Bounded Satisfiability for PCTL

Abstract: While model checking PCTL for Markov chains is decidable in polynomial-time, the decidability of PCTL satisfiability, as well as its finite model property, are long standing open problems. While general satisfiability is an intriguing challenge from a purely theoretical point of view, we argue that general solutions would not be of interest to practitioners: such solutions could be too big to be implementable or even infinite. Inspired by bounded synthesis techniques, we turn to the more applied problem of seeking models of a bounded size: we restrict our search to implementable -- and therefore reasonably simple -- models. We propose a procedure to decide whether or not a given PCTL formula has an implementable model by reducing it to an SMT problem. We have implemented our techniques and found that they can be applied to the practical problem of sanity checking -- a procedure that allows a system designer to check whether their formula has an unexpectedly small model.


A collaborative ant colony metaheuristic for distributed multi-level lot-sizing

Abstract: The paper presents an ant colony optimization metaheuristic for collaborative planning. Collaborative planning is used to coordinate individual plans of self-interested decision makers with private information in order to increase the overall benefit of the coalition. The method consists of a new search graph based on encoded solutions. Distributed and private information is integrated via voting mechanisms and via a simple but effective collaborative local search procedure. The approach is applied to a distributed variant of the multi-level lot-sizing problem and evaluated by means of 352 benchmark instances from the literature. The proposed approach clearly outperforms existing approaches on the sets of medium and large sized instances. While the best method in the literature so far achieves an average deviation from the best known non-distributed solutions of 46 percent for the set of the largest instances, for example, the presented approach reduces the average deviation to only 5 percent.


Deducing Security Goals From Shape Analysis Sentences

Abstract: Guttman presented a model-theoretic approach to establishing security goals in the context of Strand Space theory. In his approach, a run of the Cryptographic Protocol Shapes Analyzer (CPSA) produces models that determine if a goal is satisfied. This paper presents a method for extracting a sentence that completely characterizes a run of CPSA. Logical deduction can then be used to determine if a goal is satisfied. This method has been implemented and is available to all.


Doubleclick Ad Exchange Auction

Abstract: Display advertisements on the web are sold via ad exchanges that use real time auction. We describe the challenges of designing a suitable auction, and present a simple auction called the Optional Second Price (OSP) auction that is currently used in Doubleclick Ad Exchange.


The Kernelized Stochastic Batch Perceptron

Abstract: We present a novel approach for training kernel Support Vector Machines, establish learning runtime guarantees for our method that are better then those of any other known kernelized SVM optimization approach, and show that our method works well in practice compared to existing alternatives.


Multi-level agent-based modeling with the Influence Reaction principle

Abstract: This paper deals with the specification and the implementation of multi-level agent-based models, using a formal model, IRM4MLS (an Influence Reaction Model for Multi-Level Simulation), based on the Influence Reaction principle. Proposed examples illustrate forms of top-down control in (multi-level) multi-agent based-simulations.


Agreement in Directed Dynamic Networks

Abstract: We study distributed computation in synchronous dynamic networks where an omniscient adversary controls the unidirectional communication links. Its behavior is modeled as a sequence of directed graphs representing the active (i.e. timely) communication links per round. We prove that consensus is impossible under some natural weak connectivity assumptions, and introduce vertex-stable root components as a means for circumventing this impossibility. Essentially, we assume that there is a short period of time during which an arbitrary part of the network remains strongly connected, while its interconnect topology may keep changing continuously. We present a consensus algorithm that works under this assumption, and prove its correctness. Our algorithm maintains a local estimate of the communication graphs, and applies techniques for detecting stable network properties and univalent system configurations. Our possibility results are complemented by several impossibility results and lower bounds for consensus and other distributed computing problems like leader election, revealing that our algorithm is asymptotically optimal.


On the Performance of Packet Aggregation in IEEE 802.11ac MU-MIMO WLANs

Abstract: Multi-user spatial multiplexing combined with packet aggregation can significantly increase the performance of Wireless Local Area Networks (WLANs). In this letter, we present and evaluate a simple technique to perform packet aggregation in IEEE 802.11ac MU-MIMO (Multi-user Multiple Input Multiple Output) WLANs. Results show that in non-saturation conditions both the number of active stations (STAs) and the queue size have a significant impact on the system performance. If the number of stations is excessively high, the heterogeneity of destinations in the packets contained in the queue makes it difficult to take full advantage of packet aggregation. This effect can be alleviated by increasing the queue size, which increases the chances to schedule a large number of packets at each transmission, hence improving the system throughput at the cost of a higher delay.


Approximate Well-supported Nash Equilibria below Two-thirds

Abstract: In an epsilon-Nash equilibrium, a player can gain at most epsilon by changing his behaviour. Recent work has addressed the question of how best to compute epsilon-Nash equilibria, and for what values of epsilon a polynomial-time algorithm exists. An epsilon-well-supported Nash equilibrium (epsilon-WSNE) has the additional requirement that any strategy that is used with non-zero probability by a player must have payoff at most epsilon less than the best response. A recent algorithm of Kontogiannis and Spirakis shows how to compute a 2/3-WSNE in polynomial time, for bimatrix games. Here we introduce a new technique that leads to an improvement to the worst-case approximation guarantee.


Unit contradiction versus unit propagation

Abstract: Some aspects of the result of applying unit resolution on a CNF formula can be formalized as functions with domain a set of partial truth assignments. We are interested in two ways for computing such functions, depending on whether the result is the production of the empty clause or the assignment of a variable with a given truth value. We show that these two models can compute the same functions with formulae of polynomially related sizes, and we explain how this result is related to the CNF encoding of Boolean constraints.


Survey on Security Issues in Cloud Computing and Associated Mitigation Techniques

Abstract: Cloud Computing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for IT-based solutions and services that the industry uses. It promises to provide a flexible IT architecture, accessible through internet for lightweight portable devices. This would allow multi-fold increase in the capacity or capabilities of the existing and new software. In a cloud computing environment, the entire data reside over a set of networked resources, enabling the data to be accessed through virtual machines. Since these data-centers may lie in any corner of the world beyond the reach and control of users, there are multifarious security and privacy challenges that need to be understood and taken care of. Also, one can never deny the possibility of a server breakdown that has been witnessed, rather quite often in the recent times. There are various issues that need to be dealt with respect to security and privacy in a cloud computing scenario. This extensive survey paper aims to elaborate and analyze the numerous unresolved issues threatening the cloud computing adoption and diffusion affecting the various stake-holders linked to it.


Efficient Fruit Defect Detection and Glare removal Algorithm by anisotropic diffusion and 2D Gabor filter

Abstract: This paper focuses on fruit defect detection and glare removal using morphological operations, Glare removal can be considered as an important preprocessing step as uneven lighting may introduce it in images, which hamper the results produced through segmentation by Gabor filters .The problem of glare in images is very pronounced sometimes due to the unusual reflectance from the camera sensor or stray light entering, this method counteracts this problem and makes the defect detection much more pronounced. Anisotropic diffusion is used for further smoothening of the images and removing the high energy regions in an image for better defect detection and makes the defects more retrievable. Our algorithm is robust and scalable the employability of a particular mask for glare removal has been checked and proved useful for counteracting.this problem, anisotropic diffusion further enhances the defects with its use further Optimal Gabor filter at various orientations is used for defect detection.


On the Complexity of Finding Narrow Proofs

Abstract: We study the complexity of the following "resolution width problem": Does a given 3-CNF have a resolution refutation of width k? We prove that the problem cannot be decided in time O(n^((k-3)/12)). This lower bound is unconditional and does not rely on any unproven complexity theoretic assumptions. The lower bound is matched by a trivial upper bound of n^O(k). We also prove that the resolution width problem is EXPTIME-complete (if k is part of the input). This confirms a conjecture by Vardi, who has first raised the question for the complexity of the resolution width problem. Furthermore, we prove that the variant of the resolution width problem for regular resolution is PSPACE-complete, confirming a conjecture by Urquhart.


