not negotiable for any professional in an increasingly computerised environment. Educational institutions should be equipped to provide this new basic training for modern life. Accordingly, computer labs are an essential medium for education in almost any field. Computer labs are one of the most popular IT infrastructures for technical training in primary and secondary schools, universities and other educational institutions all over the world. Unfortunately, a computer lab is expensive, in terms of both initial purchase and annual maintenance costs, and especially when we want to run the latest software. Hence, research efforts addressing computer lab efficiency, performance or cost reduction would have a worldwide repercussion. In response to this concern, this paper presents a survey on thin client technology for computer labs in educational environments. Besides setting out the advantages and drawbacks of this technology, we aim to refute false prejudices against thin clients, identifying a set of educational scenarios where thin clients are a better choice and others requiring traditional solutions.


Deploying Wireless Networks with Beeps

Abstract: We present the \emph{discrete beeping} communication model, which assumes nodes have minimal knowledge about their environment and severely limited communication capabilities. Specifically, nodes have no information regarding the local or global structure of the network, don't have access to synchronized clocks and are woken up by an adversary. Moreover, instead on communicating through messages they rely solely on carrier sensing to exchange information. We study the problem of \emph{interval coloring}, a variant of vertex coloring specially suited for the studied beeping model. Given a set of resources, the goal of interval coloring is to assign every node a large contiguous fraction of the resources, such that neighboring nodes share no resources. To highlight the importance of the discreteness of the model, we contrast it against a continuous variant described in [17]. We present an O(1$ time algorithm that terminates with probability 1 and assigns an interval of size $\Omega(T/\Delta)$ that repeats every $T$ time units to every node of the network. This improves an $O(\log n)$ time algorithm with the same guarantees presented in \cite{infocom09}, and accentuates the unrealistic assumptions of the continuous model. Under the more realistic discrete model, we present a Las Vegas algorithm that solves $\Omega(T/\Delta)$-interval coloring in $O(\log n)$ time with high probability and describe how to adapt the algorithm for dynamic networks where nodes may join or leave. For constant degree graphs we prove a lower bound of $\Omega(\log n)$ on the time required to solve interval coloring for this model against randomized algorithms. This lower bound implies that our algorithm is asymptotically optimal for constant degree graphs.


Chains-into-Bins Processes

Abstract: The study of {\em balls-into-bins processes} or {\em occupancy problems} has a long history. These processes can be used to translate realistic problems into mathematical ones in a natural way. In general, the goal of a balls-into-bins process is to allocate a set of independent objects (tasks, jobs, balls) to a set of resources (servers, bins, urns) and, thereby, to minimize the maximum load. In this paper, we analyze the maximum load for the {\em chains-into-bins} problem, which is defined as follows. There are $n$ bins, and $m$ objects to be allocated. Each object consists of balls connected into a chain of length $\ell$, so that there are $m \ell$ balls in total. We assume the chains cannot be broken, and that the balls in one chain have to be allocated to $\ell$ consecutive bins. We allow each chain $d$ independent and uniformly random bin choices for its starting position. The chain is allocated using the rule that the maximum load of any bin receiving a ball of that chain is minimized. We show that, for $d \ge 2$ and $m\cdot\ell=O(n)$, the maximum load is $((\ln \ln m)/\ln d) +O(1)$ with probability $1-\tilde O(1/m^{d-1})$.


On Tractable Exponential Sums

Abstract: We consider the problem of evaluating certain exponential sums. These sums take the form $\sum_{x_1,...,x_n \in Z_N} e^{f(x_1,...,x_n) {2 \pi i / N}} $, where each x_i is summed over a ring Z_N, and f(x_1,...,x_n) is a multivariate polynomial with integer coefficients. We show that the sum can be evaluated in polynomial time in n and log N when f is a quadratic polynomial. This is true even when the factorization of N is unknown. Previously, this was known for a prime modulus N. On the other hand, for very specific families of polynomials of degree \ge 3, we show the problem is #P-hard, even for any fixed prime or prime power modulus. This leads to a complexity dichotomy theorem - a complete classification of each problem to be either computable in polynomial time or #P-hard - for a class of exponential sums. These sums arise in the classifications of graph homomorphisms and some other counting CSP type problems, and these results lead to complexity dichotomy theorems. For the polynomial-time algorithm, Gauss sums form the basic building blocks. For the hardness results, we prove group-theoretic necessary conditions for tractability. These tests imply that the problem is #P-hard for even very restricted families of simple cubic polynomials over fixed modulus N.


Pebbles and Branching Programs for Tree Evaluation

Abstract: We introduce the Tree Evaluation Problem, show that it is in logDCFL (and hence in P), and study its branching program complexity in the hope of eventually proving a superlogarithmic space lower bound. The input to the problem is a rooted, balanced d-ary tree of height h, whose internal nodes are labeled with d-ary functions on [k] = {1,...,k}, and whose leaves are labeled with elements of [k]. Each node obtains a value in [k] equal to its d-ary function applied to the values of its d children. The output is the value of the root. We show that the standard black pebbling algorithm applied to the binary tree of height h yields a deterministic k-way branching program with Theta(k^h) states solving this problem, and we prove that this upper bound is tight for h=2 and h=3. We introduce a simple semantic restriction called "thrifty" on k-way branching programs solving tree evaluation problems and show that the same state bound of Theta(k^h) is tight (up to a constant factor) for all h >= 2 for deterministic thrifty programs. We introduce fractional pebbling for trees and show that this yields nondeterministic thrifty programs with Theta(k^{h/2+1}) states solving the Boolean problem "determine whether the root has value 1". We prove that this bound is tight for h=2,3,4, and tight for unrestricted nondeterministic k-way branching programs for h=2,3.


Proviola: A Tool for Proof Re-animation

Abstract: To improve on existing models of interaction with a proof assistant (PA), in particular for storage and replay of proofs, we in- troduce three related concepts, those of: a proof movie, consisting of frames which record both user input and the corresponding PA response; a camera, which films a user's interactive session with a PA as a movie; and a proviola, which replays a movie frame-by-frame to a third party. In this paper we describe the movie data structure and we discuss a proto- type implementation of the camera and proviola based on the ProofWeb system. ProofWeb uncouples the interaction with a PA via a web- interface (the client) from the actual PA that resides on the server. Our camera films a movie by "listening" to the ProofWeb communication. The first reason for developing movies is to uncouple the reviewing of a formal proof from the PA used to develop it: the movie concept enables users to discuss small code fragments without the need to install the PA or to load a whole library into it. Other advantages include the possibility to develop a separate com- mentary track to discuss or explain the PA interaction. We assert that a combined camera+proviola provides a generic layer between a client (user) and a server (PA). Finally we claim that movies are the right type of data to be stored in an encyclopedia of formalized mathematics, based on our experience in filming the Coq standard library.


