An Explicit Nonlinear Mapping for Manifold Learning

Abstract: Manifold learning is a hot research topic in the field of computer science and has many applications in the real world. A main drawback of manifold learning methods is, however, that there is no explicit mappings from the input data manifold to the output embedding. This prohibits the application of manifold learning methods in many practical problems such as classification and target detection. Previously, in order to provide explicit mappings for manifold learning methods, many methods have been proposed to get an approximate explicit representation mapping with the assumption that there exists a linear projection between the high-dimensional data samples and their low-dimensional embedding. However, this linearity assumption may be too restrictive. In this paper, an explicit nonlinear mapping is proposed for manifold learning, based on the assumption that there exists a polynomial mapping between the high-dimensional data samples and their low-dimensional representations. As far as we know, this is the first time that an explicit nonlinear mapping for manifold learning is given. In particular, we apply this to the method of Locally Linear Embedding (LLE) and derive an explicit nonlinear manifold learning algorithm, named Neighborhood Preserving Polynomial Embedding (NPPE). Experimental results on both synthetic and real-world data show that the proposed mapping is much more effective in preserving the local neighborhood information and the nonlinear geometry of the high-dimensional data samples than previous work.


Approximating Matrix p-norms

Abstract: We consider the problem of computing the q->p norm of a matrix A, which is defined for p,q \ge 1, as |A|_{q->p} = max_{x !=0 } |Ax|_p / |x|_q. This is in general a non-convex optimization problem, and is a natural generalization of the well-studied question of computing singular values (this corresponds to p=q=2). Different settings of parameters give rise to a variety of known interesting problems (such as the Grothendieck problem when p=1 and q=\infty). However, very little is understood about the approximability of the problem for different values of p,q. Our first result is an efficient algorithm for computing the q->p norm of matrices with non-negative entries, when q \ge p \ge 1. The algorithm we analyze is based on a natural fixed point iteration, which can be seen as an analog of power iteration for computing eigenvalues. We then present an application of our techniques to the problem of constructing a scheme for oblivious routing in the l_p norm. This makes constructive a recent existential result of Englert and R\"acke [ER] on O(log n)-competitive oblivious routing schemes (which they make constructive only for p=2). On the other hand, when we do not have any restrictions on the entries (such as non-negativity), we prove that the problem is NP-hard to approximate to any constant factor, for 2 < p \le q, and p \le q < 2 (these are precisely the ranges of p,q with p\le q, where constant factor approximations are not known). In this range, our techniques also show that if NP does not have quasi-polynomial time algorithms, the q->p cannot be approximated to a factor 2^{(log n)^{1-eps}}, for any \eps>0.


Finding top-k similar pairs of objects annotated with terms from an ontology

Abstract: With the growing focus on semantic searches and interpretations, an increasing number of standardized vocabularies and ontologies are being designed and used to describe data. We investigate the querying of objects described by a tree-structured ontology. Specifically, we consider the case of finding the top-k best pairs of objects that have been annotated with terms from such an ontology when the object descriptions are available only at runtime. We consider three distance measures. The first one defines the object distance as the minimum pairwise distance between the sets of terms describing them, and the second one defines the distance as the average pairwise term distance. The third and most useful distance measure, earth mover's distance, finds the best way of matching the terms and computes the distance corresponding to this best matching. We develop lower bounds that can be aggregated progressively and utilize them to speed up the search for top-k object pairs when the earth mover's distance is used. For the minimum pairwise distance, we devise an algorithm that runs in O(D + Tk log k) time, where D is the total information size and T is the total number of terms in the ontology. We also develop a novel best-first search strategy for the average pairwise distance that utilizes lower bounds generated in an ordered manner. Experiments on real and synthetic datasets demonstrate the practicality and scalability of our algorithms.


Detecting Botnets Through Log Correlation

Abstract: Botnets, which consist of thousands of compromised machines, can cause significant threats to other systems by launching Distributed Denial of Service (SSoS) attacks, keylogging, and backdoors. In response to these threats, new effective techniques are needed to detect the presence of botnets. In this paper, we have used an interception technique to monitor Windows Application Programming Interface (API) functions calls made by communication applications and store these calls with their arguments in log files. Our algorithm detects botnets based on monitoring abnormal activity by correlating the changes in log file sizes from different hosts.


Kernel machines with two layers and multiple kernel learning

Abstract: In this paper, the framework of kernel machines with two layers is introduced, generalizing classical kernel methods. The new learning methodology provide a formal connection between computational architectures with multiple layers and the theme of kernel learning in standard regularization methods. First, a representer theorem for two-layer networks is presented, showing that finite linear combinations of kernels on each layer are optimal architectures whenever the corresponding functions solve suitable variational problems in reproducing kernel Hilbert spaces (RKHS). The input-output map expressed by these architectures turns out to be equivalent to a suitable single-layer kernel machines in which the kernel function is also learned from the data. Recently, the so-called multiple kernel learning methods have attracted considerable attention in the machine learning literature. In this paper, multiple kernel learning methods are shown to be specific cases of kernel machines with two layers in which the second layer is linear. Finally, a simple and effective multiple kernel learning method called RLS2 (regularized least squares with two layers) is introduced, and his performances on several learning problems are extensively analyzed. An open source MATLAB toolbox to train and validate RLS2 models with a Graphic User Interface is available.


Planar Visibility: Testing and Counting

Abstract: In this paper we consider query versions of visibility testing and visibility counting. Let $S$ be a set of $n$ disjoint line segments in $\R^2$ and let $s$ be an element of $S$. Visibility testing is to preprocess $S$ so that we can quickly determine if $s$ is visible from a query point $q$. Visibility counting involves preprocessing $S$ so that one can quickly estimate the number of segments in $S$ visible from a query point $q$. We present several data structures for the two query problems. The structures build upon a result by O'Rourke and Suri (1984) who showed that the subset, $V_S(s)$, of $\R^2$ that is weakly visible from a segment $s$ can be represented as the union of a set, $C_S(s)$, of $O(n^2)$ triangles, even though the complexity of $V_S(s)$ can be $\Omega(n^4)$. We define a variant of their covering, give efficient output-sensitive algorithms for computing it, and prove additional properties needed to obtain approximation bounds. Some of our bounds rely on a new combinatorial result that relates the number of segments of $S$ visible from a point $p$ to the number of triangles in $\bigcup_{s\in S} C_S(s)$ that contain $p$.


Stochastic Budget Optimization in Internet Advertising

Abstract: Internet advertising is a sophisticated game in which the many advertisers "play" to optimize their return on investment. There are many "targets" for the advertisements, and each "target" has a collection of games with a potentially different set of players involved. In this paper, we study the problem of how advertisers allocate their budget across these "targets". In particular, we focus on formulating their best response strategy as an optimization problem. Advertisers have a set of keywords ("targets") and some stochastic information about the future, namely a probability distribution over scenarios of cost vs click combinations. This summarizes the potential states of the world assuming that the strategies of other players are fixed. Then, the best response can be abstracted as stochastic budget optimization problems to figure out how to spread a given budget across these keywords to maximize the expected number of clicks. We present the first known non-trivial poly-logarithmic approximation for these problems as well as the first known hardness results of getting better than logarithmic approximation ratios in the various parameters involved. We also identify several special cases of these problems of practical interest, such as with fixed number of scenarios or with polynomial-sized parameters related to cost, which are solvable either in polynomial time or with improved approximation ratios. Stochastic budget optimization with scenarios has sophisticated technical structure. Our approximation and hardness results come from relating these problems to a special type of (0/1, bipartite) quadratic programs inherent in them. Our research answers some open problems raised by the authors in (Stochastic Models for Budget Optimization in Search-Based Advertising, Algorithmica, 58 (4), 1022-1044, 2010).


A Polynomial Diophantine Generator Function for Integer Residuals

Abstract: Two Diophantine equation generator function for integer residuals produced by integer division over closed intervals are presented. One each for the closed intervals [1,Floor(n^0.5)] and [Ceiling(n^0.5),n], respectively.


Point Location in Disconnected Planar Subdivisions

Abstract: Let $G$ be a (possibly disconnected) planar subdivision and let $D$ be a probability measure over $\R^2$. The current paper shows how to preprocess $(G,D)$ into an O(n) size data structure that can answer planar point location queries over $G$. The expected query time of this data structure, for a query point drawn according to $D$, is $O(H+1)$, where $H$ is a lower bound on the expected query time of any linear decision tree for point location in $G$. This extends the results of Collette et al (2008, 2009) from connected planar subdivisions to disconnected planar subdivisions. A version of this structure, when combined with existing results on succinct point location, provides a succinct distribution-sensitive point location structure.