A Note on the Balanced ST-Connectivity

Abstract: We prove that every YES instance of Balanced ST-Connectivity has a balanced path of polynomial length.


Self-improving Algorithms for Coordinate-wise Maxima

Abstract: Computing the coordinate-wise maxima of a planar point set is a classic and well-studied problem in computational geometry. We give an algorithm for this problem in the \emph{self-improving setting}. We have $n$ (unknown) independent distributions $\cD_1, \cD_2, ..., \cD_n$ of planar points. An input pointset $(p_1, p_2, ..., p_n)$ is generated by taking an independent sample $p_i$ from each $\cD_i$, so the input distribution $\cD$ is the product $\prod_i \cD_i$. A self-improving algorithm repeatedly gets input sets from the distribution $\cD$ (which is \emph{a priori} unknown) and tries to optimize its running time for $\cD$. Our algorithm uses the first few inputs to learn salient features of the distribution, and then becomes an optimal algorithm for distribution $\cD$. Let $\OPT_\cD$ denote the expected depth of an \emph{optimal} linear comparison tree computing the maxima for distribution $\cD$. Our algorithm eventually has an expected running time of $O(\text{OPT}_\cD + n)$, even though it did not know $\cD$ to begin with. Our result requires new tools to understand linear comparison trees for computing maxima. We show how to convert general linear comparison trees to very restricted versions, which can then be related to the running time of our algorithm. An interesting feature of our algorithm is an interleaved search, where the algorithm tries to determine the likeliest point to be maximal with minimal computation. This allows the running time to be truly optimal for the distribution $\cD$.


Bounded Counter Languages

Abstract: We show that deterministic finite automata equipped with $k$ two-way heads are equivalent to deterministic machines with a single two-way input head and $k-1$ linearly bounded counters if the accepted language is strictly bounded, i.e., a subset of $a_1^*a_2^*... a_m^*$ for a fixed sequence of symbols $a_1, a_2,..., a_m$. Then we investigate linear speed-up for counter machines. Lower and upper time bounds for concrete recognition problems are shown, implying that in general linear speed-up does not hold for counter machines. For bounded languages we develop a technique for speeding up computations by any constant factor at the expense of adding a fixed number of counters.


Optimal bounds for monotonicity and Lipschitz testing over hypercubes and hypergrids

Abstract: The problem of monotonicity testing over the hypergrid and its special case, the hypercube, is a classic, well-studied, yet unsolved question in property testing. We are given query access to $f:[k]^n \mapsto \R$ (for some ordered range $\R$). The hypergrid/cube has a natural partial order given by coordinate-wise ordering, denoted by $\prec$. A function is \emph{monotone} if for all pairs $x \prec y$, $f(x) \leq f(y)$. The distance to monotonicity, $\eps_f$, is the minimum fraction of values of $f$ that need to be changed to make $f$ monotone. For $k=2$ (the boolean hypercube), the usual tester is the \emph{edge tester}, which checks monotonicity on adjacent pairs of domain points. It is known that the edge tester using $O(\eps^{-1}n\log|\R|)$ samples can distinguish a monotone function from one where $\eps_f > \eps$. On the other hand, the best lower bound for monotonicity testing over the hypercube is $\min(|\R|^2,n)$. This leaves a quadratic gap in our knowledge, since $|\R|$ can be $2^n$. We resolve this long standing open problem and prove that $O(n/\eps)$ samples suffice for the edge tester. For hypergrids, known testers require $O(\eps^{-1}n\log k\log |\R|)$ samples, while the best known (non-adaptive) lower bound is $\Omega(\eps^{-1} n\log k)$. We give a (non-adaptive) monotonicity tester for hypergrids running in $O(\eps^{-1} n\log k)$ time. Our techniques lead to optimal property testers (with the same running time) for the natural \emph{Lipschitz property} on hypercubes and hypergrids. (A $c$-Lipschitz function is one where $|f(x) - f(y)| \leq c\|x-y\|_1$.) In fact, we give a general unified proof for $O(\eps^{-1}n\log k)$-query testers for a class of "bounded-derivative" properties, a class containing both monotonicity and Lipschitz.


The Cerny Conjecture

Abstract: The \v{C}ern\'y conjecture (\v{C}ern\'y, 1964) states that each n-state \san\ possess a \sw\ of length $(n-1)^2$. From the other side the best upper bound for the \rl\ of n-state \sa\ known so far is equal to $\frac{n^3-n}6$ (Pin, 1983) and so is cubic (a slightly better though still cubic upper bound $\frac{n(7n^2+6n-16)}{48}$ has been claimed in Trahtman but the published proof of this result contains an unclear place) in $n$. In the paper the \v{C}ern\'y conjecture is reduced to a simpler conjecture. In particular, we prove \v{C}ern\'y conjecture for one-cluster automata and quadratic upper bounds for automata closed to one-cluster automata. Our approach utilize theory of Markov chains and one simple fact from linear programming.


GeT_Move: An Efficient and Unifying Spatio-Temporal Pattern Mining Algorithm for Moving Objects

Abstract: Recent improvements in positioning technology has led to a much wider availability of massive moving object data. A crucial task is to find the moving objects that travel together. Usually, these object sets are called spatio-temporal patterns. Due to the emergence of many different kinds of spatio-temporal patterns in recent years, different approaches have been proposed to extract them. However, each approach only focuses on mining a specific kind of pattern. In addition to being a painstaking task due to the large number of algorithms used to mine and manage patterns, it is also time consuming. Moreover, we have to execute these algorithms again whenever new data are added to the existing database. To address these issues, we first redefine spatio-temporal patterns in the itemset context. Secondly, we propose a unifying approach, named GeT_Move, which uses a frequent closed itemset-based spatio-temporal pattern-mining algorithm to mine and manage different spatio-temporal patterns. GeT_Move is implemented in two versions which are GeT_Move and Incremental GeT_Move. To optimize the efficiency and to free the parameters setting, we also propose a Parameter Free Incremental GeT_Move algorithm. Comprehensive experiments are performed on real datasets as well as large synthetic datasets to demonstrate the effectiveness and efficiency of our approaches.


PID Parameters Optimization by Using Genetic Algorithm

Abstract: Time delays are components that make time-lag in systems response. They arise in physical, chemical, biological and economic systems, as well as in the process of measurement and computation. In this work, we implement Genetic Algorithm (GA) in determining PID controller parameters to compensate the delay in First Order Lag plus Time Delay (FOLPD) and compare the results with Iterative Method and Ziegler-Nichols rule results.


A New Approach to Online Scheduling: Approximating the Optimal Competitive Ratio

Abstract: We propose a new approach to competitive analysis in online scheduling by introducing the novel concept of competitive-ratio approximation schemes. Such a scheme algorithmically constructs an online algorithm with a competitive ratio arbitrarily close to the best possible competitive ratio for any online algorithm. We study the problem of scheduling jobs online to minimize the weighted sum of completion times on parallel, related, and unrelated machines, and we derive both deterministic and randomized algorithms which are almost best possible among all online algorithms of the respective settings. We also generalize our techniques to arbitrary monomial cost functions and apply them to the makespan objective. Our method relies on an abstract characterization of online algorithms combined with various simplifications and transformations. We also contribute algorithmic means to compute the actual value of the best possi- ble competitive ratio up to an arbitrary accuracy. This strongly contrasts all previous manually obtained competitiveness results for algorithms and, most importantly, it reduces the search for the optimal com- petitive ratio to a question that a computer can answer. We believe that our concept can also be applied to many other problems and yields a new perspective on online algorithms in general.