The complexity of weighted and unweighted #CSP

Abstract: We give some reductions among problems in (nonnegative) weighted #CSP which restrict the class of functions that needs to be considered in computational complexity studies. Our reductions can be applied to both exact and approximate computation. In particular, we show that a recent dichotomy for unweighted #CSP can be extended to rational-weighted #CSP.


On the Subspace of Image Gradient Orientations

Abstract: We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data population. We show that replacing intensities with gradient orientations and the $\ell_2$ norm with a cosine-based distance measure offers, to some extend, a remedy to this problem. Our scheme requires the eigen-decomposition of a covariance matrix and is as computationally efficient as standard $\ell_2$ PCA. We demonstrate some of its favorable properties on robust subspace estimation.


A note on concentration of submodular functions

Abstract: We survey a few concentration inequalities for submodular and fractionally subadditive functions of independent random variables, implied by the entropy method for self-bounding functions. The power of these concentration bounds is that they are dimension-free, in particular implying standard deviation O(\sqrt{\E[f]}) rather than O(\sqrt{n}) which can be obtained for any 1-Lipschitz function of n variables.


Evolving Genes to Balance a Pole

Abstract: We discuss how to use a Genetic Regulatory Network as an evolutionary representation to solve a typical GP reinforcement problem, the pole balancing. The network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network. We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.


Upper oriented chromatic number of undirected graphs and oriented colorings of product graphs

Abstract: The oriented chromatic number of an oriented graph $\vec G$ is the minimum order of an oriented graph $\vev H$ such that $\vec G$ admits a homomorphism to $\vev H$. The oriented chromatic number of an undirected graph $G$ is then the greatest oriented chromatic number of its orientations. In this paper, we introduce the new notion of the upper oriented chromatic number of an undirected graph $G$, defined as the minimum order of an oriented graph $\vev U$ such that every orientation $\vec G$ of $G$ admits a homomorphism to $\vec U$. We give some properties of this parameter, derive some general upper bounds on the ordinary and upper oriented chromatic numbers of Cartesian, strong, direct and lexicographic products of graphs, and consider the particular case of products of paths.


Constructing Path Efficient and Energy Aware Virtual Multicast Backbones in Static Ad Hoc Wireless Networks

Abstract: For stationary wireless ad hoc networks, one of the key challenging issues in routing and multicasting is to conserve as much energy as possible without compromising path efficiency measured as end-to-end delay. In this paper, we address the problem of path efficient and energy aware multicasting in static wireless ad hoc networks. We propose a novel distributed scalable algorithm for finding a virtual multicast backbone (VMB). Based on this VMB, we have further developed a multicasting scheme that jointly improves path efficiency and energy conservation. By exploiting inherent broadcast advantage of wireless communication and employing a more realistic energy consumption model for wireless communication which not only depends on radio propagation losses but also on energy losses in transceiver circuitry, our simulation results show that the proposed VMB-based multicasting scheme outperforms existing prominent tree based energy conserving, path efficient multicasting schemes.


Surface Parametrization of Nonsimply Connected Planar B\'ezier Regions

Abstract: A technique is described for constructing three-dimensional vector graphics representations of planar regions bounded by cubic B\'ezier curves, such as smooth glyphs. It relies on a novel algorithm for compactly partitioning planar B\'ezier regions into nondegenerate Coons patches. New optimizations are also described for B\'ezier inside-outside tests and the computation of global bounds of directionally monotonic functions over a B\'ezier surface (such as its bounding box or optimal field-of-view angle). These algorithms underlie the three-dimensional illustration and typography features of the TeX-aware vector graphics language Asymptote.


Note on Maximal Bisection above Tight Lower Bound

Abstract: In a graph $G=(V,E)$, a bisection $(X,Y)$ is a partition of $V$ into sets $X$ and $Y$ such that $|X|\le |Y|\le |X|+1$. The size of $(X,Y)$ is the number of edges between $X$ and $Y$. In the Max Bisection problem we are given a graph $G=(V,E)$ and are required to find a bisection of maximum size. It is not hard to see that $\lceil |E|/2 \rceil$ is a tight lower bound on the maximum size of a bisection of $G$. We study parameterized complexity of the following parameterized problem called Max Bisection above Tight Lower Bound (Max-Bisec-ATLB): decide whether a graph $G=(V,E)$ has a bisection of size at least $\lceil |E|/2 \rceil+k,$ where $k$ is the parameter. We show that this parameterized problem has a kernel with $O(k^2)$ vertices and $O(k^3)$ edges, i.e., every instance of Max-Bisec-ATLB is equivalent to an instance of Max-Bisec-ATLB on a graph with at most $O(k^2)$ vertices and $O(k^3)$ edges.


On Testing Constraint Programs

Abstract: The success of several constraint-based modeling languages such as OPL, ZINC, or COMET, appeals for better software engineering practices, particularly in the testing phase. This paper introduces a testing framework enabling automated test case generation for constraint programming. We propose a general framework of constraint program development which supposes that a first declarative and simple constraint model is available from the problem specifications analysis. Then, this model is refined using classical techniques such as constraint reformulation, surrogate and global constraint addition, or symmetry-breaking to form an improved constraint model that must be thoroughly tested before being used to address real-sized problems. We think that most of the faults are introduced in this refinement step and propose a process which takes the first declarative model as an oracle for detecting non-conformities. We derive practical test purposes from this process to generate automatically test data that exhibit non-conformities. We implemented this approach in a new tool called CPTEST that was used to automatically detect non-conformities on two classical benchmark programs, namely the Golomb rulers and the car-sequencing problem.


Optimal Gradient Clock Synchronization in Dynamic Networks

Abstract: We study the problem of clock synchronization in highly dynamic networks, where communication links can appear or disappear at any time. The nodes in the network are equipped with hardware clocks, but the rate of the hardware clocks can vary arbitrarily within specific bounds, and the estimates that nodes can obtain about the clock values of other nodes are inherently inaccurate. Our goal in this setting is to output a logical clock at each node such that the logical clocks of any two nodes are not too far apart, and nodes that remain close to each other in the network for a long time are better synchronized than distant nodes. This property is called gradient clock synchronization. Gradient clock synchronization has been widely studied in the static setting, where the network topology does not change. We show that the asymptotically optimal bounds obtained for the static case also apply to our highly dynamic setting: if two nodes remain at distance $d$ from each other for sufficiently long, it is possible to upper bound the difference between their clock values by $O(d \log (D / d))$, where $D$ is the diameter of the network. This is known to be optimal even for static networks. Furthermore, we show that our algorithm has optimal stabilization time: when a path of length $d$ appears between two nodes, the time required until the clock skew between the two nodes is reduced to $O(d \log (D / d))$ is $O(D)$, which we prove to be optimal. Finally, the techniques employed for the more intricate analysis of the algorithm for dynamic graphs provide additional insights that are also of interest for the static setting. In particular, we establish self-stabilization of the gradient property within $O(D)$ time.