Universally Optimal Privacy Mechanisms for Minimax Agents

Abstract: A scheme that publishes aggregate information about sensitive data must resolve the trade-off between utility to information consumers and privacy of the database participants. Differential privacy is a well-established definition of privacy--this is a universal guarantee against all attackers, whatever their side-information or intent. In this paper, we present a universal treatment of utility based on the standard minimax rule from decision theory (in contrast to the utility model in, which is Bayesian). In our model, information consumers are minimax (risk-averse) agents, each possessing some side-information about the query, and each endowed with a loss-function which models their tolerance to inaccuracies. Further, information consumers are rational in the sense that they actively combine information from the mechanism with their side-information in a way that minimizes their loss. Under this assumption of rational behavior, we show that for every fixed count query, a certain geometric mechanism is universally optimal for all minimax information consumers. Additionally, our solution makes it possible to release query results at multiple levels of privacy in a collusion-resistant manner.


Modeling Web Evolution

Abstract: The Web is the largest human information construct in history transforming our society. How can we understand, measure and model the Web evolution in order to design effective policies and optimize its social benefit? Early measurements of the Internet traffic and the Web graph indicated the scale-free structure of the Web and other Complex Networks. Going a step further Kouroupas, Koutsoupias, Papadimitriou and Sideri (KKPS) presented an economic-inspired model which explains the scale-free behavior as the interaction of Documents, Users and Search engines. The purpose of this paper is to clarify the open issues arising within the KKPS model through analysis and simulations and to highlight future research developments in Web modeling, which is the backbone of Web Science.


Termination Detection of Local Computations

Abstract: Contrary to the sequential world, the processes involved in a distributed system do not necessarily know when a computation is globally finished. This paper investigates the problem of the detection of the termination of local computations. We define four types of termination detection: no detection, detection of the local termination, detection by a distributed observer, detection of the global termination. We give a complete characterisation (except in the local termination detection case where a partial one is given) for each of this termination detection and show that they define a strict hierarchy. These results emphasise the difference between computability of a distributed task and termination detection. Furthermore, these characterisations encompass all standard criteria that are usually formulated : topological restriction (tree, rings, or triangu- lated networks ...), topological knowledge (size, diameter ...), and local knowledge to distinguish nodes (identities, sense of direction). These results are now presented as corollaries of generalising theorems. As a very special and important case, the techniques are also applied to the election problem. Though given in the model of local computations, these results can give qualitative insight for similar results in other standard models. The necessary conditions involve graphs covering and quasi-covering; the sufficient conditions (constructive local computations) are based upon an enumeration algorithm of Mazurkiewicz and a stable properties detection algorithm of Szymanski, Shi and Prywes.


Synthesis of AMBA AHB from Formal Specification

Abstract: The standard procedure for hardware design consists of describing circuit in a hardware description language at logic level followed by extensive verification and logic-synthesis. However, this process consumes significant time and needs a lot of effort. An alternative is to use formal specification language as a high-level hardware description language and synthesize hardware from formal specification. Bloem et.al. gave formal specifications and synthesize the AMBA AHB Arbiter. Our contributions are as follows:(1) We present more complete and compact formal specifications for the AMBA AHB Arbiter, and obtain significant (order of magnitude) improvement in synthesis results (both with respect to time and the number of gates of the synthesize circuit); (2) we present formal specification and synthesize to generate compact circuits for the remaining two components of the AMBA AHB protocol, namely, the AMBA AHB Master and AMBA AHB Slave; and (3) from the lessons learnt we present few principles for writing formal specifications for efficient hardware synthesis. Thus with intelligently written complete formal specifications we are able to automatically synthesize an important and widely used industrial protocol.


Grammatical Aspects for Language Descriptions

Abstract: For the purposes of tool development, computer languages are usually described using context-free grammars with annotations such as semantic actions or pretty-printing instructions. These descriptions are processed by generators which automatically build software, e.g., parsers, pretty-printers and editing support. In many cases the annotations make grammars unreadable, and when generating code for several tools supporting the same language, one usually needs to duplicate the grammar in order to provide different annotations for different generators. We present an approach to describing languages which improves readability of grammars and reduces the duplication. To achieve this we use Aspect-Oriented Programming principles. This approach has been implemented in an open-source tool named Grammatic. We show how it can be used to generate pretty-printers and syntax highlighters.


Evaluation Study for Delay and Link Utilization with the New-Additive Increase Multiplicative Decrease Congestion Avoidance and Control Algorithm

Abstract: As the Internet becomes increasingly heterogeneous, the issue of congestion avoidance and control becomes ever more important. And the queue length, end-to-end delays and link utilization is some of the important things in term of congestion avoidance and control mechanisms. In this work we continue to study the performances of the New-AIMD (Additive Increase Multiplicative Decrease) mechanism as one of the core protocols for TCP congestion avoidance and control algorithm, we want to evaluate the effect of using the AIMD algorithm after developing it to find a new approach, as we called it the New-AIMD algorithm to measure the Queue length, delay and bottleneck link utilization, and use the NCTUns simulator to get the results after make the modification for the mechanism. And we will use the Droptail mechanism as the active queue management mechanism (AQM) in the bottleneck router. After implementation of our new approach with different number of flows, we expect the delay will less when we measure the delay dependent on the throughput for all the system, and also we expect to get end-to-end delay less. And we will measure the second type of delay a (queuing delay), as we shown in the figure 1 bellow. Also we will measure the bottleneck link utilization, and we expect to get high utilization for bottleneck link with using this mechanism, and avoid the collisions in the link.


Succinct Dictionary Matching With No Slowdown

Abstract: The problem of dictionary matching is a classical problem in string matching: given a set S of d strings of total length n characters over an (not necessarily constant) alphabet of size sigma, build a data structure so that we can match in a any text T all occurrences of strings belonging to S. The classical solution for this problem is the Aho-Corasick automaton which finds all occ occurrences in a text T in time O(|T| + occ) using a data structure that occupies O(m log m) bits of space where m <= n + 1 is the number of states in the automaton. In this paper we show that the Aho-Corasick automaton can be represented in just m(log sigma + O(1)) + O(d log(n/d)) bits of space while still maintaining the ability to answer to queries in O(|T| + occ) time. To the best of our knowledge, the currently fastest succinct data structure for the dictionary matching problem uses space O(n log sigma) while answering queries in O(|T|log log n + occ) time. In this paper we also show how the space occupancy can be reduced to m(H0 + O(1)) + O(d log(n/d)) where H0 is the empirical entropy of the characters appearing in the trie representation of the set S, provided that sigma < m^epsilon for any constant 0 < epsilon < 1. The query time remains unchanged.


On Touching Triangle Graphs

Abstract: In this paper, we consider the problem of representing graphs by triangles whose sides touch. As a simple necessary condition, we show that pairs of vertices must have a small common neighborhood. On the positive side, we present linear time algorithms for creating touching triangle representations for outerplanar graphs, square grid graphs, and hexagonal grid graphs. We note that this class of graphs is not closed under minors, making characterization difficult. However, we present a complete characterization of the subclass of biconnected graphs that can be represented as triangulations of some polygon.


Approximate Self-Assembly of the Sierpinski Triangle

Abstract: The Tile Assembly Model is a Turing universal model that Winfree introduced in order to study the nanoscale self-assembly of complex (typically aperiodic) DNA crystals. Winfree exhibited a self-assembly that tiles the first quadrant of the Cartesian plane with specially labeled tiles appearing at exactly the positions of points in the Sierpinski triangle. More recently, Lathrop, Lutz, and Summers proved that the Sierpinski triangle cannot self-assemble in the "strict" sense in which tiles are not allowed to appear at positions outside the target structure. Here we investigate the strict self-assembly of sets that approximate the Sierpinski triangle. We show that every set that does strictly self-assemble disagrees with the Sierpinski triangle on a set with fractal dimension at least that of the Sierpinski triangle (roughly 1.585), and that no subset of the Sierpinski triangle with fractal dimension greater than 1 strictly self-assembles. We show that our bounds are tight, even when restricted to supersets of the Sierpinski triangle, by presenting a strict self-assembly that adds communication fibers to the fractal structure without disturbing it. To verify this strict self-assembly we develop a generalization of the local determinism method of Soloveichik and Winfree.


Detecting High Log-Densities -- an O(n^1/4) Approximation for Densest k-Subgraph

Abstract: In the Densest k-Subgraph problem, given a graph G and a parameter k, one needs to find a subgraph of G induced on k vertices that contains the largest number of edges. There is a significant gap between the best known upper and lower bounds for this problem. It is NP-hard, and does not have a PTAS unless NP has subexponential time algorithms. On the other hand, the current best known algorithm of Feige, Kortsarz and Peleg, gives an approximation ratio of n^(1/3-epsilon) for some specific epsilon > 0 (estimated at around 1/60). We present an algorithm that for every epsilon > 0 approximates the Densest k-Subgraph problem within a ratio of n^(1/4+epsilon) in time n^O(1/epsilon). In particular, our algorithm achieves an approximation ratio of O(n^1/4) in time n^O(log n). Our algorithm is inspired by studying an average-case version of the problem where the goal is to distinguish random graphs from graphs with planted dense subgraphs. The approximation ratio we achieve for the general case matches the distinguishing ratio we obtain for this planted problem. At a high level, our algorithms involve cleverly counting appropriately defined trees of constant size in G, and using these counts to identify the vertices of the dense subgraph. Our algorithm is based on the following principle. We say that a graph G(V,E) has log-density alpha if its average degree is Theta(|V|^alpha). The algorithmic core of our result is a family of algorithms that output k-subgraphs of nontrivial density whenever the log-density of the densest k-subgraph is larger than the log-density of the host graph.