Certified Rational Parametric Approximation of Real Algebraic Space Curves with Local Generic Position Method

Abstract: In this paper, an algorithm to compute a certified $G^1$ rational parametric approximation for algebraic space curves is given by extending the local generic position method for solving zero dimensional polynomial equation systems to the case of dimension one. By certified, we mean the approximation curve and the original curve have the same topology and their Hausdauff distance is smaller than a given precision. Thus, the method also gives a new algorithm to compute the topology for space algebraic curves. The main advantage of the algorithm, inhering from the local generic method, is that topology computation and approximation for a space curve is directly reduced to the same tasks for two plane curves. In particular, the error bound of the approximation space curve is obtained from the error bounds of the approximation plane curves explicitly. Nontrivial examples are used to show the effectivity of the method.


A procedural framework and mathematical analysis for solid sweeps

Abstract: Sweeping is a powerful and versatile method of designing objects. Boundary of volumes (henceforth envelope) obtained by sweeping solids have been extensively investigated in the past, though, obtaining an accurate parametrization of the envelope remained computationally hard. The present work reports our approach to this problem as well as the important problem of identifying self-intersections within the envelope. Parametrization of the envelope is, of course, necessary for its use in most current CAD systems. We take the more interesting case when the solid is composed of several faces meeting smoothly. We show that the face structure of the envelope mimics locally that of the solid. We adopt the procedural approach at defining the geometry in this work which has the advantage of being accurate as well as computationally efficient. The problem of detecting local self-intersections is central to a robust implementation of the solid sweep. This has been addressed by computing a subtle mathematical invariant which detects self-intersections, and which is computationally benign and requires only point queries.


Reclaiming the energy of a schedule: models and algorithms

Abstract: We consider a task graph to be executed on a set of processors. We assume that the mapping is given, say by an ordered list of tasks to execute on each processor, and we aim at optimizing the energy consumption while enforcing a prescribed bound on the execution time. While it is not possible to change the allocation of a task, it is possible to change its speed. Rather than using a local approach such as backfilling, we consider the problem as a whole and study the impact of several speed variation models on its complexity. For continuous speeds, we give a closed-form formula for trees and series-parallel graphs, and we cast the problem into a geometric programming problem for general directed acyclic graphs. We show that the classical dynamic voltage and frequency scaling (DVFS) model with discrete modes leads to a NP-complete problem, even if the modes are regularly distributed (an important particular case in practice, which we analyze as the incremental model). On the contrary, the VDD-hopping model leads to a polynomial solution. Finally, we provide an approximation algorithm for the incremental model, which we extend for the general DVFS model.


Testing Booleanity and the Uncertainty Principle

Abstract: Let f:{-1,1}^n -> R be a real function on the hypercube, given by its discrete Fourier expansion, or, equivalently, represented as a multilinear polynomial. We say that it is Boolean if its image is in {-1,1}. We show that every function on the hypercube with a sparse Fourier expansion must either be Boolean or far from Boolean. In particular, we show that a multilinear polynomial with at most k terms must either be Boolean, or output values different than -1 or 1 for a fraction of at least 2/(k+2)^2 of its domain. It follows that given oracle access to f, together with the guarantee that its representation as a multilinear polynomial has at most k terms, one can test Booleanity using O(k^2) queries. We show an \Omega(k) queries lower bound for this problem. Our proof crucially uses Hirschman's entropic version of Heisenberg's uncertainty principle.


Robust methods for LTE and WiMAX dimensioning

Abstract: This paper proposes an analytic model for dimensioning OFDMA based networks like WiMAX and LTE systems. In such a system, users require a number of subchannels which depends on their \SNR, hence of their position and the shadowing they experience. The system is overloaded when the number of required subchannels is greater than the number of available subchannels. We give an exact though not closed expression of the loss probability and then give an algorithmic method to derive the number of subchannels which guarantees a loss probability less than a given threshold. We show that Gaussian approximation lead to optimistic values and are thus unusable. We then introduce Edgeworth expansions with error bounds and show that by choosing the right order of the expansion, one can have an approximate dimensioning value easy to compute but with guaranteed performance. As the values obtained are highly dependent from the parameters of the system, which turned to be rather undetermined, we provide a procedure based on concentration inequality for Poisson functionals, which yields to conservative dimensioning. This paper relies on recent results on concentration inequalities and establish new results on Edgeworth expansions.


Approximability of the Vertex Cover Problem in Power Law Graphs

Abstract: In this paper we construct an approximation algorithm for the Minimum Vertex Cover Problem (Min-VC) with an expected approximation ratio of 2-f(beta) for random Power Law Graphs (PLG) in the (alpha,beta)-model of Aiello et. al., where f(beta) is a strictly positive function of the parameter beta. We obtain this result by combining the Nemhauser and Trotter approach for Min-VC with a new deterministic rounding procedure which achieves an approximation ratio of 3/2 on a subset of low degree vertices for which the expected contribution to the cost of the associated linear program is sufficiently large.


Adjacency Matrix Based Energy Efficient Scheduling using S-MAC Protocol in Wireless Sensor Networks

Abstract: Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the shortest depths and schedules the idle node in to sleep mode for a specific time threshold so energy at the idle nodes can be saved.


A formal definition and a new security mechanism of physical unclonable functions

Abstract: The characteristic novelty of what is generally meant by a "physical unclonable function" (PUF) is precisely defined, in order to supply a firm basis for security evaluations and the proposal of new security mechanisms. A PUF is defined as a hardware device which implements a physical function with an output value that changes with its argument. A PUF can be clonable, but a secure PUF must be unclonable. This proposed meaning of a PUF is cleanly delineated from the closely related concepts of "conventional unclonable function", "physically obfuscated key", "random-number generator", "controlled PUF" and "strong PUF". The structure of a systematic security evaluation of a PUF enabled by the proposed formal definition is outlined. Practically all current and novel physical (but not conventional) unclonable physical functions are PUFs by our definition. Thereby the proposed definition captures the existing intuition about what is a PUF and remains flexible enough to encompass further research. In a second part we quantitatively characterize two classes of PUF security mechanisms, the standard one, based on a minimum secret read-out time, and a novel one, based on challenge-dependent erasure of stored information. The new mechanism is shown to allow in principle the construction of a "quantum-PUF", that is absolutely secure while not requiring the storage of an exponentially large secret. The construction of a PUF that is mathematically and physically unclonable in principle does not contradict the laws of physics.


Online submodular welfare maximization: Greedy is optimal

Abstract: We prove that no online algorithm (even randomized, against an oblivious adversary) is better than 1/2-competitive for welfare maximization with coverage valuations, unless $NP = RP$. Since the Greedy algorithm is known to be 1/2-competitive for monotone submodular valuations, of which coverage is a special case, this proves that Greedy provides the optimal competitive ratio. On the other hand, we prove that Greedy in a stochastic setting with i.i.d.items and valuations satisfying diminishing returns is $(1-1/e)$-competitive, which is optimal even for coverage valuations, unless $NP=RP$. For online budget-additive allocation, we prove that no algorithm can be 0.612-competitive with respect to a natural LP which has been used previously for this problem.


The Power of Linear Programming for Valued CSPs

Abstract: A class of valued constraint satisfaction problems (VCSPs) is characterised by a valued constraint language, a fixed set of cost functions on a finite domain. An instance of the problem is specified by a sum of cost functions from the language with the goal to minimise the sum. This framework includes and generalises well-studied constraint satisfaction problems (CSPs) and maximum constraint satisfaction problems (Max-CSPs). Our main result is a precise algebraic characterisation of valued constraint languages whose instances can be solved exactly by the basic linear programming relaxation. Using this result, we obtain tractability of several novel and previously widely-open classes of VCSPs, including problems over valued constraint languages that are: (1) submodular on arbitrary lattices; (2) bisubmodular (also known as k-submodular) on arbitrary finite domains; (3) weakly (and hence strongly) tree-submodular on arbitrary trees.