Call-by-value, call-by-name and the vectorial behaviour of the algebraic \lambda-calculus

Abstract: We examine the relationship between the algebraic lambda-calculus, a fragment of the differential lambda-calculus and the linear-algebraic lambda-calculus, a candidate lambda-calculus for quantum computation. Both calculi are algebraic: each one is equipped with an additive and a scalar-multiplicative structure, and their set of terms is closed under linear combinations. However, the two languages were built using different approaches: the former is a call-by-name language whereas the latter is call-by-value; the former considers algebraic equalities whereas the latter approaches them through rewrite rules. In this paper, we analyse how these different approaches relate to one another. To this end, we propose four canonical languages based on each of the possible choices: call-by-name versus call-by-value, algebraic equality versus algebraic rewriting. We show that the various languages simulate one another. Due to subtle interaction between beta-reduction and algebraic rewriting, to make the languages consistent some additional hypotheses such as confluence or normalisation might be required. We carefully devise the required properties for each proof, making them general enough to be valid for any sub-language satisfying the corresponding properties.


Interactive Realizers and Monads

Abstract: We propose a realizability interpretation of a system for quantifier free arithmetic which is equivalent to the fragment of classical arithmetic without "nested" quantifiers, called here EM1-arithmetic. We interpret classical proofs as interactive learning strategies, namely as processes going through several stages of knowledge and learning by interacting with the "environment" and with each other. We give a categorical presentation of the interpretation through the construction of two suitable monads.


A Multiprocessor Communication Architecture For High Speed Networks

Abstract: Over the years, communication speed of networks has increased from a few Kbps to several Mbps, as also the bandwidth demand, Communication Protocols, however have not improved to that extent. With the advent of Wavelength Division Multiplexing (WDM), it is now possible to "tune" protocols to current and future demands. The purpose of this paper is to evolve a High Speed Network architecture, which will cater to the needs of bandwidth-consuming applications, such as voice, video and high definition image transmission.


Observable dynamics and coordinate systems for automotive target tracking

Abstract: We investigate several coordinate systems and dynamical vector fields for target tracking to be used in driver assistance systems. We show how to express the discrete dynamics of maneuvering target vehicles in arbitrary coordinates starting from the target's and the own (ego) vehicle's assumed dynamical model in global coordinates. We clarify the notion of "ego compensation" and show how non-inertial effects are to be included when using a body-fixed coordinate system for target tracking. We finally compare the tracking error of different combinations of target tracking coordinates and dynamical vector fields for simulated data.


A Proof for P =? NP Problem

Abstract: The $\textbf{P}$ vs. $\textbf{NP}$ problem is an important problem in contemporary mathematics and theoretical computer science. Many proofs have been proposed to this problem. This paper proposes a theoretic proof for $\textbf{P}$ vs. $\textbf{NP}$ problem. The central idea of this proof is a recursive definition for Turing machine (shortly TM) that accepts the encoding strings of valid TMs. By the definition, an infinite sequence of TM is constructed, and it is proven that the sequence includes all valid TMs. Based on these TMs, the class $\textbf{D}$ that includes all decidable languages and the union and reduction operators are defined. By constructing a language $\textbf{Up}$ of the union of $\textbf{D}$, it is proved that $\textbf{P}=\textbf{Up}$ and $\textbf{Up}=\textbf{NP}$, and the result $\textbf{P}=\textbf{NP}$ is proven.


Hierarchical and Nonhierarchical Three-Dimensional Underwater Wireless Sensor Networks

Abstract: In some underwater sensor networks, sensor nodes may be deployed at various depths of an ocean making those networks three-dimensional (3D). While most terrestrial sensor networks can usually be modeled as two dimensional (2D) networks, these underwater sensor networks must be modeled as 3D networks. This leads to new research challenges in the area of network architecture and topology. In this paper, we present two different network architectures for 3D underwater sensor networks. The first one is a hierarchical architecture that uses a relatively small number of robust backbone nodes to create the network where a large number of inexpensive sensors communicate with their nearest backbone nodes, and packets from a backbone node to the sink is routed through other backbone nodes. This hierarchical approach allows creating a network of smaller number of expensive backbone nodes while keeping the mobile sensors simple and inexpensive. Along with network topology, we also study energy efficiency and frequency reuse issues for such 3D networks. The second approach is a nonhierarchical architecture which assumes that all nodes are identical and randomly deployed. It partitions the whole 3D network space into identical cells and keeps one node active in each cell such that sensing coverage and connectivity are maintained while limiting the energy consumed. We also study closeness to optimality of our proposed scheme.


Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving

Abstract: Recent work in theoretical computer science and scientific computing has focused on nearly-linear-time algorithms for solving systems of linear equations. While introducing several novel theoretical perspectives, this work has yet to lead to practical algorithms. In an effort to bridge this gap, we describe in this paper two related results. Our first and main result is a simple algorithm to approximate the solution to a set of linear equations defined by a Laplacian (for a graph $G$ with $n$ nodes and $m \le n^2$ edges) constraint matrix. The algorithm is a non-recursive algorithm; even though it runs in $O(n^2 \cdot \polylog(n))$ time rather than $O(m \cdot polylog(n))$ time (given an oracle for the so-called statistical leverage scores), it is extremely simple; and it can be used to compute an approximate solution with a direct solver. In light of this result, our second result is a straightforward connection between the concept of graph resistance (which has proven useful in recent algorithms for linear equation solvers) and the concept of statistical leverage (which has proven useful in numerically-implementable randomized algorithms for large matrix problems and which has a natural data-analytic interpretation).


Stimulating Cooperation in Self-Organized Vehicular Networks

Abstract: A Vehicular Ad-hoc NETwork (VANET) is a special form of Mobile Ad-hoc Network designed to provide communications among nearby vehicles and between vehicles and nearby fixed roadside equipment. Its main goal is to improve safety and comfort for passengers, but it can also be used for commercial applications. In this latter case, it will be necessary to motivate drivers to cooperate and contribute to packet forwarding in Vehicle-to-Vehicle and Vehicle-to-Roadside communications. This paper examines the problem, analyzes the drawbacks of known schemes and proposes a new secure incentive scheme to stimulate cooperation in VANETs, taking into account factors such as time and distance.