Pi/2-Angle Yao Graphs are Spanners

Abstract: We show that the Yao graph Y4 in the L2 metric is a spanner with stretch factor 8(29+23sqrt(2)). Enroute to this, we also show that the Yao graph Y4 in the Linf metric is a planar spanner with stretch factor 8.


Towards Transactional Load over XtreemFS

Abstract: We propose using trace-based assessment of the performance of distributed file systems (DFS) under transactional IO load. The assessment includes simulations and experiments using the IO traces. Our experiments suggest that DFS, and specifically XtreemFS have a good potential to support transactional IO load in distributed environments: they demonstrate good performance, high availability and scalability, while at the same time opening the way to TCO reduction.


On equations over sets of integers

Abstract: Systems of equations with sets of integers as unknowns are considered. It is shown that the class of sets representable by unique solutions of equations using the operations of union and addition $S+T=\makeset{m+n}{m \in S, \: n \in T}$ and with ultimately periodic constants is exactly the class of hyper-arithmetical sets. Equations using addition only can represent every hyper-arithmetical set under a simple encoding. All hyper-arithmetical sets can also be represented by equations over sets of natural numbers equipped with union, addition and subtraction $S \dotminus T=\makeset{m-n}{m \in S, \: n \in T, \: m \geqslant n}$. Testing whether a given system has a solution is $\Sigma^1_1$-complete for each model. These results, in particular, settle the expressive power of the most general types of language equations, as well as equations over subsets of free groups.


Parallel computation of real solving bivariate polynomial systems by zero-matching method

Abstract: We present a new algorithm for solving the real roots of a bivariate polynomial system $\Sigma=\{f(x,y),g(x,y)\}$ with a finite number of solutions by using a zero-matching method. The method is based on a lower bound for bivariate polynomial system when the system is non-zero. Moreover, the multiplicities of the roots of $\Sigma=0$ can be obtained by a given neighborhood. From this approach, the parallelization of the method arises naturally. By using a multidimensional matching method this principle can be generalized to the multivariate equation systems.


Weakness Analysis and Improvement of a Gateway-Oriented Password-Based Authenticated Key Exchange Protocol

Abstract: Recently, Abdalla et al. proposed a new gateway-oriented password-based authenticated key exchange (GPAKE) protocol among a client, a gateway, and an authentication server, where each client shares a human-memorable password with a trusted server so that they can resort to the server for authentication when want to establish a shared session key with the gateway. In the letter, we show that a malicious client of GPAKE is still able to gain information of password by performing an undetectable on-line password guessing attack and can not provide the implicit key confirmation. At last, we present a countermeasure to against the attack.


Asymptotic Learning Curve and Renormalizable Condition in Statistical Learning Theory

Abstract: Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovered that the asymptotic learning curves in Bayes estimation are subject to a universal law, even if the log likelihood function can not be approximated by any quadratic form. However, it is left unknown what mathematical property ensures such a universal law. In this paper, we define a renormalizable condition of the statistical estimation problem, and show that, under such a condition, the asymptotic learning curves are ensured to be subject to the universal law, even if the true distribution is unrealizable and singular for a statistical model. Also we study a nonrenormalizable case, in which the learning curves have the different asymptotic behaviors from the universal law.


Improved code-based identification scheme

Abstract: We revisit the 3-pass code-based identification scheme proposed by Stern at Crypto'93, and give a new 5-pass protocol for which the probability of the cheater is 1/2 (instead of 2/3 in the original Stern's proposal). Furthermore, we propose to use quasi-cyclic construction in order to dramatically reduce the size of the public key. The proposed scheme is zero-knowledge and relies on an NP-complete problem coming from coding theory (namely the q-ary Syndrome Decoding problem). Taking into account a recent study of a generalization of Stern's information-set-decoding algorithm for decoding linear codes over arbitrary finite fields Fq we suggest parameters so that the public key be 34Kbits while those of Stern's scheme is about 66Kbits. This provides a very practical identification (and possibly signature) scheme which is mostly attractive for light-weight cryptography


Mortality and Longevity Valuation - A Quantitative Approach

Abstract: This paper examines several computer algorithms designed to assess mortality and longevity risk.


Dynamic sharing of a multiple access channel

Abstract: In this paper we consider the mutual exclusion problem on a multiple access channel. Mutual exclusion is one of the fundamental problems in distributed computing. In the classic version of this problem, n processes perform a concurrent program which occasionally triggers some of them to use shared resources, such as memory, communication channel, device, etc. The goal is to design a distributed algorithm to control entries and exits to/from the shared resource in such a way that in any time there is at most one process accessing it. We consider both the classic and a slightly weaker version of mutual exclusion, called ep-mutual-exclusion, where for each period of a process staying in the critical section the probability that there is some other process in the critical section is at most ep. We show that there are channel settings, where the classic mutual exclusion is not feasible even for randomized algorithms, while ep-mutual-exclusion is. In more relaxed channel settings, we prove an exponential gap between the makespan complexity of the classic mutual exclusion problem and its weaker ep-exclusion version. We also show how to guarantee fairness of mutual exclusion algorithms, i.e., that each process that wants to enter the critical section will eventually succeed.


Strong Robustness of Randomized Rumor Spreading Protocols

Abstract: Randomized rumor spreading is a classical protocol to disseminate information across a network. At SODA 2008, a quasirandom version of this protocol was proposed and competitive bounds for its run-time were proven. This prompts the question: to what extent does the quasirandom protocol inherit the second principal advantage of randomized rumor spreading, namely robustness against transmission failures? In this paper, we present a result precise up to $(1 \pm o(1))$ factors. We limit ourselves to the network in which every two vertices are connected by a direct link. Run-times accurate to their leading constants are unknown for all other non-trivial networks. We show that if each transmission reaches its destination with a probability of $p \in (0,1]$, after $(1+\e)(\frac{1}{\log_2(1+p)}\log_2n+\frac{1}{p}\ln n)$ rounds the quasirandom protocol has informed all $n$ nodes in the network with probability at least $1-n^{-p\e/40}$. Note that this is faster than the intuitively natural $1/p$ factor increase over the run-time of approximately $\log_2 n + \ln n $ for the non-corrupted case. We also provide a corresponding lower bound for the classical model. This demonstrates that the quasirandom model is at least as robust as the fully random model despite the greatly reduced degree of independent randomness.


An Immuno-Inspired Approach to Misbehavior Detection in Ad Hoc Wireless Networks

Abstract: We propose and evaluate an immuno-inspired approach to misbehavior detection in ad hoc wireless networks. Node misbehavior can be the result of an intrusion, or a software or hardware failure. Our approach is motivated by co-stimulatory signals present in the Biological immune system. The results show that co-stimulation in ad hoc wireless networks can both substantially improve energy efficiency of detection and, at the same time, help achieve low false positives rates. The energy efficiency improvement is almost two orders of magnitude, if compared to misbehavior detection based on watchdogs. We provide a characterization of the trade-offs between detection approaches executed by a single node and by several nodes in cooperation. Additionally, we investigate several feature sets for misbehavior detection. These feature sets impose different requirements on the detection system, most notably from the energy efficiency point of view.


Gaze and Gestures in Telepresence: multimodality, embodiment, and roles of collaboration

Abstract: This paper proposes a controlled experiment to further investigate the usefulness of gaze awareness and gesture recognition in the support of collaborative work at a distance. We propose to redesign experiments conducted several years ago with more recent technology that would: a) enable to better study of the integration of communication modalities, b) allow users to freely move while collaborating at a distance and c) avoid asymmetries of communication between collaborators.


Optimal Reverse Carpooling Over Wireless Networks - A Distributed Optimization Approach

Abstract: We focus on a particular form of network coding, reverse carpooling, in a wireless network where the potentially coded transmitted messages are to be decoded immediately upon reception. The network is fixed and known, and the system performance is measured in terms of the number of wireless broadcasts required to meet multiple unicast demands. Motivated by the structure of the coding scheme, we formulate the problem as a linear program by introducing a flow variable for each triple of connected nodes. This allows us to have a formulation polynomial in the number of nodes. Using dual decomposition and projected subgradient method, we present a decentralized algorithm to obtain optimal routing schemes in presence of coding opportunities. We show that the primal sub-problem can be expressed as a shortest path problem on an \emph{edge-graph}, and the proposed algorithm requires each node to exchange information only with its neighbors.


S\'ecurit\'e des syst\`emes critiques et cybercriminalit\'e : vers une s\'ecurit\'e globale ?