Set It and Forget It: Approximating the Set Once Strip Cover Problem

Abstract: We consider the Set Once Strip Cover problem, in which n wireless sensors are deployed over a one-dimensional region. Each sensor has a fixed battery that drains in inverse proportion to a radius that can be set just once, but activated at any time. The problem is to find an assignment of radii and activation times that maximizes the length of time during which the entire region is covered. We show that this problem is NP-hard. Second, we show that RoundRobin, the algorithm in which the sensors simply take turns covering the entire region, has a tight approximation guarantee of 3/2 in both Set Once Strip Cover and the more general Strip Cover problem, in which each radius may be set finitely-many times. Moreover, we show that the more general class of duty cycle algorithms, in which groups of sensors take turns covering the entire region, can do no better. Finally, we give an optimal O(n^2 log n)-time algorithm for the related Set Radius Strip Cover problem, in which all sensors must be activated immediately.


Space efficient streaming algorithms for the distance to monotonicity and asymmetric edit distance

Abstract: Approximating the length of the longest increasing sequence (LIS) of an array is a well-studied problem. We study this problem in the data stream model, where the algorithm is allowed to make a single left-to-right pass through the array and the key resource to be minimized is the amount of additional memory used. We present an algorithm which, for any $\delta > 0$, given streaming access to an array of length $n$ provides a $(1+\delta)$-multiplicative approximation to the \emph{distance to monotonicity} ($n$ minus the length of the LIS), and uses only $O((\log^2 n)/\delta)$ space. The previous best known approximation using polylogarithmic space was a multiplicative 2-factor. Our algorithm can be used to estimate the length of the LIS to within an additive $\delta n$ for any $\delta >0$ while previous algorithms could only achieve additive error $n(1/2-o(1))$. Our algorithm is very simple, being just 3 lines of pseudocode, and has a small update time. It is essentially a polylogarithmic space approximate implementation of a classic dynamic program that computes the LIS. We also give a streaming algorithm for approximating $LCS(x,y)$, the length of the longest common subsequence between strings $x$ and $y$, each of length $n$. Our algorithm works in the asymmetric setting (inspired by \cite{AKO10}), in which we have random access to $y$ and streaming access to $x$, and runs in small space provided that no single symbol appears very often in $y$. More precisely, it gives an additive-$\delta n$ approximation to $LCS(x,y)$ (and hence also to $E(x,y) = n-LCS(x,y)$, the edit distance between $x$ and $y$ when insertions and deletions, but not substitutions, are allowed), with space complexity $O(k(\log^2 n)/\delta)$, where $k$ is the maximum number of times any one symbol appears in $y$.


Faster Algorithms for Rectangular Matrix Multiplication

Abstract: Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations. In this paper we show that \alpha>0.30298, which improves the previous record \alpha>0.29462 by Coppersmith (Journal of Complexity, 1997). More generally, we construct a new algorithm for multiplying an n x n^k matrix by an n^k x n matrix, for any value k\neq 1. The complexity of this algorithm is better than all known algorithms for rectangular matrix multiplication. In the case of square matrix multiplication (i.e., for k=1), we recover exactly the complexity of the algorithm by Coppersmith and Winograd (Journal of Symbolic Computation, 1990). These new upper bounds can be used to improve the time complexity of several known algorithms that rely on rectangular matrix multiplication. For example, we directly obtain a O(n^{2.5302})-time algorithm for the all-pairs shortest paths problem over directed graphs with small integer weights, improving over the O(n^{2.575})-time algorithm by Zwick (JACM 2002), and also improve the time complexity of sparse square matrix multiplication.


Faster Walks in Graphs: A $\tilde O(n^2)$ Time-Space Trade-off for Undirected s-t Connectivity

Abstract: In this paper, we make use of the Metropolis-type walks due to Nonaka et al. (2010) to provide a faster solution to the $S$-$T$-connectivity problem in undirected graphs (USTCON). As our main result, we propose a family of randomized algorithms for USTCON which achieves a time-space product of $S\cdot T = \tilde O(n^2)$ in graphs with $n$ nodes and $m$ edges (where the $\tilde O$-notation disregards poly-logarithmic terms). This improves the previously best trade-off of $\tilde O(n m)$, due to Feige (1995). Our algorithm consists in deploying several short Metropolis-type walks, starting from landmark nodes distributed using the scheme of Broder et al. (1994) on a modified input graph. In particular, we obtain an algorithm running in time $\tilde O(n+m)$ which is, in general, more space-efficient than both BFS and DFS. We close the paper by showing how to fine-tune the Metropolis-type walk so as to match the performance parameters (e.g., average hitting time) of the unbiased random walk for any graph, while preserving a worst-case bound of $\tilde O(n^2)$ on cover time.


Cloud Computing Security in Business Information Systems

Abstract: Cloud computing providers' and customers' services are not only exposed to existing security risks, but, due to multi-tenancy, outsourcing the application and data, and virtualization, they are exposed to the emergent, as well. Therefore, both the cloud providers and customers must establish information security system and trustworthiness each other, as well as end users. In this paper we analyze main international and industrial standards targeting information security and their conformity with cloud computing security challenges. We evaluate that almost all main cloud service providers (CSPs) are ISO 27001:2005 certified, at minimum. As a result, we propose an extension to the ISO 27001:2005 standard with new control objective about virtualization, to retain generic, regardless of company's type, size and nature, that is, to be applicable for cloud systems, as well, where virtualization is its baseline. We also define a quantitative metric and evaluate the importance factor of ISO 27001:2005 control objectives if customer services are hosted on-premise or in cloud. The conclusion is that obtaining the ISO 27001:2005 certificate (or if already obtained) will further improve CSP and CC information security systems, and introduce mutual trust in cloud services but will not cover all relevant issues. In this paper we also continue our efforts in business continuity detriments cloud computing produces, and propose some solutions that mitigate the risks.


Numerical Invariants through Convex Relaxation and Max-Strategy Iteration

Abstract: In this article we develop a max-strategy improvement algorithm for computing least fixpoints of operators on on the reals that are point-wise maxima of finitely many monotone and order-concave operators. Computing the uniquely determined least fixpoint of such operators is a problem that occurs frequently in the context of numerical program/systems verification/analysis. As an example for an application we discuss how our algorithm can be applied to compute numerical invariants of programs by abstract interpretation based on quadratic templates.


Web Services Supply Chains: A Literature Review

Abstract: The aim of this review paper is to bring into light a potential area i.e., web services supply chains for research by analyzing the existing state of art in this. It is observed from the review process that there seems to be much less work done in the area of web service supply chains as compared to e-commerce and product oriented service supply chains. The service quality assurance models, end to end Quality of Service (QoS) models, attempts made to QoS attributes are also found to be from individual perspectives of participating entities in a service process rather than a collective perspective considering individual QoS attributes rather than multiple QoS attributes. In light of these gaps we highlight the comparison between product oriented and pure online/ web service supply chains, a need for quality driven optimization in the web services supply chains, perceived complexities in the existing work and propose a conceptual model.


Performance of the Google Desktop, Arabic Google Desktop and Peer to Peer Application in Arabic Language

Abstract: The Arabic language is a complex language; it is different from Western languages especially at the morphological and spelling variations. Indeed, the performance of information retrieval systems in the Arabic language is still a problem. For this reason, we are interested in studying the performance of the most famous search engine, which is a Google Desktop, while searching in Arabic language documents. Then, we propose an update to the Google Desktop to take into consideration in search the Arabic words that have the same root. After that, we evaluate the performance of the Google Desktop in this context. Also, we are interested in evaluation the performance of peer-to-peer application in two ways. The first one uses a simple indexation that indexes Arabic documents without taking in consideration the root of words. The second way takes in consideration the roots in the indexation of Arabic documents. This evaluation is done by using a corpus of ten thousand documents and one hundred different queries.