Verifiable Network-Performance Measurements

Abstract: In the current Internet, there is no clean way for affected parties to react to poor forwarding performance: when a domain violates its Service Level Agreement (SLA) with a contractual partner, the partner must resort to ad-hoc probing-based monitoring to determine the existence and extent of the violation. Instead, we propose a new, systematic approach to the problem of forwarding-performance verification. Our mechanism relies on voluntary reporting, allowing each domain to disclose its loss and delay performance to its neighbors; it does not disclose any information regarding the participating domains' topology or routing policies beyond what is already publicly available. Most importantly, it enables verifiable performance measurements, i.e., domains cannot abuse it to significantly exaggerate their performance. Finally, our mechanism is tunable, allowing each participating domain to determine how many resources to devote to it independently (i.e., without any inter-domain coordination), exposing a controllable trade-off between performance-verification quality and resource consumption. Our mechanism comes at the cost of deploying modest functionality at the participating domains' border routers; we show that it requires reasonable processing and memory resources within modern network capabilities.


Improvement Cache Efficiency of Explicit Finite Element Procedure and its Application to Parallel Casting Solidification Simulation

Abstract: A simple method for improving cache efficiency of serial and parallel explicit finite procedure with application to casting solidification simulation over three-dimensional complex geometries is presented. The method is based on division of the global data to smaller blocks and treating each block independently from others at each time step. A novel parallel finite element algorithm for non-overlapped element-base decomposed domain is presented for implementation of serial and parallel version of the presented method. Effect of mesh reordering on the efficiency is also investigated. A simple algorithm is presented for high quality decomposition of decoupled global mesh. Our result shows 10-20 \% performance improvement by mesh reordering and 1.2-2.2 speedup with application of the presented cache efficient algorithm (for serial and parallel versions). Also the presented parallel solver (without cache-efficient feature) shows nearly linear speedup on the traditional Ethernet networked Linux cluster.


Virtual Texturing

Abstract: In this thesis a rendering system and an accompanying tool chain for Virtual Texturing is presented. Our tools allow to automatically retexture existing geometry in order to apply unique texturing on each face. Furthermore we investigate several techniques that try to minimize visual artifacts in the case that only a small amount of pages can be streamed per frame. We analyze the influence of different heuristics that are responsible for the page selection. Alongside these results we present a measurement method to allow the comparison of our heuristics.


Haptics in computer music : a paradigm shift

Abstract: With an historical point of view combined with a bibliographic overview, the article discusses the idea that haptic force feedback transducers correspond with a paradigm shift in our real-time tools for creating music. So doing, il shows that computer music may be regarded as a major field of research and application for haptics.


Dynamical issues in interactive representation of physical objects

Abstract: The quality of a simulator equipped with a haptic interface is given by the dynamical properties of its components: haptic interface, simulator and control system. Some application areas of such kind of simulator like musical synthesis, animation or more general, instrumental art have specific requirements as for the "haptic rendering" of small movements that go beyond the usual haptic interfaces allow. Object properties variability and different situations of object combination represent important aspects of such type of application which makes that the user can be interested as much in the restitution of certain global properties of an entire object domain as in the restitution of properties that are specific to an isolate object. In the traditional approaches, the usual criteria are founded on the paradigm of transparency and are related to the impedance error introduced by the technical aspects of the system. As a general aim, rather than to minimize these effects, we look to characterize them by physical metaphors conferring to haptic medium the role of a tool. This positioning leads to firstly analyze the natural human object interaction as a simplified evolutive system and then considers its synthesis in the case of the interactive physical simulation. By means of a frequential method, this approach is presented for some elementary configurations of the simulator


Flexible Authentication in Vehicular Ad hoc Networks

Abstract: A Vehicular Ad-Hoc Network (VANET) is a form of Mobile ad-hoc network, to provide communications among nearby vehicles and between vehicles and nearby fixed roadside equipment. The key operation in VANETs is the broadcast of messages. Consequently, the vehicles need to make sure that the information has been sent by an authentic node in the network. VANETs present unique challenges such as high node mobility, real-time constraints, scalability, gradual deployment and privacy. No existent technique addresses all these requirements. In particular, both inter-vehicle and vehicle-to-roadside wireless communications present different characteristics that should be taken into account when defining node authentication services. That is exactly what is done in this paper, where the features of inter-vehicle and vehicle-to-roadside communications are analyzed to propose differentiated services for node authentication, according to privacy and efficiency needs.


A Survey on Temporal Logics

Abstract: This paper surveys main and recent studies on temporal logics in a broad sense by presenting various logic systems, dealing with various time structures, and discussing important features, such as decidability (or undecidability) results, expressiveness and proof systems.


Real-time and Probabilistic Temporal Logics: An Overview

Abstract: Over the last two decades, there has been an extensive study on logical formalisms for specifying and verifying real-time systems. Temporal logics have been an important research subject within this direction. Although numerous logics have been introduced for the formal specification of real-time and complex systems, an up to date comprehensive analysis of these logics does not exist in the literature. In this paper we analyse real-time and probabilistic temporal logics which have been widely used in this field. We extrapolate the notions of decidability, axiomatizability, expressiveness, model checking, etc. for each logic analysed. We also provide a comparison of features of the temporal logics discussed.


Cellular Automata in Stream Ciphers

Abstract: A wide family of nonlinear sequence generators, the so-called clock-controlled shrinking generators, has been analyzed and identified with a subset of linear cellular automata. The algorithm that converts the given generator into a linear model based on automata is very simple and can be applied in a range of practical interest. Due to the linearity of these automata as well as the characteristics of this class of generators, a cryptanalytic approach can be proposed. Linear cellular structures easily model keystream generators with application in stream cipher cryptography.


An LP with Integrality Gap 1+epsilon for Multidimensional Knapsack

Abstract: In this note we study packing or covering integer programs with at most k constraints, which are also known as k-dimensional knapsack problems. For any integer k > 0 and real epsilon > 0, we observe there is a polynomial-sized LP for the k-dimensional knapsack problem with integrality gap at most 1+epsilon. The variables may be unbounded or have arbitrary upper bounds. In the packing case, we can also remove the dependence of the LP on the cost-function, yielding a polyhedral approximation of the integer hull. This generalizes a recent result of Bienstock on the classical knapsack problem.