Abstract: For modern critical systems, it is necessary to consider their ability to avoid catastrophic behavior following fortuitous events such as internal failures in hardware components, environmental disturbances or even involuntary human error in the design and operation, but also non fortuitous events such as malicious attacks. Unfortunately, in French the same word "s\'ecurit\'e" is used to cover two different problematics, what in English is expressed in two different words : safety and security. The interconnected modern information systems, such as rail traffic signalling systems point out the need to deal in an overall way with both safety and security


A finiteness structure on resource terms

Abstract: In our paper "Uniformity and the Taylor expansion of ordinary lambda-terms" (with Laurent Regnier), we studied a translation of lambda-terms as infinite linear combinations of resource lambda-terms, from a calculus similar to Boudol's lambda-calculus with resources and based on ideas coming from differential linear logic and differential lambda-calculus. The good properties of this translation wrt. beta-reduction were guaranteed by a coherence relation on resource terms: normalization is "linear and stable" (in the sense of the coherence space semantics of linear logic) wrt. this coherence relation. Such coherence properties are lost when one considers non-deterministic or algebraic extensions of the lambda-calculus (the algebraic lambda-calculus is an extension of the lambda-calculus where terms can be linearly combined). We introduce a "finiteness structure" on resource terms which induces a linearly topologized vector space structure on terms and prevents the appearance of infinite coefficients during reduction, in typed settings.


Extending INET Framework for Directional and Asymmetrical Wireless Communications

Abstract: This paper reports our work on extending the Omnet INET Framework with a directional radio model, putting a special emphasis on the implementation of asymmetrical communications. We first analyze the original INET radio model, focusing on its design and components. Then we discuss the modifications that have been done to support directional communications. Our preliminary results show that the new model is flexible enough to allow the user to provide any antenna pattern shape, with only an additional reasonable computational cost.


Optimal Gossip-Based Aggregate Computation

Abstract: We present the first provably almost-optimal gossip-based algorithms for aggregate computation that are both time optimal and message-optimal. Given a $n$-node network, our algorithms guarantee that all the nodes can compute the common aggregates (such as Min, Max, Count, Sum, Average, Rank etc.) of their values in optimal $O(\log n)$ time and using $O(n \log \log n)$ messages. Our result improves on the algorithm of Kempe et al. \cite{kempe} that is time-optimal, but uses $O(n \log n)$ messages as well as on the algorithm of Kashyap et al. \cite{efficient-gossip} that uses $O(n \log \log n)$ messages, but is not time-optimal (takes $O(\log n \log \log n)$ time). Furthermore, we show that our algorithms can be used to improve gossip-based aggregate computation in sparse communication networks, such as in peer-to-peer networks. The main technical ingredient of our algorithm is a technique called {\em distributed random ranking (DRR)} that can be useful in other applications as well. DRR gives an efficient distributed procedure to partition the network into a forest of (disjoint) trees of small size. Our algorithms are non-address oblivious. In contrast, we show a lower bound of $\Omega(n\log n)$ on the message complexity of any address-oblivious algorithm for computing aggregates. This shows that non-address oblivious algorithms are needed to obtain significantly better message complexity. Our lower bound holds regardless of the number of rounds taken or the size of the messages used. Our lower bound is the first non-trivial lower bound for gossip-based aggregate computation and also gives the first formal proof that computing aggregates is strictly harder than rumor spreading in the address-oblivious model.


The Recognition of Tolerance and Bounded Tolerance Graphs

Abstract: Tolerance graphs model interval relations in such a way that intervals can tolerate a certain degree of overlap without being in conflict. This subclass of perfect graphs has been extensively studied, due to both its interesting structure and its numerous applications. Several efficient algorithms for optimization problems that are NP-hard on general graphs have been designed for tolerance graphs. In spite of this, the recognition of tolerance graphs - namely, the problem of deciding whether a given graph is a tolerance graph - as well as the recognition of their main subclass of bounded tolerance graphs, have been the most fundamental open problems on this class of graphs (cf. the book on tolerance graphs \cite{GolTol04}) since their introduction in 1982 \cite{GoMo82}. In this article we prove that both recognition problems are NP-complete, even in the case where the input graph is a trapezoid graph. The presented results are surprising because, on the one hand, most subclasses of perfect graphs admit polynomial recognition algorithms and, on the other hand, bounded tolerance graphs were believed to be efficiently recognizable as they are a natural special case of trapezoid graphs (which can be recognized in polynomial time) and share a very similar structure with them. For our reduction we extend the notion of an \emph{acyclic orientation} of permutation and trapezoid graphs. Our main tool is a new algorithm that uses \emph{vertex splitting} to transform a given trapezoid graph into a permutation graph, while preserving this new acyclic orientation property. This method of vertex splitting is of independent interest; very recently, it has been proved a powerful tool also in the design of efficient recognition algorithms for other classes of graphs \cite{MC-Trapezoid}.


Research Challenges for Enterprise Cloud Computing

Abstract: Cloud computing represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to consumers over the internet from large-scale data centers - or "clouds". This paper discusses some of the research challenges for cloud computing from an enterprise or organizational perspective, and puts them in context by reviewing the existing body of literature in cloud computing. Various research challenges relating to the following topics are discussed: the organizational changes brought about by cloud computing; the economic and organizational implications of its utility billing model; the security, legal and privacy issues that cloud computing raises. It is important to highlight these research challenges because cloud computing is not simply about a technological improvement of data centers but a fundamental change in how IT is provisioned and used. This type of research has the potential to influence wider adoption of cloud computing in enterprise, and in the consumer market too.


Research Agenda in Cloud Technologies

Abstract: Cloud computing is the latest effort in delivering computing resources as a service. It represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to consumers over the internet from large-scale data centres - or "clouds". Whilst cloud computing is gaining growing popularity in the IT industry, academia appeared to be lagging behind the rapid developments in this field. This paper is the first systematic review of peer-reviewed academic research published in this field, and aims to provide an overview of the swiftly developing advances in the technical foundations of cloud computing and their research efforts. Structured along the technical aspects on the cloud agenda, we discuss lessons from related technologies; advances in the introduction of protocols, interfaces, and standards; techniques for modelling and building clouds; and new use-cases arising through cloud computing.


A Real World Mechanism for Testing Satisfiability in Polynomial Time

Abstract: Whether the satisfiability of any formula F of propositional calculus can be determined in polynomial time is an open question. I propose a simple procedure based on some real world mechanisms to tackle this problem. The main result is the blueprint for a machine which is able to test any formula in conjunctive normal form (CNF) for satisfiability in linear time. The device uses light and some electrochemical properties to function. It adapts itself to the scope of the problem without growing exponentially in mass with the size of the formula. It requires infinite precision in its components instead.


On Utilization and Importance of Perl Status Reporter (SRr) in Text Mining

Abstract: In Bioinformatics, text mining and text data mining sometimes interchangeably used is a process to derive high-quality information from text. Perl Status Reporter (SRr) is a data fetching tool from a flat text file and in this research paper we illustrate the use of SRr in text or data mining. SRr needs a flat text input file where the mining process to be performed. SRr reads input file and derives the high quality information from it. Typically text mining tasks are text categorization, text clustering, concept and entity extraction, and document summarization. SRr can be utilized for any of these tasks with little or none customizing efforts. In our implementation we perform text categorization mining operation on input file. The input file has two parameters of interest (firstKey and secondKey). The composition of these two parameters describes the uniqueness of entries in that file in the similar manner as done by composite key in database. SRr reads the input file line by line and extracts the parameters of interest and form a composite key by joining them together. It subsequently generates an output file consisting of the name as firstKey secondKey. SRr reads the input file and tracks the composite key. It further stores all that data lines, having the same composite key, in output file generated by SRr based on that composite key.


Recursive Secret Sharing for Distributed Storage and Information Hiding

Abstract: This paper presents a recursive computational multi-secret sharing technique that hides k-2 secrets of size b each into n shares of a single secret S of size b, such that any k of the n shares suffice to recreate the secret S as well as all the hidden secrets. This may act as a steganographic channel to transmit hidden information or used for authentication and verification of shares and the secret itself. Further, such a recursive technique may be used as a computational secret sharing technique that has potential applications in secure and reliable storage of information on the Web, in sensor networks and information dispersal schemes. The presented technique, unlike previous computational techniques, does not require the use of any encryption key or storage of public information.


Minimum Vertex Cover in Rectangle Graphs

Abstract: We consider the Vertex Cover problem in intersection graphs of axis-parallel rectangles on the plane. We present two algorithms: The first is an EPTAS for non-crossing rectangle families, rectangle families $\calR$ where $R_1 \setminus R_2$ is connected for every pair of rectangles $R_1,R_2 \in \calR$. This algorithm extends to intersection graphs of pseudo-disks. The second algorithm achieves a factor of $(1.5 + \varepsilon)$ in general rectangle families, for any fixed $\varepsilon > 0$, and works also for the weighted variant of the problem. Both algorithms exploit the plane properties of axis-parallel rectangles in a non-trivial way.