Exploring Application Logs

Abstract: This paper deals with the problem of analyzing application event logs in relevance to dependability evaluation. We present the significance of application logs as a valuable source of information on operational profiles, anomalies and errors. They can enhance classical approaches based on monitoring system logs and performance variables. Keywords; event monitoring, operational profiles, anomalies


Principal Component Analysis-Linear Discriminant Analysis Feature Extractor for Pattern Recognition

Abstract: Robustness of embedded biometric systems is of prime importance with the emergence of fourth generation communication devices and advancement in security systems This paper presents the realization of such technologies which demands reliable and error-free biometric identity verification systems. High dimensional patterns are not permitted due to eigen-decomposition in high dimensional image space and degeneration of scattering matrices in small size sample. Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors. Results show good pattern by multimodal biometric system proposed in this paper. This paper is aimed at investigating a biometric identity system using Principal Component Analysis and Lindear Discriminant Analysis with K-Nearest Neighbor and implementing such system in real-time using SignalWAVE.


An initial peer configuration algorithm for multi-streaming peer-to-peer networks

Abstract: The growth of the Internet technology enables us to use network applications for streaming audio and video. Especially, real-time streaming services using peer-to-peer (P2P) technology are currently emerging. An important issue on P2P streaming is how to construct a logical network (overlay network) on a physical network (IP network). In this paper, we propose an initial peer configuration algorithm for a multi-streaming peer-to-peer network. The proposed algorithm is based on a mesh-pull approach where any node has multiple parent and child nodes as neighboring nodes, and content transmitted between these neighboring nodes depends on their parent-child relationships. Our simulation experiments show that the proposed algorithm improves the number of joining node and traffic load.


C-slow Technique vs Multiprocessor in designing Low Area Customized Instruction set Processor for Embedded Applications

Abstract: The demand for high performance embedded processors, for consumer electronics, is rapidly increasing for the past few years. Many of these embedded processors depend upon custom built Instruction Ser Architecture (ISA) such as game processor (GPU), multimedia processors, DSP processors etc. Primary requirement for consumer electronic industry is low cost with high performance and low power consumption. A lot of research has been evolved to enhance the performance of embedded processors through parallel computing. But some of them focus superscalar processors i.e. single processors with more resources like Instruction Level Parallelism (ILP) which includes Very Long Instruction Word (VLIW) architecture, custom instruction set extensible processor architecture and others require more number of processing units on a single chip like Thread Level Parallelism (TLP) that includes Simultaneous Multithreading (SMT), Chip Multithreading (CMT) and Chip Multiprocessing (CMP). In this paper, we present a new technique, named C-slow, to enhance performance for embedded processors for consumer electronics by exploiting multithreading technique in single core processors. Without resulting into the complexity of micro controlling with Real Time Operating system (RTOS), C-slowed processor can execute multiple threads in parallel using single datapath of Instruction Set processing element. This technique takes low area & approach complexity of general purpose processor running RTOS.


Query Language for Complex Similarity Queries

Abstract: For complex data types such as multimedia, traditional data management methods are not suitable. Instead of attribute matching approaches, access methods based on object similarity are becoming popular. Recently, this resulted in an intensive research of indexing and searching methods for the similarity-based retrieval. Nowadays, many efficient methods are already available, but using them to build an actual search system still requires specialists that tune the methods and build the system manually. Several attempts have already been made to provide a more convenient high-level interface in a form of query languages for such systems, but these are limited to support only basic similarity queries. In this paper, we propose a new language that allows to formulate content-based queries in a flexible way, taking into account the functionality offered by a particular search engine in use. To ensure this, the language is based on a general data model with an abstract set of operations. Consequently, the language supports various advanced query operations such as similarity joins, reverse nearest neighbor queries, or distinct kNN queries, as well as multi-object and multi-modal queries. The language is primarily designed to be used with the MESSIF framework for content-based searching but can be employed by other retrieval systems as well.


The Complexity of Monotone Hybrid Logics over Linear Frames and the Natural Numbers

Abstract: Hybrid logic with binders is an expressive specification language. Its satisfiability problem is undecidable in general. If frames are restricted to N or general linear orders, then satisfiability is known to be decidable, but of non-elementary complexity. In this paper, we consider monotone hybrid logics (i.e., the Boolean connectives are conjunction and disjunction only) over N and general linear orders. We show that the satisfiability problem remains non-elementary over linear orders, but its complexity drops to PSPACE-completeness over N. We categorize the strict fragments arising from different combinations of modal and hybrid operators into NP-complete and tractable (i.e. complete for NC1or LOGSPACE). Interestingly, NP-completeness depends only on the fragment and not on the frame. For the cases above NP, satisfiability over linear orders is harder than over N, while below NP it is at most as hard. In addition we examine model-theoretic properties of the fragments in question.


A Complete Workflow for Development of Bangla OCR

Abstract: Developing a Bangla OCR requires bunch of algorithm and methods. There were many effort went on for developing a Bangla OCR. But all of them failed to provide an error free Bangla OCR. Each of them has some lacking. We discussed about the problem scope of currently existing Bangla OCR's. In this paper, we present the basic steps required for developing a Bangla OCR and a complete workflow for development of a Bangla OCR with mentioning all the possible algorithms required.


VANET Routing Protocols: Pros and Cons

Abstract: VANET (Vehicular Ad-hoc Network) is a new technology which has taken enormous attention in the recent years. Due to rapid topology changing and frequent disconnection makes it difficult to design an efficient routing protocol for routing data among vehicles, called V2V or vehicle to vehicle communication and vehicle to road side infrastructure, called V2I. The existing routing protocols for VANET are not efficient to meet every traffic scenarios. Thus design of an efficient routing protocol has taken significant attention. So, it is very necessary to identify the pros and cons of routing protocols which can be used for further improvement or development of any new routing protocol. This paper presents the pros and cons of VANET routing protocols for inter vehicle communication.


Experimental Analysis of AODV & DSR over TCP & CBR Connections with Varying Speed and Node Density in VANET

Abstract: Vehicular adhoc network or VANET is special types of adhoc network consists of moving cars referred to as nodes; provide a way to exchange any information between cars without depending on fixed infrastructure. For efficient communication between nodes various routing protocols and mobility models have been proposed based on different scenarios. Due to rapid topology changing and frequent disconnection makes it difficult to select suitable mobility model and routing protocols. Hence performance evaluation and comparison between routing protocols is required to understand any routing protocol as well as to develop a new routing protocol. In this research paper, the performance of two on-demand routing protocols AODV & DSR has been analyzed by means of packet delivery ratio, loss packet ratio & average end-to-end delay with varying speed limit and node density under TCP & CBR connection.


Performance Evaluation of Aodv&DSR with Varying Pause Time & Node Density Over TCP&CBR Connections in Vanet

Abstract: Vehicular ad hoc network is formed by cars which are called nodes; allow them to communicate with one another without using any fixed road side unit. It has some unique characteristics which make it different from other ad hoc network as well as difficult to define any exact mobility model and routing protocols because of their high mobility and changing mobility pattern. Hence performance of routing protocols can vary with the various parameters such as speed, pause time, node density and traffic scenarios. In this research paper, the performance of two on-demand routing protocols AODV & DSR has been analyzed by means of packet delivery ratio, loss packet ratio & average end-to-end delay with varying pause time and node density under TCP & CBR connection.


On the Value of Multiple Read/Write Streams for Data Compression

Abstract: We study whether, when restricted to using polylogarithmic memory and polylogarithmic passes, we can achieve qualitatively better data compression with multiple read/write streams than we can with only one. We first show how we can achieve universal compression using only one pass over one stream. We then show that one stream is not sufficient for us to achieve good grammar-based compression. Finally, we show that two streams are necessary and sufficient for us to achieve entropy-only bounds.