Bounding the Impact of Unbounded Attacks in Stabilization

Abstract: Self-stabilization is a versatile approach to fault-tolerance since it permits a distributed system to recover from any transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an attractive feature of distributed systems that permits to cope with arbitrary malicious behaviors. Combining these two properties proved difficult: it is impossible to contain the spatial impact of Byzantine nodes in a self-stabilizing context for global tasks such as tree orientation and tree construction. We present and illustrate a new concept of Byzantine containment in stabilization. Our property, called Strong Stabilization enables to contain the impact of Byzantine nodes if they actually perform too many Byzantine actions. We derive impossibility results for strong stabilization and present strongly stabilizing protocols for tree orientation and tree construction that are optimal with respect to the number of Byzantine nodes that can be tolerated in a self-stabilizing context.


Self-Organized Authentication Architecture for Mobile Ad-hoc Networks

Abstract: This work proposes a new architecture, called Global Authentication Scheme for Mobile Ad-hoc Networks (GASMAN), for fully distributed and self-organized authentication. In this paper apart from describing all the GASMAN components, special emphasis is placed on proving that it fulfils every requirement of a secure distributed authentication scheme, including limited physical protection of broadcast medium, frequent route changes caused by mobility, lack of structured hierarchy, etc. Furthermore, an extensive analysis through simulation experiments in different scenarios is described and discussed.


Efficient System-Enforced Deterministic Parallelism

Abstract: Deterministic execution offers many benefits for debugging, fault tolerance, and security. Running parallel programs deterministically is usually difficult and costly, however - especially if we desire system-enforced determinism, ensuring precise repeatability of arbitrarily buggy or malicious software. Determinator is a novel operating system that enforces determinism on both multithreaded and multi-process computations. Determinator's kernel provides only single-threaded, "shared-nothing" address spaces interacting via deterministic synchronization. An untrusted user-level runtime uses distributed computing techniques to emulate familiar abstractions such as Unix processes, file systems, and shared memory multithreading. The system runs parallel applications deterministically both on multicore PCs and across nodes in a cluster. Coarse-grained parallel benchmarks perform and scale comparably to - sometimes better than - conventional systems, though determinism is costly for fine-grained parallel applications.


Efficient Algorithms and Data Structures for Massive Data Sets

Abstract: For many algorithmic problems, traditional algorithms that optimise on the number of instructions executed prove expensive on I/Os. Novel and very different design techniques, when applied to these problems, can produce algorithms that are I/O efficient. This thesis adds to the growing chorus of such results. The computational models we use are the external memory model and the W-Stream model. On the external memory model, we obtain the following results. (1) An I/O efficient algorithm for computing minimum spanning trees of graphs that improves on the performance of the best known algorithm. (2) The first external memory version of soft heap, an approximate meldable priority queue. (3) Hard heap, the first meldable external memory priority queue that matches the amortised I/O performance of the known external memory priority queues, while allowing a meld operation at the same amortised cost. (4) I/O efficient exact, approximate and randomised algorithms for the minimum cut problem, which has not been explored before on the external memory model. (5) Some lower and upper bounds on I/Os for interval graphs. On the W-Stream model, we obtain the following results. (1) Algorithms for various tree problems and list ranking that match the performance of the best known algorithms and are easier to implement than them. (2) Pass efficient algorithms for sorting, and the maximal independent set problems, that improve on the best known algorithms. (3) Pass efficient algorithms for the graphs problems of finding vertex-colouring, approximate single source shortest paths, maximal matching, and approximate weighted vertex cover. (4) Lower bounds on passes for list ranking and maximal matching. We propose two variants of the W-Stream model, and design algorithms for the maximal independent set, vertex-colouring, and planar graph single source shortest paths problems on those models.


Using machine learning to make constraint solver implementation decisions

Abstract: Programs to solve so-called constraint problems are complex pieces of software which require many design decisions to be made more or less arbitrarily by the implementer. These decisions affect the performance of the finished solver significantly. Once a design decision has been made, it cannot easily be reversed, although a different decision may be more appropriate for a particular problem. We investigate using machine learning to make these decisions automatically depending on the problem to solve with the alldifferent constraint as an example. Our system is capable of making non-trivial, multi-level decisions that improve over always making a default choice.


Evolution with Drifting Targets

Abstract: We consider the question of the stability of evolutionary algorithms to gradual changes, or drift, in the target concept. We define an algorithm to be resistant to drift if, for some inverse polynomial drift rate in the target function, it converges to accuracy 1 -- \epsilon , with polynomial resources, and then stays within that accuracy indefinitely, except with probability \epsilon , at any one time. We show that every evolution algorithm, in the sense of Valiant (2007; 2009), can be converted using the Correlational Query technique of Feldman (2008), into such a drift resistant algorithm. For certain evolutionary algorithms, such as for Boolean conjunctions, we give bounds on the rates of drift that they can resist. We develop some new evolution algorithms that are resistant to significant drift. In particular, we give an algorithm for evolving linear separators over the spherically symmetric distribution that is resistant to a drift rate of O(\epsilon /n), and another algorithm over the more general product normal distributions that resists a smaller drift rate. The above translation result can be also interpreted as one on the robustness of the notion of evolvability itself under changes of definition. As a second result in that direction we show that every evolution algorithm can be converted to a quasi-monotonic one that can evolve from any starting point without the performance ever dipping significantly below that of the starting point. This permits the somewhat unnatural feature of arbitrary performance degradations to be removed from several known robustness translations.


Learning Kernel-Based Halfspaces with the Zero-One Loss

Abstract: We describe and analyze a new algorithm for agnostically learning kernel-based halfspaces with respect to the \emph{zero-one} loss function. Unlike most previous formulations which rely on surrogate convex loss functions (e.g. hinge-loss in SVM and log-loss in logistic regression), we provide finite time/sample guarantees with respect to the more natural zero-one loss function. The proposed algorithm can learn kernel-based halfspaces in worst-case time $\poly(\exp(L\log(L/\epsilon)))$, for $\emph{any}$ distribution, where $L$ is a Lipschitz constant (which can be thought of as the reciprocal of the margin), and the learned classifier is worse than the optimal halfspace by at most $\epsilon$. We also prove a hardness result, showing that under a certain cryptographic assumption, no algorithm can learn kernel-based halfspaces in time polynomial in $L$.