Practical Parallel External Memory Algorithms via Simulation of Parallel Algorithms

Abstract: This thesis introduces PEMS2, an improvement to PEMS (Parallel External Memory System). PEMS executes Bulk-Synchronous Parallel (BSP) algorithms in an External Memory (EM) context, enabling computation with very large data sets which exceed the size of main memory. Many parallel algorithms have been designed and implemented for Bulk-Synchronous Parallel models of computation. Such algorithms generally assume that the entire data set is stored in main memory at once. PEMS overcomes this limitation without requiring any modification to the algorithm by using disk space as memory for additional "virtual processors". Previous work has shown this to be a promising approach which scales well as computational resources (i.e. processors and disks) are added. However, the technique incurs significant overhead when compared with purpose-built EM algorithms. PEMS2 introduces refinements to the simulation process intended to reduce this overhead as well as the amount of disk space required to run the simulation. New functionality is also introduced, including asynchronous I/O and support for multi-core processors. Experimental results show that these changes significantly improve the runtime of the simulation. PEMS2 narrows the performance gap between simulated BSP algorithms and their hand-crafted EM counterparts, providing a practical system for using BSP algorithms with data sets which exceed the size of RAM.


Linear Recursion

Abstract: We define two extensions of the typed linear lambda-calculus that yield minimal Turing-complete systems. The extensions are based on unbounded recursion in one case, and bounded recursion with minimisation in the other. We show that both approaches are compatible with linearity and typeability constraints. Both extensions of the typed linear lambda-calculus are minimal, in the sense that taking out any of the components breaks the universality of the system. We discuss implementation techniques that exploit the linearity of the calculi. Finally, we apply the results to languages with fixpoint operators: we give a compilation of the programming language PCF into a linear lambda-calculus with linear unbounded recursion.


Approximate Privacy: PARs for Set Problems

Abstract: In previous work (arXiv:0910.5714), we introduced the Privacy Approximation Ratio (PAR) and used it to study the privacy of protocols for second-price Vickrey auctions and Yao's millionaires problem. Here, we study the PARs of multiple protocols for both the disjointness problem (in which two participants, each with a private subset of {1,...,k}, determine whether their sets are disjoint) and the intersection problem (in which the two participants, each with a private subset of {1,...,k}, determine the intersection of their private sets). We show that the privacy, as measured by the PAR, provided by any protocol for each of these problems is necessarily exponential (in k). We also consider the ratio between the subjective PARs with respect to each player in order to show that one protocol for each of these problems is significantly fairer than the others (in the sense that it has a similarly bad effect on the privacy of both players).


Adaptive resource allocation at the cell border using cooperative technique

Abstract: The technique of cooperative communication has recently gained momentum in the research community; this technique utilizes the notion of relay, as an intermediate node between the source and the destination, to enhance the overall system performance. In this paper we ex-plored the benefits of adaptive cooperation, in which the relay adapts its relaying process in response to channel conditions and data priorities. We are particularly interested in applying this concept to the cell border situation, in which two mobile nodes acting as destinations com-municate with base stations (sources) through a relay. The adaptive cooperation is proposed here since the transmission channel conditions (Packet Error Rate for example) and data priori-ties are not the same for both mobiles. We show that using the adaptive resource allocation technique in combination with the cross layer design techniques, we can achieve Real-Time data constraints with no additional overhead.


Positioning based information technique in cooperative MIMO-OFDM systems

Abstract: Future Communication networks are tending towards a diverse wireless networking world where the positioning information (PI) could be helpful in different techniques like the dynamic resource allocation. On the other hand, the PI could be widely used for cooperative techniques in the relay and/or routing selection process. In this paper, we propose to use the PI in the selection of the relays and then to apply an efficient double layer distributed space time block code (DLSTBC) scheme between the different relays. Using the amplify and forward (AF) technique, we show that the proposed code is very efficient whatever the transmitted power is. Moreover, we show that the relay selection process based on PI yields very powerful results when compared to the random relay selection (RS) process


HYMAD: Hybrid DTN-MANET Routing for Dense and Highly Dynamic Wireless Networks

Abstract: In this paper we propose HYMAD, a Hybrid DTN-MANET routing protocol which uses DTN between disjoint groups of nodes while using MANET routing within these groups. HYMAD is fully decentralized and only makes use of topological information exchanges between the nodes. We evaluate the scheme in simulation by replaying real life traces which exhibit this highly dynamic connectivity. The results show that HYMAD outperforms the multi-copy Spray-and-Wait DTN routing protocol it extends, both in terms of delivery ratio and delay, for any number of message copies. Our conclusion is that such a Hybrid DTN-MANET approach offers a promising venue for the delivery of elastic data in mobile ad-hoc networks as it retains the resilience of a pure DTN protocol while significantly improving performance.


Tuning Message Size in Opportunistic Mobile Networks

Abstract: We describe a new model for studying intermittently connected mobile networks, based on Markovian random temporal graphs, that captures the influence of message size, maximum tolerated delay and link stability on the delivery ratio.


Dimensionnement des messages dans un reseau mobile opportuniste

Abstract: Understanding transport capacity in intermittently connected mobile networks (ICMN) is crucial since different applications have different interactivity and bandwidth requirements. One practical issue is how to transform an application's messages into packets suitable for transport over an ICMN. In this paper, we propose a new Markovian model for random temporal graphs and show, both analytically and by replaying a real life trace obtained in a rollerblading tour, that the size of the messages sent over an ICMN has a decisive impact on their delivery ratio. A given message could therefore be broken down into smaller packets to increase reliability. However, we also show that this gain in reliability only appears under tight constraints on the maximum delay tolerated. Mobile application designers should therefore balance message size against both application requirements and network topology dynamics to improve performance.


Formalizing cCSP Synchronous Semantics in PVS

Abstract: Compensating CSP (cCSP) is a language defined to model long running business transactions within the framework of standard CSP process algebra. In earlier work, we have defined both traces and operational semantics of the language. We have shown the consistency between the two semantic models by defining a relationship between them. Synchronization was missing from the earlier semantic definitions which is an important feature for any process algebra. In this paper, we address this issue by extending the syntax and semantics to support synchronization and define a relationship between the semantic models. Moreover, we improve the scalability of our proof technique by mechanically verifying the semantic relationship using theorem prover PVS. We show how to embed process algebra terms and semantics into PVS and to use these embeddings to prove the semantic relationship.


Software Metrics Evaluation Based on Entropy

Abstract: Software engineering activities in the Industry has come a long way with various improve- ments brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the expectation for high quality products demand the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this paper the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. We have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness.


New Multi-step Worm Attack Model

Abstract: The traditional worms such as Blaster, Code Red, Slammer and Sasser, are still infecting vulnerable machines on the internet. They will remain as significant threats due to their fast spreading nature on the internet. Various traditional worms attack pattern has been analyzed from various logs at different OSI layers such as victim logs, attacker logs and IDS alert log. These worms attack pattern can be abstracted to form worms' attack model which describes the process of worms' infection. For the purpose of this paper, only Blaster variants were used during the experiment. This paper proposes a multi-step worm attack model which can be extended into research areas in alert correlation and computer forensic investigation.


Role of Interestingness Measures in CAR Rule Ordering for Associative Classifier: An Empirical Approach

Abstract: Associative Classifier is a novel technique which is the integration of Association Rule Mining and Classification. The difficult task in building Associative Classifier model is the selection of relevant rules from a large number of class association rules (CARs). A very popular method of ordering rules for selection is based on confidence, support and antecedent size (CSA). Other methods are based on hybrid orderings in which CSA method is combined with other measures. In the present work, we study the effect of using different interestingness measures of Association rules in CAR rule ordering and selection for associative classifier.


A Holistic Approach to Securing Web Applications

Abstract: Protection of Web applications is an activity that requires constant monitoring of security threats as well as looking for solutions in this field. Since protection has moved from the lower layers of OSI models to the application layer and having in mind the fact that 75% of all the attacks are performed at the application layer, special attention should be paid to the application layer. It is possible to improve protection of Web application on the level of the system architecture by introducing new components which will realize protection on higher levels of OSI models. This paper deals with Intrusion Detection Systems, Intrusion Prevention Systems, Web Application Firewall and gives a holistic approach to securing Web applications using aforementioned components.


Resolution scalability improvement for JPEG2000 standard color image

Abstract: Removed by arXiv administration. This article was plagiarised from http://www.dmi.unict.it/~battiato/download/NSIP_2003_VQ.pdf and other locations.


BGP Converges to stable solution in Interdomain routing

Abstract: Withdrawn by arXiv administration. This article was plagiarised directly from http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5061961 , which appeared in the conference INFOCOM 2009.


Information criminality - a phenomenon met within the informatics field

Abstract: The phenomenon described as "information criminality" has taken significant proportions in the last decade, fact that carried out towards an international legislative frame, by implementing judicial forms, which might stop its occurrences. As matter of fact, the information criminality represents an information technology aiming towards fraud and prejudicing the users of informational data, by various means to infringement of the law. In this way, some international organizations have dealt with performing a legislative framework, able to punish the phenomenon of information criminality and implicitly to protect the users of computers. The transnational expansions, extremely fast as concerns the computer networks, and extending the access to these networks, by means of mobile telephony, have brought the increasing of these systems' vulnerability and the creating of opportunities of breaking the law. Considering these aspects, the world legislation is continuously changing, due to a more and more accelerated development of the information technology.