Scanning of Rich Web Applications for Parameter Tampering Vulnerabilities

Abstract: Web applications require exchanging parameters between a client and a server to function properly. In real-world systems such as online banking transfer, traversing multiple pages with parameters contributed by both the user and server is a must, and hence the applications have to enforce workflow and parameter dependency controls across multiple requests. An application that applies insufficient server-side input validations is however vulnerable to parameter tampering attacks, which manipulate the exchanged parameters. Existing fuzzing-based scanning approaches however neglected these important controls, and this caused their fuzzing requests to be dropped before they can reach any vulnerable code. In this paper, we propose a novel approach to identify the workflow and parameter dependent constraints, which are then maintained and leveraged for automatic detection of server acceptances during fuzzing. We realized the approach by building a generic blackbox parameter tampering scanner. It successfully uncovered a number of severe vulnerabilities, including one from the largest multi-national banking website, which other scanners miss.


How Many Vote Operations Are Needed to Manipulate A Voting System?

Abstract: In this paper, we propose a framework to study a general class of strategic behavior in voting, which we call vote operations. We prove the following theorem: if we fix the number of alternatives, generate $n$ votes i.i.d. according to a distribution $\pi$, and let $n$ go to infinity, then for any $\epsilon >0$, with probability at least $1-\epsilon$, the minimum number of operations that are needed for the strategic individual to achieve her goal falls into one of the following four categories: (1) 0, (2) $\Theta(\sqrt n)$, (3) $\Theta(n)$, and (4) $\infty$. This theorem holds for any set of vote operations, any individual vote distribution $\pi$, and any integer generalized scoring rule, which includes (but is not limited to) almost all commonly studied voting rules, e.g., approval voting, all positional scoring rules (including Borda, plurality, and veto), plurality with runoff, Bucklin, Copeland, maximin, STV, and ranked pairs. We also show that many well-studied types of strategic behavior fall under our framework, including (but not limited to) constructive/destructive manipulation, bribery, and control by adding/deleting votes, margin of victory, and minimum manipulation coalition size. Therefore, our main theorem naturally applies to these problems.


Experimenting with Component-Based Middleware for Adaptive Fault Tolerant Computing

Abstract: This short paper describes early experiments to validate the capabilities of a component-based platform to observe and control a software architecture in the small. This is part of a whole process for resilient computing, i.e. targeting the adaptation of fault-tolerance mechanisms at runtime.


Reducing Total Power Consumption Method in Cloud Computing Environments

Abstract: The widespread use of cloud computing services is expected to increase the power consumed by ICT equipment in cloud computing environments rapidly. This paper first identifies the need of the collaboration among servers, the communication network and the power network, in order to reduce the total power consumption by the entire ICT equipment in cloud computing environments. Five fundamental policies for the collaboration are proposed and the algorithm to realize each collaboration policy is outlined. Next, this paper proposes possible signaling sequences to exchange information on power consumption between network and servers, in order to realize the proposed collaboration policy. Then, in order to reduce the power consumption by the network, this paper proposes a method of estimating the volume of power consumption by all network devices simply and assigning it to an individual user.


Proposed congestion control method for cloud computing environments

Abstract: As cloud computing services rapidly expand their customer base, it has become important to share cloud resources, so as to provide them economically. In cloud computing services, multiple types of resources, such as processing ability, bandwidth and storage, need to be allocated simultaneously. If there is a surge of requests, a competition will arise between these requests for the use of cloud resources. This leads to the disruption of the service and it is necessary to consider a measure to avoid or relieve congestion of cloud computing environments. This paper proposes a new congestion control method for cloud computing environments which reduces the size of required resource for congested resource type instead of restricting all service requests as in the existing networks. Next, this paper proposes the user service specifications for the proposed congestion control method, and clarifies the algorithm to decide the optimal size of required resource to be reduced, based on the load offered to the system. It is demonstrated by simulation evaluations that the proposed method can handle more requests compared with the conventional methods and relieve the congestion. Then, this paper proposes to enhance the proposed method, so as to enable the fair resource allocation among users in congested situation.


Proposed optimal LSP selection method in MPLS networks

Abstract: Multi-Protocol Label Switching (MPLS) had been deployed by many data networking service providers, including the next-generation mobile backhaul networks, because of its undeniable potential in terms of virtual private network (VPN) management, traffic engineering, etc. In MPLS networks, IP packets are transmitted along a Label Switched Path (LSP) established between edge nodes. To improve the efficiency of resource use in MPLS networks, it is essential to utilize the LSPs efficiently. This paper proposes a method of selecting the optimal LSP pair from among multiple LSP pairs which are established between the same pair of edge nodes, on the assumption that both the upward and downward LSPs are established as a pair (both-way operation). It is supposed that both upward and downward bandwidths are allocated simultaneously in the selected LSP pair for each service request. It is demonstrated by simulation evaluations that the proposal method could reduce the total amount of the bandwidth required by up to 15% compared with the conventional selection method. The proposed method can also reuse the know-how and management tools in many existing networks which are based on both-way operation.


The Exponential Mechanism for Social Welfare: Private, Truthful, and Nearly Optimal

Abstract: In this paper we show that for any mechanism design problem with the objective of maximizing social welfare, the exponential mechanism can be implemented as a truthful mechanism while still preserving differential privacy. Our instantiation of the exponential mechanism can be interpreted as a generalization of the VCG mechanism in the sense that the VCG mechanism is the extreme case when the privacy parameter goes to infinity. To our knowledge, this is the first general tool for designing mechanisms that are both truthful and differentially private.


Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback

Abstract: Albeit, the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world applications, it is much less researched than the explicit feedback case. State-of-the-art algorithms that are efficient on the explicit case cannot be straightforwardly transformed to the implicit case if scalability should be maintained. There are few if any implicit feedback benchmark datasets, therefore new ideas are usually experimented on explicit benchmarks. In this paper, we propose a generic context-aware implicit feedback recommender algorithm, coined iTALS. iTALS apply a fast, ALS-based tensor factorization learning method that scales linearly with the number of non-zero elements in the tensor. The method also allows us to incorporate diverse context information into the model while maintaining its computational efficiency. In particular, we present two such context-aware implementation variants of iTALS. The first incorporates seasonality and enables to distinguish user behavior in different time intervals. The other views the user history as sequential information and has the ability to recognize usage pattern typical to certain group of items, e.g. to automatically tell apart product types or categories that are typically purchased repetitively (collectibles, grocery goods) or once (household appliances). Experiments performed on three implicit datasets (two proprietary ones and an implicit variant of the Netflix dataset) show that by integrating context-aware information with our factorization framework into the state-of-the-art implicit recommender algorithm the recommendation quality improves significantly.


Mouse Simulation Using Two Coloured Tapes

Abstract: In this paper, we present a novel approach for Human Computer Interaction (HCI) where, we control cursor movement using a real-time camera. Current methods involve changing mouse parts such as adding more buttons or changing the position of the tracking ball. Instead, our method is to use a camera and computer vision technology, such as image segmentation and gesture recognition, to control mouse tasks (left and right clicking, double-clicking, and scrolling) and we show how it can perform everything as current mouse devices can. The software will be developed in JAVA language. Recognition and pose estimation in this system are user independent and robust as we will be using colour tapes on our finger to perform actions. The software can be used as an intuitive input interface to applications that require multi-dimensional control e.g. computer games etc.


A Sliding Mode Control for a Sensorless Tracker: Application on a Photovoltaic System

Abstract: The photovoltaic sun tracker allows us to increase the energy production. The sun tracker considered in this study has two degrees of freedom (2-DOF) and especially specified by the lack of sensors. In this way, the tracker will have as a set point the sun position at every second during the day for a period of five years. After sunset, the tracker goes back to the initial position (which of sunrise). The sliding mode control (SMC) will be applied to ensure at best the tracking mechanism and, in another hand, the sliding mode observer will replace the velocity sensor which suffers from a lot of measurement disturbances. Experimental measurements show that this autonomic dual axis Sun Tracker increases the power production by over 40%.