Nominal Unification from a Higher-Order Perspective

Abstract: Nominal Logic is a version of first-order logic with equality, name-binding, renaming via name-swapping and freshness of names. Contrarily to higher-order logic, bindable names, called atoms, and instantiable variables are considered as distinct entities. Moreover, atoms are capturable by instantiations, breaking a fundamental principle of lambda-calculus. Despite these differences, nominal unification can be seen from a higher-order perspective. From this view, we show that nominal unification can be reduced to a particular fragment of higher-order unification problems: Higher-Order Pattern Unification. This reduction proves that nominal unification can be decided in quadratic deterministic time, using the linear algorithm for Higher-Order Pattern Unification. We also prove that the translation preserves most generality of unifiers.


Behavioral Simulations in MapReduce

Abstract: In many scientific domains, researchers are turning to large-scale behavioral simulations to better understand important real-world phenomena. While there has been a great deal of work on simulation tools from the high-performance computing community, behavioral simulations remain challenging to program and automatically scale in parallel environments. In this paper we present BRACE (Big Red Agent-based Computation Engine), which extends the MapReduce framework to process these simulations efficiently across a cluster. We can leverage spatial locality to treat behavioral simulations as iterated spatial joins and greatly reduce the communication between nodes. In our experiments we achieve nearly linear scale-up on several realistic simulations. Though processing behavioral simulations in parallel as iterated spatial joins can be very efficient, it can be much simpler for the domain scientists to program the behavior of a single agent. Furthermore, many simulations include a considerable amount of complex computation and message passing between agents, which makes it important to optimize the performance of a single node and the communication across nodes. To address both of these challenges, BRACE includes a high-level language called BRASIL (the Big Red Agent SImulation Language). BRASIL has object oriented features for programming simulations, but can be compiled to a data-flow representation for automatic parallelization and optimization. We show that by using various optimization techniques, we can achieve both scalability and single-node performance similar to that of a hand-coded simulation.


A Better Memoryless Online Algorithm for FIFO Buffering Packets with Two Values

Abstract: We consider scheduling packets with values in a capacity-bounded buffer in an online setting. In this model, there is a buffer with limited capacity $B$. At any time, the buffer cannot accommodate more than $B$ packets. Packets arrive over time. Each packet is associated with a non-negative value. Packets leave the buffer only because they are either sent or dropped. Those packets that have left the buffer will not be reconsidered for delivery any more. In each time step, at most one packet in the buffer can be sent. The order in which the packets are sent should comply with the order of their arrival time. The objective is to maximize the total value of the packets sent in an online manner. In this paper, we study a variant of this FIFO buffering model in which a packet's value is either 1 or $\alpha > 1$. We present a deterministic memoryless 1.304-competitive algorithm. This algorithm has the same competitive ratio as the one presented in (Lotker and Patt-Shamir. PODC 2002, Computer Networks 2003). However, our algorithm is simpler and does not employ any marking bits. The idea used in our algorithm is novel and different from all previous approaches applied for the general model and its variants. We do not proactively preempt one packet when a new packet arrives. Instead, we may preempt more than one 1-value packet when the buffer contains sufficiently many $\alpha$-value packets.


Morphonette: a morphological network of French

Abstract: This paper describes in details the first version of Morphonette, a new French morphological resource and a new radically lexeme-based method of morphological analysis. This research is grounded in a paradigmatic conception of derivational morphology where the morphological structure is a structure of the entire lexicon and not one of the individual words it contains. The discovery of this structure relies on a measure of morphological similarity between words, on formal analogy and on the properties of two morphological paradigms:


Optical phase extraction algorithm based on the continuous wavelet and the Hilbert transforms

Abstract: In this paper we present an algorithm for optical phase evaluation based on the wavelet transform technique. The main advantage of this method is that it requires only one fringe pattern. This algorithm is based on the use of a second {\pi}/2 phase shifted fringe pattern where it is calculated via the Hilbert transform. To test its validity, the algorithm was used to demodulate a simulated fringe pattern giving the phase distribution with a good accuracy.


An Ontology-based Context Aware System for Selective Dissemination of Information in a Digital Library

Abstract: Users of Institutional Repositories and Digital Libraries are known by their needs for very specific information about one or more subjects. To characterize users profiles and offer them new documents and resources is one of the main challenges of today's libraries. In this paper, a Selective Dissemination of Information service is described, which proposes an Ontology-based Context Aware system for identifying user's context (research subjects, work team, areas of interest). This system enables librarians to broaden users profiles beyond the information that users have introduced by hand (such as institution, age and language). The system requires a context retrieval layer to capture user information and behavior, and an inference engine to support context inference from many information sources (selected documents and users' queries).


Contention Based Routing in Mobile Ad Hoc Networks with Multiple Copies

Abstract: Routing the packets efficiently in mobile ad hoc network does not have end to end paths. Multiple copies are forwarded from the source to the destination. To deal with such networks, researches introduced flooding based routing schemes which leads to high probability of delivery. But the flooding based routing schemes suffered with contention and large delays. Here the proposed protocol "Spray Select Focus", sprays a few message copies into the network, neighbors receives a copy and by that relay nodes we are choosing the shortest route and then route that copy towards the destination. Previous works assumption is that there is no contention and dead ends. But we argue that contention and dead ends must be considered for finding efficiency in routing. So we are including a network which has contention and dead ends and we applied the proposed protocol. We can say that this protocol works well for the contention based network.


Scalable Energy Efficient Location Aware Multicast Protocol for MANET (SEELAMP)

Abstract: Multicast plays an important role in implementing the group communications in bandwidth scarce multihop mobile ad hoc networks. However, due to the dynamic topology of MANETs it is very difficult to build optimal multicast trees and maintaining group membership, making even more challenging to implement scalable and robust multicast in Mobile Ad hoc Networks (MANET). A scalable and energy efficient location aware multicast algorithm, called SEELAMP, for mobile ad hoc networks is presented in the paper that is based on creation of shared tree using the physical location of the nodes for the multicast sessions. It constructs a shared bi-directional multicast tree for its routing operations rather than a mesh, which helps in achieving more efficient multicast delivery. The algorithm uses the concept of small overlapped zones around each node for proactive topology maintenance with in the zone. Protocol depends on the location information obtained using a distributed location service, which effectively reduces the overheads for route searching and shared multicast tree maintenance. In this paper a new technique of local connectivity management is being proposed that attempts to improve the performance and reliability. It employs a preventive route reconfiguration to avoid the latency in case of link breakages and to prevent the network from splitting.


Criticism of Knapsack Encryption Scheme

Abstract: In this paper, we analyze a knapsack schemes. The one is suggested by Su, which is relied on a new method entitled permutation combination method. We demonstrate that this permutation method is useless to the security of the scheme. Since the special super increasing construction, we can break this scheme employ the algorithm provided by Shamir scheme. Finally, we provide an enhanced version of Su scheme to avoid these attacks.