Randomness Testing of Compressed Data

Abstract: Random Number Generators play a critical role in a number of important applications. In practice, statistical testing is employed to gather evidence that a generator indeed produces numbers that appear to be random. In this paper, we reports on the studies that were conducted on the compressed data using 8 compression algorithms or compressors. The test results suggest that the output of compression algorithms or compressors has bad randomness, the compression algorithms or compressors are not suitable as random number generator. We also found that, for the same compression algorithm, there exists positive correlation relationship between compression ratio and randomness, increasing the compression ratio increases randomness of compressed data. As time permits, additional randomness testing efforts will be conducted.


Features Based Text Similarity Detection

Abstract: As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, in handling some large content articles, there are some weaknesses in fingerprint matching technique especially in space and time consumption issue. In this paper, we propose a new approach to detect plagiarism which integrates the use of fingerprint matching technique with four key features to assist in the detection process. These proposed features are capable to choose the main point or key sentence in the articles to be compared. Those selected sentence will be undergo the fingerprint matching process in order to detect the similarity between the sentences. Hence, time and space usage for the comparison process is reduced without affecting the effectiveness of the plagiarism detection.


A Model for Mining Multilevel Fuzzy Association Rule in Database

Abstract: The problem of developing models and algorithms for multilevel association mining pose for new challenges for mathematics and computer science. These problems become more challenging, when some form of uncertainty like fuzziness is present in data or relationships in data. This paper proposes a multilevel fuzzy association rule mining models for extracting knowledge implicit in transactions database with different support at each level. The proposed algorithm adopts a top-down progressively deepening approach to derive large itemsets. This approach incorporates fuzzy boundaries instead of sharp boundary intervals. An example is also given to demonstrate that the proposed mining algorithm can derive the multiple-level association rules under different supports in a simple and effective manner.


Applying MVC and PAC patterns in mobile applications

Abstract: Additional requirements are set for mobile applications in relation to applications for desktop computers. These requirements primarily concern the support to different platforms on which such applications are performed, as well as the requirement for providing more modalities of input/output interaction. These requirements have influence on the user interface and therefore it is needed to consider the usability of MVC (Model-View-Controller) and PAC (Presentation-Abstraction-Control) design patterns for the separation of the user interface tasks from the business logic, specifically in mobile applications. One of the questions is making certain choices of design patterns for certain classes of mobile applications. When using these patterns the possibilities of user interface automatic transformation should be kept in mind. Although the MVC design pattern is widely used in mobile applications, it is not universal, especially in cases where there are requirements for heterogeneous multi-modal input-output interactions.


Particle Swarm Optimization Based Reactive Power Optimization

Abstract: Reactive power plays an important role in supporting the real power transfer by maintaining voltage stability and system reliability. It is a critical element for a transmission operator to ensure the reliability of an electric system while minimizing the cost associated with it. The traditional objectives of reactive power dispatch are focused on the technical side of reactive support such as minimization of transmission losses. Reactive power cost compensation to a generator is based on the incurred cost of its reactive power contribution less the cost of its obligation to support the active power delivery. In this paper an efficient Particle Swarm Optimization (PSO) based reactive power optimization approach is presented. The optimal reactive power dispatch problem is a nonlinear optimization problem with several constraints. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum thereby reducing cost allocation. The purpose of reactive power dispatch is to determine the proper amount and location of reactive support. Reactive Optimal Power Flow (ROPF) formulation is developed as an analysis tool and the validity of proposed method is examined using an IEEE-14 bus system.


Posynomial Geometric Programming Problems with Multiple Parameters

Abstract: Geometric programming problem is a powerful tool for solving some special type non-linear programming problems. It has a wide range of applications in optimization and engineering for solving some complex optimization problems. Many applications of geometric programming are on engineering design problems where parameters are estimated using geometric programming. When the parameters in the problems are imprecise, the calculated objective value should be imprecise as well. In this paper we have developed a method to solve geometric programming problems where the exponent of the variables in the objective function, cost coefficients and right hand side are multiple parameters. The equivalent mathematical programming problems are formulated to find their corresponding value of the objective function based on the duality theorem. By applying a variable separable technique the multi-choice mathematical programming problem is transformed into multiple one level geometric programming problem which produces multiple objective values that helps engineers to handle more realistic engineering design problems.


Proposing a New Method for Query Processing Adaption in DataBase

Abstract: This paper proposes a multi agent system by compiling two technologies, query processing optimization and agents which contains features of personalized queries and adaption with changing of requirements. This system uses a new algorithm based on modeling of users' long-term requirements and also GA to gather users' query data. Experimented Result shows more adaption capability for presented algorithm in comparison with classic algorithms.


Expert System Models in the Companies' Financial and Accounting Domain

Abstract: The present paper is based on studying, analyzing and implementing the expert systems in the financial and accounting domain of the companies, describing the use method of the informational systems that can be used in the multi-national companies, public interest institutions, and medium and small dimension economical entities, in order to optimize the managerial decisions and render efficient the financial-accounting functionality. The purpose of this paper is aimed to identifying the economical exigencies of the entities, based on the already used accounting instruments and the management software that could consent the control of the economical processes and patrimonial assets.


Spatial Domain Watermarking Scheme for Colored Images Based on Log-average Luminance

Abstract: In this paper a new watermarking scheme is presented based on log-average luminance. A colored-image is divided into blocks after converting the RGB colored image to YCbCr color space. A monochrome image of 1024 bytes is used as the watermark. To embed the watermark, 16 blocks of size 8X8 are selected and used to embed the watermark image into the original image. The selected blocks are chosen spirally (beginning form the center of the image) among the blocks that have log-average luminance higher than or equal the log-average luminance of the entire image. Each byte of the monochrome watermark is added by updating a luminance value of a pixel of the image. If the byte of the watermark image represented white color (255) a value <alpha> is added to the image pixel luminance value, if it is black (0) the <alpha> is subtracted from the luminance value. To extract the watermark, the selected blocks are chosen as the above, if the difference between the luminance value of the watermarked image pixel and the original image pixel is greater than 0, the watermark pixel is supposed to be white, otherwise it supposed to be black. Experimental results show that the proposed scheme is efficient against changing the watermarked image to grayscale, image cropping, and JPEG compression.


Mapping of SOA and RUP: DOA as Case Study

Abstract: SOA (Service Oriented Architecture) is a new trend towards increasing the profit margins in an organization due to incorporating business services to business practices. Rational Unified Process (RUP) is a unified method planning form for large business applications that provides a language for describing method content and processes. The well defined mapping of SOA and RUP leads to successful completion of RUP software projects to provide services to their users. DOA (Digital Office Assistant) is a multi user SOA type application that provides appropriate viewer for each user to assist him through services. In this paper authors proposed the mapping strategy of SOA with RUP by considering DOA as case study.


3D Skull Recognition Using 3D Matching Technique

Abstract: Biometrics has become a "hot" area. Governments are funding research programs focused on biometrics. In this paper the problem of person recognition and verification based on a different biometric application has been addressed. The system is based on the 3DSkull recognition using 3D matching technique, in fact this paper present several bio-metric approaches in order of assign the weak point in term of used the biometric from the authorize person and insure the person who access the data is the real person. The feature of the simulate system shows the capability of using 3D matching system as an efficient way to identify the person through his or her skull by match it with database, this technique grantee fast processing with optimizing the false positive and negative as well .


Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm

Abstract: The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: pre-processing, feature extraction, association rule mining and hybrid classifier. The pre-processing step has been done using the median filtering process and edge features have been extracted using canny edge detection technique. The two image mining approaches with a hybrid manner have been proposed in this paper. The frequent patterns from the CT scan images are generated by frequent pattern tree (FP-Tree) algorithm that mines the association rules. The decision tree method has been used to classify the medical images for diagnosis. This system enhances the classification process to be more accurate. The hybrid method improves the efficiency of the proposed method than the traditional image mining methods. The experimental result on prediagnosed database of brain images showed 97% sensitivity and 95% accuracy respectively. The physicians can make use of this accurate decision tree classification phase for classifying the brain images into normal, benign and malignant for effective medical diagnosis.


A Noise Addition Scheme in Decision Tree for Privacy Preserving Data Mining

Abstract: Data mining deals with automatic extraction of previously unknown patterns from large amounts of data. Organizations all over the world handle large amounts of data and are dependent on mining gigantic data sets for expansion of their enterprises. These data sets typically contain sensitive individual information, which consequently get exposed to the other parties. Though we cannot deny the benefits of knowledge discovery that comes through data mining, we should also ensure that data privacy is maintained in the event of data mining. Privacy preserving data mining is a specialized activity in which the data privacy is ensured during data mining. Data privacy is as important as the extracted knowledge and efforts that guarantee data privacy during data mining are encouraged. In this paper we propose a strategy that protects the data privacy during decision tree analysis of data mining process. We propose to add specific noise to the numeric attributes after exploring the decision tree of the original data. The obfuscated data then is presented to the second party for decision tree analysis. The decision tree obtained on the original data and the obfuscated data are similar but by using our method the data proper is not revealed to the second party during the mining process and hence the privacy will be preserved.