Towards a Security Engineering Process Model for Electronic Business Processes

Abstract: Business process management (BPM) and accompanying systems aim at enabling enterprises to become adaptive. In spite of the dependency of enterprises on secure business processes, BPM languages and techniques provide only little support for security. Several complementary approaches have been proposed for security in the domain of BPM. Nevertheless, support for a systematic procedure for the development of secure electronic business processes is still missing. In this paper, we pinpoint the need for a security engineering process model in the domain of BPM and identify key requirements for such process model.


An Implementation of Intrusion Detection System Using Genetic Algorithm

Abstract: Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. So, the quest of betterment continues. In this progression, here we present an Intrusion Detection System (IDS), by applying genetic algorithm (GA) to efficiently detect various types of network intrusions. Parameters and evolution processes for GA are discussed in details and implemented. This approach uses evolution theory to information evolution in order to filter the traffic data and thus reduce the complexity. To implement and measure the performance of our system we used the KDD99 benchmark dataset and obtained reasonable detection rate.


An approximation algorithm for the link building problem

Abstract: In this work we consider the problem of maximizing the PageRank of a given target node in a graph by adding $k$ new links. We consider the case that the new links must point to the given target node (backlinks). Previous work shows that this problem has no fully polynomial time approximation schemes unless $P=NP$. We present a polynomial time algorithm yielding a PageRank value within a constant factor from the optimal. We also consider the naive algorithm where we choose backlinks from nodes with high PageRank values compared to the outdegree and show that the naive algorithm performs much worse on certain graphs compared to the constant factor approximation scheme.


Characteristics of Minimal Effective Programming Systems

Abstract: The Rogers semilattice of effective programming systems (epses) is the collection of all effective numberings of the partial computable functions ordered such that \theta\ is less than or equal to \psi\ whenever \theta-programs can be algorithmically translated into \psi-programs. Herein, it is shown that an eps \psi\ is minimal in this ordering if and only if, for each translation function t into \psi, there exists a computably enumerable equivalence relation (ceer) R such that (i) R is a subrelation of \psi's program equivalence relation, and (ii) R equates each \psi-program to some program in the range of t. It is also shown that there exists a minimal eps for which no single such R does the work for all such t. In fact, there exists a minimal eps \psi\ such that, for each ceer R, either R contradicts \psi's program equivalence relation, or there exists a translation function t into \psi\ such that the range of t fails to intersect infinitely many of R's equivalence classes.


Spectra: Robust Estimation of Distribution Functions in Networks

Abstract: Distributed aggregation allows the derivation of a given global aggregate property from many individual local values in nodes of an interconnected network system. Simple aggregates such as minima/maxima, counts, sums and averages have been thoroughly studied in the past and are important tools for distributed algorithms and network coordination. Nonetheless, this kind of aggregates may not be comprehensive enough to characterize biased data distributions or when in presence of outliers, making the case for richer estimates of the values on the network. This work presents Spectra, a distributed algorithm for the estimation of distribution functions over large scale networks. The estimate is available at all nodes and the technique depicts important properties, namely: robust when exposed to high levels of message loss, fast convergence speed and fine precision in the estimate. It can also dynamically cope with changes of the sampled local property, not requiring algorithm restarts, and is highly resilient to node churn. The proposed approach is experimentally evaluated and contrasted to a competing state of the art distribution aggregation technique.


An Intelligent Network Selection Strategy Based on MADM Methods in Heterogeneous Networks

Abstract: Providing service continuity to the end users with best quality is a very important issue in the next generation wireless communications. With the evolution of the mobile devices towards a multimode architecture and the coexistence of multitude of radio access technologies (RAT's), the users are able to benefit simultaneously from these RAT's. However, the major issue in heterogeneous wireless communications is how to choose the most suitable access network for mobile's user which can be used as long as possible for communication. To achieve this issue, this paper proposes an intelligent network selection strategy which combines two multi attribute decision making (MADM) methods such as analytic network process (ANP) and the technique for order preference by similarity to an ideal solution (TOPSIS) method. The ANP method is used to find the differentiate weights of available networks by considering each criterion and the TOPSIS method is applied to rank the alternatives. Our new strategy for network selection can dealing with the limitations of MADM methods which are the ranking abnormality and the ping-ponf effect.


Refinement of Strategy and Technology Domains STOPE View on ISO 27001

Abstract: It is imperative for organizations to us Information Security Management System (ISMS) to effectively manage their information assets. ISMS starts with a set of policies that dictate the usage computer resources. It starts with the "21 essential security controls" of ISO 27001, which give the basic standard requirements of information security management. Our research is concerned with the assessment of the application of these controls to organizations. STOPE (Strategy, Technology Organization, People and Environment) methodologies were used to integrated domains as a framework for this assessment. The controls are mapped on these domains and subsequently refined into "246 simple and easily comprehended elements".


Continuous Markov Random Fields for Robust Stereo Estimation

Abstract: In this paper we present a novel slanted-plane MRF model which reasons jointly about occlusion boundaries as well as depth. We formulate the problem as the one of inference in a hybrid MRF composed of both continuous (i.e., slanted 3D planes) and discrete (i.e., occlusion boundaries) random variables. This allows us to define potentials encoding the ownership of the pixels that compose the boundary between segments, as well as potentials encoding which junctions are physically possible. Our approach outperforms the state-of-the-art on Middlebury high resolution imagery as well as in the more challenging KITTI dataset, while being more efficient than existing slanted plane MRF-based methods, taking on average 2 minutes to perform inference on high resolution imagery.


An Effective Information Retrieval for Ambiguous Query

Abstract: Search engine returns thousands of web pages for a single user query, in which most of them are not relevant. In this context, effective information retrieval from the expanding web is a challenging task, in particular, if the query is ambiguous. The major question arises here is that how to get the relevant pages for an ambiguous query. We propose an approach for the effective result of an ambiguous query by forming community vector based on association concept of data minning using vector space model and the freedictionary. We develop clusters by computing the similarity between community vectors and document vectors formed from the extracted web pages by the search engine. We use Gensim package to implement the algorithm because of its simplicity and robust nature. Analysis shows that our approach is an effective way to form clusters for an ambiguous query.


An integrated ranking algorithm for efficient information computing in social networks

Abstract: Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.


A single-exponential FPT algorithm for the $K_4$-minor cover problem

Abstract: Given an input graph G and an integer k, the parameterized K_4-minor cover problem asks whether there is a set S of at most k vertices whose deletion results in a K_4-minor-free graph, or equivalently in a graph of treewidth at most 2. This problem is inspired by two well-studied parameterized vertex deletion problems, Vertex Cover and Feedback Vertex Set, which can also be expressed as Treewidth-t Vertex Deletion problems: t=0 for Vertex Cover and t=1 for Feedback Vertex Set. While a single-exponential FPT algorithm has been known for a long time for \textsc{Vertex Cover}, such an algorithm for Feedback Vertex Set was devised comparatively recently. While it is known to be unlikely that Treewidth-t Vertex Deletion can be solved in time c^{o(k)}.n^{O(1)}, it was open whether the K_4-minor cover problem could be solved in single-exponential FPT time, i.e. in c^k.n^{O(1)} time. This paper answers this question in the affirmative.


Intra-bodyhybrid communication scheme for healthcare systems

Abstract: Intra-body communication (IBC) is a type of Body Area Network (BAN)that utilizes human body as the medium for data transmission. Thelow power requirements of intra-body communication (IBC) as compared to near field electromagnetic waves showed that it can be a suitable solution for Medical Body Area Networks (MBANs) in a mobile health care system.In this paper, we investigate the transmission characteristics of the human body as a conductor of signals by considering different data transmission rates of multi-point to point network in order to reduce overall power consumption of the BAN.Furthermore, we utilize IBC and propose a new scheme to combines Slotted ALOHA, TDMA, and Reservation ALOHA together to increase the throughput and decrease the delay. By using our new hybrid scheme with the movable boundary designed for health status monitoring, we are able to increase the efficiency of data transmission by prioritizing the more critical data from the sensors.