Sensors Lifetime Enhancement Techniques in Wireless Sensor Networks - A Survey

Abstract: Wireless Sensor Networks are basically used for gathering information needed by smart environments but they are particularly useful in unattended situations where terrain, climate and other environmental constraints may hinder in the deployment of wired/conventional networks. Unlike traditional networks, these sensor networks do not have a continuous power supply at their disposal. Rather the individual sensors are battery operated and the lifetime of the individual sensors and thus the overall network depend heavily on duty cycle of these sensors. Analysis on WSNs shows that communication module is the main part which consumes most of the sensor energy and that is why energy conservation is the major optimization goal. Since routing protocols and MAC protocols directly access the communication module therefore the design of protocols in these two domains should take into account the energy conservation goal. In this paper, we discuss different state-of-the-art protocols both in MAC and routing domains that have been proposed for WSNs to achieve the overall goal of prolonging the network lifetime. The routing protocols in WSNs are generally categorized into three groups - data centric, hierarchical and location-based but we focus on only the first two categories because location-based routing protocols generally require a prior knowledge about sensors location which most of the times is not available due to random deployment of the sensors. We then discuss how schedule-based and contention-based MAC protocols can contribute to achieve optimal utilization of the limited energy resource by avoiding or reducing the chances of collisions and thus the need for retransmission.


A Study on Potential of Integrating Multimodal Interaction into Musical Conducting Education

Abstract: With the rapid development of computer technology, computer music has begun to appear in the laboratory. Many potential utility of computer music is gradually increasing. The purpose of this paper is attempted to analyze the possibility of integrating multimodal interaction such as vision-based hand gesture and speech interaction into musical conducting education. To achieve this purpose, this paper is focus on discuss some related research and the traditional musical conducting education. To do so, six musical conductors had been interviewed to share their musical conducting learning/ teaching experience. These interviews had been analyzed in this paper to show the syllabus and the focus of musical conducting education for beginners.


A Prioritized Access Point Algorithm for 802.11b Networks in a Lossy Environment

Abstract: In recent years, WLAN technology has been gaining popularity around the world with its sub standard 802.11b receiving major deployments in many indoor and outdoor environments. In this article we investigate the performance of IEEE 802.11b infrastructure networks in the lossless and lossy environments by means of a simulation study. Also, this study shows how the FIFO discipline of the 802.11b MAC affects on the global performance when at least one channel is under the influence of the bursty errors. Furthermore, this paper proposes a channel aware backoff algorithm for the Access Point (AP) to prioritize its transmissions and to accelerate the transmissions in the poor radio channels to enhance the performance of the real time applications. The final results of this simulation study showed that the proposed algorithm is able to enhance the throughput and the delay in lossy environment by an average of 49% and 83% respectively.


Democracy, essential element of the electronic government

Abstract: This paper emphasizes a determinant aim of identifying different approaches, as comparing to the education and democracy ways specific to e-government system. Introducing the information technology should offer the possibility by which reform processes of the government should become more efficient, transparent and much more public for the citizens; in this way, their ability of participating directly to government activities should prove the carrying out of a democratic and free frame. One of the essential issues of such phenomenon is that of proving that adopting the information and communication technology programs to government process or electronic government depends upon a series of external factors, such as the level of state's development, the cultural level, the frame of developing the structures of central and local public authority, criteria that differentiate the applicability of such system, to various countries. This difference is especially seen as comparing to the East states of European Union. Information systems can be applied in order to allow the citizens to monitor and coordinate the providing of local services; such exchanges have created trust and the feeling of influence, encouraging the participation to political life. Carrying into effect the new informational technologies, aiming to issuing, informing and to participation of citizens to political life, will model the concept of democracy within a new frame.


A Route Optimization technique for registered and unregistered CN's in NEMO

Abstract: As the demand of, requesting the Internet without any disturbance by the mobile users of any network is increasing the IETF started working on Network Mobility (NEMO). Maintaining the session of all the nodes in mobile network with its home network and external nodes can be provided by the basic Network Mobility support protocol. It provides mobility at IP level to complete networks, allowing a Mobile Network to change its point of attachment to the Internet, while maintaining the ongoing sessions of the nodes of the network. The Mobile Router (MR) manages the mobility even though the nodes don't know the status of mobility. This article discusses few basic concepts and limitations of NEMO protocol and proposes two ways to optimize the NEMO routing technique for registered and unregistered Correspondent Nodes (CN) of the Mobile Network Node (MNN).


A grid environment consisting of heterogeneous compute resources for high performance computation

Abstract: This paper has been withdrawn.


Image Segmentation by Using Threshold Techniques

Abstract: This paper attempts to undertake the study of segmentation image techniques by using five threshold methods as Mean method, P-tile method, Histogram Dependent Technique (HDT), Edge Maximization Technique (EMT) and visual Technique and they are compared with one another so as to choose the best technique for threshold segmentation techniques image. These techniques applied on three satellite images to choose base guesses for threshold segmentation image.


Software Effort Estimation using Radial Basis and Generalized Regression Neural Networks

Abstract: Software development effort estimation is one of the most major activities in software project management. A number of models have been proposed to construct a relationship between software size and effort; however we still have problems for effort estimation. This is because project data, available in the initial stages of project is often incomplete, inconsistent, uncertain and unclear. The need for accurate effort estimation in software industry is still a challenge. Artificial Neural Network models are more suitable in such situations. The present paper is concerned with developing software effort estimation models based on artificial neural networks. The models are designed to improve the performance of the network that suits to the COCOMO Model. Artificial Neural Network models are created using Radial Basis and Generalized Regression. A case study based on the COCOMO81 database compares the proposed neural network models with the Intermediate COCOMO. The results were analyzed using five different criterions MMRE, MARE, VARE, Mean BRE and Prediction. It is observed that the Radial Basis Neural Network provided better results


Molecular Programming Pseudo-code Representation to Molecular Electronics

Abstract: This research paper is proposing the idea of pseudo code representation to molecular programming used in designing molecular electronics devices. Already the schematic representation of logical gates like AND, OR, NOT etc.from molecular diodes or resonant tunneling diode are available. This paper is setting a generic pseudo code model so that various logic gates can be formulated. These molecular diodes have designed from organic molecules or Bio-molecules. Our focus is on to give a scenario of molecular computation through molecular programming. We have restricted our study to molecular rectifying diode and logic device as AND gate from organic molecules only.