Transformation of Networks through Cognitive Approaches

Abstract: The growth in data traffic and the increased demand for quality of service had generated a large demand for network systems to be more efficient. The introduction of improved routing systems to meet the increasing demand and varied protocols to accommodate various scales of challenges in network efficiency had further complicated the operations. This means that a better mode of intelligence has to be infused into networking for smoother operations and better autonomic features. Cognitive networks are defined and analyzed in this angle. They are identified to have the potential to deal with the future user related quality and efficiency of service at optimized levels. The cognitive elements of a system like perception, learning, planning, reasoning and decision forming can enable the systems to be more aware of their environment and offer better services. These approaches are expected to transform the mode of operation of future networks.


Multicore Applications in Real Time Systems

Abstract: Microprocessor roadmaps clearly show a trend towards multiple core CPUs. Modern operating systems already make use of these CPU architectures by distributing tasks between processing cores thereby increasing system performance. This review article highlights a brief introduction of what a multicore system is, the various methods adopted to program these systems and also the industrial application of these high speed systems.


Effective Defect Prevention Approach in Software Process for Achieving Better Quality Levels

Abstract: Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a high quality product. The key challenge of an IT industry is to engineer a software product with minimum post deployment defects. This effort is an analysis based on data obtained for five selected projects from leading software companies of varying software production competence. The main aim of this paper is to provide information on various methods and practices supporting defect detection and prevention leading to thriving software generation. The defect prevention technique unearths 99% of defects. Inspection is found to be an essential technique in generating ideal software generation in factories through enhanced methodologies of abetted and unaided inspection schedules. On an average 13 % to 15% of inspection and 25% - 30% of testing out of whole project effort time is required for 99% - 99.75% of defect elimination. A comparison of the end results for the five selected projects between the companies is also brought about throwing light on the possibility of a particular company to position itself with an appropriate complementary ratio of inspection testing.


Estimation of Defect proneness Using Design complexity Measurements in Object- Oriented Software

Abstract: Software engineering is continuously facing the challenges of growing complexity of software packages and increased level of data on defects and drawbacks from software production process. This makes a clarion call for inventions and methods which can enable a more reusable, reliable, easily maintainable and high quality software systems with deeper control on software generation process. Quality and productivity are indeed the two most important parameters for controlling any industrial process. Implementation of a successful control system requires some means of measurement. Software metrics play an important role in the management aspects of the software development process such as better planning, assessment of improvements, resource allocation and reduction of unpredictability. The process involving early detection of potential problems, productivity evaluation and evaluating external quality factors such as reusability, maintainability, defect proneness and complexity are of utmost importance. Here we discuss the application of CK metrics and estimation model to predict the external quality parameters for optimizing the design process and production process for desired levels of quality. Estimation of defect-proneness in object-oriented system at design level is developed using a novel methodology where models of relationship between CK metrics and defect-proneness index is achieved. A multifunctional estimation approach captures the correlation between CK metrics and defect proneness level of software modules.


Farthest-Polygon Voronoi Diagrams

Abstract: Given a family of k disjoint connected polygonal sites in general position and of total complexity n, we consider the farthest-site Voronoi diagram of these sites, where the distance to a site is the distance to a closest point on it. We show that the complexity of this diagram is O(n), and give an O(n log^3 n) time algorithm to compute it. We also prove a number of structural properties of this diagram. In particular, a Voronoi region may consist of k-1 connected components, but if one component is bounded, then it is equal to the entire region.


Type-Safe Feature-Oriented Product Lines

Abstract: A feature-oriented product line is a family of programs that share a common set of features. A feature implements a stakeholder's requirement, represents a design decision and configuration option and, when added to a program, involves the introduction of new structures, such as classes and methods, and the refinement of existing ones, such as extending methods. With feature-oriented decomposition, programs can be generated, solely on the basis of a user's selection of features, by the composition of the corresponding feature code. A key challenge of feature-oriented product line engineering is how to guarantee the correctness of an entire feature-oriented product line, i.e., of all of the member programs generated from different combinations of features. As the number of valid feature combinations grows progressively with the number of features, it is not feasible to check all individual programs. The only feasible approach is to have a type system check the entire code base of the feature-oriented product line. We have developed such a type system on the basis of a formal model of a feature-oriented Java-like language. We demonstrate that the type system ensures that every valid program of a feature-oriented product line is well-typed and that the type system is complete.


Tight products and Expansion

Abstract: In this paper we study a new product of graphs called {\em tight product}. A graph $H$ is said to be a tight product of two (undirected multi) graphs $G_1$ and $G_2$, if $V(H)=V(G_1)\times V(G_2)$ and both projection maps $V(H)\to V(G_1)$ and $V(H)\to V(G_2)$ are covering maps. It is not a priori clear when two given graphs have a tight product (in fact, it is $NP$-hard to decide). We investigate the conditions under which this is possible. This perspective yields a new characterization of class-1 $(2k+1)$-regular graphs. We also obtain a new model of random $d$-regular graphs whose second eigenvalue is almost surely at most $O(d^{3/4})$. This construction resembles random graph lifts, but requires fewer random bits.


Collaboration in an Open Data eScience: A Case Study of Sloan Digital Sky Survey

Abstract: Current science and technology has produced more and more publically accessible scientific data. However, little is known about how the open data trend impacts a scientific community, specifically in terms of its collaboration behaviors. This paper aims to enhance our understanding of the dynamics of scientific collaboration in the open data eScience environment via a case study of co-author networks of an active and highly cited open data project, called Sloan Digital Sky Survey. We visualized the co-authoring networks and measured their properties over time at three levels: author, institution, and country levels. We compared these measurements to a random network model and also compared results across the three levels. The study found that 1) the collaboration networks of the SDSS community transformed from random networks to small-world networks; 2) the number of author-level collaboration instances has not changed much over time, while the number of collaboration instances at the other two levels has increased over time; 3) pairwise institutional collaboration become common in recent years. The open data trend may have both positive and negative impacts on scientific collaboration.


Plausible Mobility: Inferring Movement from Contacts

Abstract: We address the difficult question of inferring plausible node mobility based only on information from wireless contact traces. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure, whereas contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. We propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.


Infocast: A New Paradigm for Collaborative Content Distribution from Roadside Units to Vehicular Networks Using Rateless Codes

Abstract: In this paper, we address the problem of distributing a large amount of bulk data to a sparse vehicular network from roadside infostations, using efficient vehicle-to-vehicle collaboration. Due to the highly dynamic nature of the underlying vehicular network topology, we depart from architectures requiring centralized coordination, reliable MAC scheduling, or global network state knowledge, and instead adopt a distributed paradigm with simple protocols. In other words, we investigate the problem of reliable dissemination from multiple sources when each node in the network shares a limited amount of its resources for cooperating with others. By using \emph{rateless} coding at the Road Side Unit (RSU) and using vehicles as data carriers, we describe an efficient way to achieve reliable dissemination to all nodes (even disconnected clusters in the network). In the nutshell, we explore vehicles as mobile storage devices. We then develop a method to keep the density of the rateless codes packets as a function of distance from the RSU at the desired level set for the target decoding distance. We investigate various tradeoffs involving buffer size, maximum capacity, and the mobility parameter of the vehicles.


On Fast Algorithm for Computing Even-Length DCT

Abstract: We study recursive algorithm for computing DCT of lengths $N=q 2^m$ ($m,q \in \mathbb{N}$, $q$ is odd) due to C.W.Kok. We show that this algorithm has the same multiplicative complexity as theoretically achievable by the prime factor decomposition, when $m \leqslant 2$. We also show that C.W.Kok's factorization allows a simple conversion to a scaled form. We analyze complexity of such a scaled factorization, and show that for some lengths it achieves lower multiplicative complexity than one of known prime factor-based scaled transforms.


Network Codes Resilient to Jamming and Eavesdropping

Abstract: We consider the problem of communicating information over a network secretly and reliably in the presence of a hidden adversary who can eavesdrop and inject malicious errors. We provide polynomial-time, rate-optimal distributed network codes for this scenario, improving on the rates achievable in previous work. Our main contribution shows that as long as the sum of the adversary's jamming rate Zo and his eavesdropping rate Zi is less than the network capacity C, (i.e., Zo+Zi<C), our codes can communicate (with vanishingly small error probability) a single bit correctly and without leaking any information to the adversary. We then use this to design codes that allow communication at the optimal source rate of C-Zo-Zi, while keeping the communicated message secret from the adversary. Interior nodes are oblivious to the presence of adversaries and perform random linear network coding; only the source and destination need to be tweaked. In proving our results we correct an error in prior work by a subset of the authors in this work.