A Novel Method for Intrusion Detection System to Enhance Security in Ad hoc Network

Abstract: The notion of an ad hoc network is a new paradigm that allows mobile hosts (nodes) to communicate without relying on a predefined infrastructure to keep the network connected. Most nodes are assumed to be mobile and communication is assumed to be wireless. The mobility of nodes in an ad-hoc network means that both the population and the topology of the network are highly dynamic. It is very difficult to design a once-for-all intrusion detection system. A secure protocol should atleast include mechanisms against known attack types. In addition, it should provide a scheme to easily add new security features in the future. The paper includes the detailed description of Proposed Intrusion Detection System based on Local Reputation Scheme. The proposed System also includes concept of Redemption and Fading these are mechanism that allow nodes previously considered malicious to become a part of the network again. The simulation of the proposed system is to be done using NS-2 simulator.


A Soft Computing Model for Physicians' Decision Process

Abstract: In this paper the author presents a kind of Soft Computing Technique, mainly an application of fuzzy set theory of Prof. Zadeh [16], on a problem of Medical Experts Systems. The choosen problem is on design of a physician's decision model which can take crisp as well as fuzzy data as input, unlike the traditional models. The author presents a mathematical model based on fuzzy set theory for physician aided evaluation of a complete representation of information emanating from the initial interview including patient past history, present symptoms, and signs observed upon physical examination and results of clinical and diagnostic tests.


Abstract: Without a doubt, the electronic learning makes education quite flexible. Nowadays, all organizations and institutions are trying to avoid Monotony and the delay and inertia. As well the universities should be improving their systems continually to achieve success. Whereas, the students need to access the dissertations in the library. In this paper we will present Dissertations Repository System Using Context Module to allow the students to benefit the dissertations which is in the library flexibly.


Internet Banking System Prototype

Abstract: Internet Banking System refers to systems that enable bank customers to access accounts and general information on bank products and services through a personal computer or other intelligent device. Internet banking products and services can include detailed account information for corporate customers as well as account summery and transfer money. Ultimately, the products and services obtained through Internet Banking may mirror products and services offered through other bank delivery channels. In this paper, Internet Banking System Prototype has been proposed in order to illustrate the services which is provided by the Bank online services.


On the Module of Internet Banking System

Abstract: Because of the speed, flexibility, and efficiency that it offers, the Internet has become the means for conducting growing numbers of transactions between suppliers and large international corporations. In this way, the Internet has opened new markets to the world and has accelerated the diffusion of knowledge. The meaning of Internet markets or online business has been widely used in these days. The success of the business depends on its flexibility, availability and security. Since that the web-based systems should have a special way to design the system and implement it. Nowadays, the Internet Banking System widely used and the banks looking to provide the best quality system with highly available, fast response, secure and safe to use. The Unified Modelling Language (UML) is the uniquely language which is used to analyse and design any system. In this paper, the UML diagrams has been proposed to illustrate the design phase for any banking system. The authors, presented two types of architecture which is used for the Internet Banking System.


Scope of cloud computing for SMEs in India

Abstract: Cloud computing is a set of services that provide infrastructure resources using internet media and data storage on a third party server. SMEs are said to be the lifeblood of any vibrant economy. They are known to be the silent drivers of a nation's economy. SMEs of India are one of the most aggressive adopters of ERP Packages. Most of the Indian SMEs have adopted the traditional ERP Systems and have incurred a heavy cost while implementing these systems. This paper presents the cost savings and reduction in the level of difficulty in adopting a cloud computing Service (CCS) enabled ERP system. For the study, IT people from 30 North Indian SMEs were interviewed. In the cloud computing environment the SMEs will not have to own the infrastructure so they can abstain from any capital expenditure and instead they can utilize the resources as a service and pay as per their usage. We consider the results of the paper to be supportive to our proposed research concept.


Energy Efficient Multi-Level Clustering To Prolong The Lifetime of Wireless Sensor Networks

Abstract: Clustering in wireless sensor networks (WSNs) is an important technique to ease topology management and routing. Clustering provides an effective method for prolonging lifetime of a WSN. This paper proposes energy efficient multi-level clustering schemes for wireless sensor networks. Wireless sensor nodes are extremely energy constrained with a limited transmission range. Due to large area of deployment, the network needs to have a multi-level clustering protocol that will enable far-off nodes to communicate with the base station. Simulation is used to analyze the proposed protocols and compare their performance with existing protocol EEMC. Simulation results demonstrate that our proposed protocols are effective in prolonging the network lifetime.


Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition

Abstract: In this paper we present an OCR for Handwritten Devnagari Characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow feature, chain code histogram and straight line fitting features. Shadow features are computed globally for character image while intersection features, chain code histogram features and line fitting features are computed by dividing the character image into different segments. Weighted majority voting technique is used for combining the classification decision obtained from four Multi Layer Perceptron(MLP) based classifier. On experimentation with a dataset of 4900 samples the overall recognition rate observed is 92.80% as we considered top five choices results. This method is compared with other recent methods for Handwritten Devnagari Character Recognition and it has been observed that this approach has better success rate than other methods.


Polylogarithmic Approximation for Edit Distance and the Asymmetric Query Complexity

Abstract: We present a near-linear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed epsilon>0, it can compute a (log n)^O(1/epsilon) approximation in n^(1+epsilon) time. This is an exponential improvement over the previously known factor, 2^(O (sqrt(log n))), with a comparable running time (Ostrovsky and Rabani J.ACM 2007; Andoni and Onak STOC 2009). Previously, no efficient polylogarithmic approximation algorithm was known for any computational task involving edit distance (e.g., nearest neighbor search or sketching). This result arises naturally in the study of a new asymmetric query model. In this model, the input consists of two strings x and y, and an algorithm can access y in an unrestricted manner, while being charged for querying every symbol of x. Indeed, we obtain our main result by designing an algorithm that makes a small number of queries in this model. We then provide a nearly-matching lower bound on the number of queries. Our lower bound is the first to expose hardness of edit distance stemming from the input strings being "repetitive", which means that many of their substrings are approximately identical. Consequently, our lower bound provides the first rigorous separation between edit distance and Ulam distance, which is edit distance on non-repetitive strings, such as permutations.


Face Synthesis (FASY) System for Generation of a Face Image from Human Description

Abstract: This paper aims at generating a new face based on the human like description using a new concept. The FASY (FAce SYnthesis) System is a Face Database Retrieval and new Face generation System that is under development. One of its main features is the generation of the requested face when it is not found in the existing database, which allows a continuous growing of the database also.