A Multicore Processor based Real-Time System for Automobile management application

Abstract: In this paper we propose an Intelligent Management System which is capable of managing the automobile functions using the rigorous real-time principles and a multicore processor in order to realize higher efficiency and safety for the vehicle. It depicts how various automobile functionalities can be fine grained and treated to fit in real time concepts. It also shows how the modern multicore processors can be of good use in organizing vast amounts of correlated functions to be executed in real-time with excellent time commitments. The modeling of the automobile tasks with real time commitments, organizing appropriate scheduling for various real time tasks and the usage of a multicore processor enables the system to realize higher efficiency and offer better safety levels to the vehicle. The industry available real time operating system is used for scheduling various tasks and jobs on the multicore processor.


Severity Prediction of Drought in A Large Geographical Area Using Distributed Wireless Sensor Networks

Abstract: In this paper, the severity prediction of drought through the implementation of modern sensor networks is discussed. We describe how to design a drought prediction system using wireless sensor networks. This paper will describe a terrestrial interconnected wireless sensor network paradigm for the prediction of severity of drought over a vast area of 10,000 sq km. The communication architecture for sensor network is outlined and the protocols developed for each layer is explored. The data integration model and sensor data analysis at the central computer is explained. The advantages and limitations are discussed along with the use of wireless standards. They are analyzed for its relevance. Finally a conclusion is presented along with open research issues.


Page-Differential Logging: An Efficient and DBMS-independent Approach for Storing Data into Flash Memory

Abstract: Flash memory is widely used as the secondary storage in lightweight computing devices due to its outstanding advantages over magnetic disks. Flash memory has many access characteristics different from those of magnetic disks, and how to take advantage of them is becoming an important research issue. There are two existing approaches to storing data into flash memory: page-based and log-based. The former has good performance for read operations, but poor performance for write operations. In contrast, the latter has good performance for write operations when updates are light, but poor performance for read operations. In this paper, we propose a new method of storing data, called page-differential logging, for flash-based storage systems that solves the drawbacks of the two methods. The primary characteristics of our method are: (1) writing only the difference (which we define as the page-differential) between the original page in flash memory and the up-to-date page in memory; (2) computing and writing the page-differential only once at the time the page needs to be reflected into flash memory. The former contrasts with existing page-based methods that write the whole page including both changed and unchanged parts of data or from log-based ones that keep track of the history of all the changes in a page. Our method allows existing disk-based DBMSs to be reused as flash-based DBMSs just by modifying the flash memory driver, i.e., it is DBMS-independent. Experimental results show that the proposed method improves the I/O performance by 1.2 ~ 6.1 times over existing methods for the TPC-C data of approximately 1 Gbytes.


Effectiveness Of Defect Prevention In I.T. For Product Development

Abstract: Defect Prevention is the most critical but most neglected component of the software quality assurance in any project. If applied at all stages of software development, it can reduce the time, cost and resources required to engineer a high quality product. Software inspection has proved to be the most effective and efficient technique enabling defect detection and prevention. Inspections carried at all phases of software life cycle have proved to be most beneficial and value added to the attributes of the software. Work is an analysis based on the data collected for three different projects from a leading product based company. The purpose of the paper is to show that 55% to 65% of total number of defects occurs at design phase. Position of this paper also emphasizes the importance of inspections at all phases of the product development life cycle in order to achieve the minimal post deployment defects.


Fault Tolerance in Real Time Multiprocessors - Embedded Systems

Abstract: All real time tasks which are termed as critical tasks by nature have to complete its execution before its deadline, even in presence of faults. The most popularly used real time task assignment algorithms are First Fit (FF), Best Fit (BF), Bin Packing (BP).The common task scheduling algorithms are Rate Monotonic (RM), Earliest Deadline First (EDF) etc.All the current approaches deal with either fault tolerance or criticality in real time. In this paper we have proposed an integrated approach with a new algorithm, called SASA (Sorting And Sequential Assignment) which maps the real time task assignment with task schedule and fault tolerance


Software Components for Web Services

Abstract: Service-oriented computing has emerged as the new area to address software as a service. This paper proposes a model for component based development for service-oriented systems and have created best practice guidelines on software component design.


Gradient Based Seeded Region Grow method for CT Angiographic Image Segmentation

Abstract: Segmentation of medical images using seeded region growing technique is increasingly becoming a popular method because of its ability to involve high-level knowledge of anatomical structures in seed selection process. Region based segmentation of medical images are widely used in varied clinical applications like visualization, bone detection, tumor detection and unsupervised image retrieval in clinical databases. As medical images are mostly fuzzy in nature, segmenting regions based intensity is the most challenging task. In this paper, we discuss about popular seeded region grow methodology used for segmenting anatomical structures in CT Angiography images. We have proposed a gradient based homogeneity criteria to control the region grow process while segmenting CTA images.


Cognitive Routing with Stretched Network Awareness through Hidden Markov Model Learning at Router Level

Abstract: The routing of packets are generally performed based on the destination address and forward link channel available from the instantaneous Router without sufficient cognizance of either the performance of the forward Router or forward channel characteristics. The lack of awareness of forward channel property can lead to packet loss or delayed delivery leading to multipleretransmissions or routing to an underperforming pathway. This paper describes an application of Cognitive Network to improve the network performance by implementing a Hidden Markov Model (HMM) algorithm for learning and predicting the performance of surrounding routers continuously while a routing demand is initiated. The cognition segment/domain of every router can gain knowledge about the quality of forward network. The information of the current network conditions is shared between routers by the Forward Channel Performance Index FCPI. This enables complete cognition of surroundings and efficient delivery of messages in various paradigms of performance


Application of Artificial Neural Networks in Aircraft Maintenance, Repair and Overhaul Solutions

Abstract: This paper reviews application of Artificial Neural Networks in Aircraft Maintenance, Repair and Overhaul (MRO). MRO solutions are designed to facilitate the authoring and delivery of maintenance and repair information to the line maintenance technicians who need to improve aircraft repair turn around time, optimize the efficiency and consistency of fleet maintenance and ensure regulatory compliance. The technical complexity of aircraft systems, especially in avionics, has increased to the point at which it poses a significant troubleshotting and repair challenge for MRO personnel. As per the existing scenario, the MRO systems in place are inefficient. In this paper, we propose the centralization and integration of the MRO database to increase its efficiency. Moreover the implementation of Artificial Neural Networks in this system can rid the system of many of its deficiencies. In order to make the system more efficient we propose to integrate all the modules so as to reduce the efficacy of repair.


Multicast Transmission Prefix and Popularity Aware Interval Caching Based Admission Control Policy

Abstract: Admission control is a key component in multimedia servers, which will allow the resources to be used by the client only when they are available. A problem faced by numerous content serving machines is overload, when there are too many clients who need to be served, the server tends to slow down. An admission control algorithm for a multimedia server is responsible for determining if a new request can be accepted without violating the QoS requirements of the existing requests in the system. By caching and streaming only the data in the interval between two successive requests on the same object, the following request can be serviced directly from the buffer cache without disk operations and within the deadline of the request. An admission control strategy based on Popularity-aware interval caching for Prefix [3] scheme extends the interval caching by considering different popularity of multimedia objects. The method of Prefix caching with multicast transmission of popular objects utilizes the hard disk and network bandwidth efficiently and increases the number of requests being served.


Enhancing Fine Motor Skills of Wards with Special Needs Using Cluster Model of Cognition

Abstract: Technology offers great potential to overcome physical barriers of human race. This paper presents the methods of enhanced learning applicable to children having special needs using better human-computer interaction. The Audio-Visual (AV) effects that the graphic tools or animations help in achieving better learning, understanding, remembering and performance from such students. The 3L-R Cluster Program Model enable them to look into pictures and animated objects while listening to the related audio. It also motivates them to do the FMS development activities like drawing, coloring, tracing etc., certain types of games in the clustered model will help the children to improve concentration, thinking, reasoning, cognitive skills and the eye-to hand co-ordination. Here we introduced a novel cluster model along with the methodology described which provides an ample exposure to the effectiveness of the training. Classify the students with similar problems or disability and the associated curriculum of modified teaching methodology to meet their special needs is met through the specialized IT tool which form a part of the cluster model. It ensures effective learning in wards by enhancing multifaceted interaction. The main objective of this paper is to support the development of Fine Motor Skills (FMS) of wards with special needs.


Two-phase algorithms for the parametric shortest path problem

Abstract: A {\em parametric weighted graph} is a graph whose edges are labeled with continuous real functions of a single common variable. For any instantiation of the variable, one obtains a standard edge-weighted graph. Parametric weighted graph problems are generalizations of weighted graph problems, and arise in various natural scenarios. Parametric weighted graph algorithms consist of two phases. A {\em preprocessing phase} whose input is a parametric weighted graph, and whose output is a data structure, the advice, that is later used by the {\em instantiation phase}, where a specific value for the variable is given. The instantiation phase outputs the solution to the (standard) weighted graph problem that arises from the instantiation. The goal is to have the running time of the instantiation phase supersede the running time of any algorithm that solves the weighted graph problem from scratch, by taking advantage of the advice. In this paper we construct several parametric algorithms for the shortest path problem. For the case of linear function weights we present an algorithm for the single source shortest path problem.