Web service selection based on ranking of qos using associative classification

Abstract: With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user's preferences. The similarity measure (outputs-inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user's QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters' non-functional requirements.


Online multipath convolutional coding for real-time transmission

Abstract: Most of multipath multimedia streaming proposals use Forward Error Correction (FEC) approach to protect from packet losses. However, FEC does not sustain well burst of losses even when packets from a given FEC block are spread over multiple paths. In this article, we propose an online multipath convolutional coding for real-time multipath streaming based on an on-the-fly coding scheme called Tetrys. We evaluate the benefits brought out by this coding scheme inside an existing FEC multipath load splitting proposal known as Encoded Multipath Streaming (EMS). We demonstrate that Tetrys consistently outperforms FEC in both uniform and burst losses with EMS scheme. We also propose a modification of the standard EMS algorithm that greatly improves the performance in terms of packet recovery. Finally, we analyze different spreading policies of the Tetrys redundancy traffic between available paths and observe that the longer propagation delay path should be preferably used to carry repair packets.


The Transitivity of Trust Problem in the Interaction of Android Applications

Abstract: Mobile phones have developed into complex platforms with large numbers of installed applications and a wide range of sensitive data. Application security policies limit the permissions of each installed application. As applications may interact, restricting single applications may create a false sense of security for the end users while data may still leave the mobile phone through other applications. Instead, the information flow needs to be policed for the composite system of applications in a transparent and usable manner. In this paper, we propose to employ static analysis based on the software architecture and focused data flow analysis to scalably detect information flows between components. Specifically, we aim to reveal transitivity of trust problems in multi-component mobile platforms. We demonstrate the feasibility of our approach with Android applications, although the generalization of the analysis to similar composition-based architectures, such as Service-oriented Architecture, can also be explored in the future.


Efficient computational noise in GLSL

Abstract: We present GLSL implementations of Perlin noise and Perlin simplex noise that run fast enough for practical consideration on current generation GPU hardware. The key benefits are that the functions are purely computational, i.e. they use neither textures nor lookup tables, and that they are implemented in GLSL version 1.20, which means they are compatible with all current GLSL-capable platforms, including OpenGL ES 2.0 and WebGL 1.0. Their performance is on par with previously presented GPU implementations of noise, they are very convenient to use, and they scale well with increasing parallelism in present and upcoming GPU architectures.


Learning Fuzzy {\beta}-Certain and {\beta}-Possible rules from incomplete quantitative data by rough sets

Abstract: The rough-set theory proposed by Pawlak, has been widely used in dealing with data classification problems. The original rough-set model is, however, quite sensitive to noisy data. Tzung thus proposed deals with the problem of producing a set of fuzzy certain and fuzzy possible rules from quantitative data with a predefined tolerance degree of uncertainty and misclassification. This model allowed, which combines the variable precision rough-set model and the fuzzy set theory, is thus proposed to solve this problem. This paper thus deals with the problem of producing a set of fuzzy certain and fuzzy possible rules from incomplete quantitative data with a predefined tolerance degree of uncertainty and misclassification. A new method, incomplete quantitative data for rough-set model and the fuzzy set theory, is thus proposed to solve this problem. It first transforms each quantitative value into a fuzzy set of linguistic terms using membership functions and then finding incomplete quantitative data with lower and the fuzzy upper approximations. It second calculates the fuzzy {\beta}-lower and the fuzzy {\beta}-upper approximations. The certain and possible rules are then generated based on these fuzzy approximations. These rules can then be used to classify unknown objects.


Performance evaluation of beacon enabled IEEE 802.15.4 under NS2

Abstract: The increasing demand for real-time applications has made the Quality of Service (Qos) support for wireless sensor networks (WSN) a fairly new research framework. In this paper, we propose an extended model of the Beacon enabled IEEE 802.15.4 including the Guaranteed Time Slot GTS allocation mechanism in the aim to analyze and evaluate network performances. Series of extensive simulations were performed to analyze the impact of the Beacon Order BO and the Superframe Order SO on the network performance based on commonly known metrics. In particular, we examine data packet delivery performance and the throughput for different duty cycle rates. Also, we analyze the impact of the number of nodes on collision probability. Thus, for high number of nodes, collision becomes higher and the reachability begins to decline slightly. We discuss and compare simulation results conducted under various parameter settings to the IEEE 802.11 network.


Reliable Resource Selection in Grid Environment

Abstract: The primary concern in area of computational grid is security and resources. Most of the existing grids address this problem by authenticating the users, hosts and their interactions in an appropriate manner. A secured system is compulsory for the efficient utilization of grid services. The high degree of strangeness has been identified as the problem factors in the secured selection of grid. Without the assurance of a higher degree of trust relationship, competent resource selection and utilization cannot be achieved. In this paper we proposed an approach which is providing reliability and reputation aware security for resource selection in grid environment. In this approach, the self-protection capability and reputation weightage is utilized to obtain the Reliability Factor (RF) value. Therefore jobs are allocated to the resources that posses higher RF values. Extensive experimental evaluation shows that as higher trust and reliable nodes are selected the chances of failure decreased drastically.


Extracting Geospatial Preferences Using Relational Neighbors

Abstract: With the increasing popularity of location-based social media applications and devices that automatically tag generated content with locations, large repositories of collaborative geo-referenced data are appearing on-line. Efficiently extracting user preferences from these data to determine what information to recommend is challenging because of the sheer volume of data as well as the frequency of updates. Traditional recommender systems focus on the interplay between users and items, but ignore contextual parameters such as location. In this paper we take a geospatial approach to determine locational preferences and similarities between users. We propose to capture the geographic context of user preferences for items using a relational graph, through which we are able to derive many new and state-of-the-art recommendation algorithms, including combinations of them, requiring changes only in the definition of the edge weights. Furthermore, we discuss several solutions for cold-start scenarios. Finally, we conduct experiments using two real-world datasets and provide empirical evidence that many of the proposed algorithms outperform existing location-aware recommender algorithms.


Ensuring QOS Guarantees in a Hybrid OCS/OBS Network

Abstract: The bursting aggregation assembly in edge nodes is one of the key technologies in OBS (Optical Burst Switching) network, which has a direct impact on flow characteristics and packet loss rate. An optical burst assembly technique supporting QoS is presented through this paper, which can automatically adjust the threshold along with the increasing and decreasing volume of business, reduce the operational burst, and generate corresponding BDP (Burst Data Packet) and BCP (Burst Control Packet). In addition to the burst aggregation technique a packet recovery technique by restoration method is also described. The data packet loss due to the physical optical link failure is not currently included in the QoS descriptions. This link failure is also a severe problem which reduces the data throughput of the transmitter node. A mechanism for data recovery from this link failure is vital for guaranteeing the QoS demanded by each user. So this paper will also discusses a specific protocol for reducing the packet loss by utilizing the features of both optical circuit switching (OCS) and Optical Burst switching (OBS) techniques.


Towards Quranic reader controlled by speech

Abstract: In this paper we describe the process of designing a task-oriented continuous speech recognition system for Arabic, based on CMU Sphinx4, to be used in the voice interface of Quranic reader. The concept of the Quranic reader controlled by speech is presented, the collection of the corpus and creation of acoustic model are described in detail taking into account a specificities of Arabic language and the desired application.


A Complexity Preserving Transformation from Jinja Bytecode to Rewrite Systems

Abstract: We revisit known transformations from Jinja bytecode to rewrite systems from the viewpoint of runtime complexity. Suitably generalising the constructions proposed in the literature, we define an alternative representation of Jinja bytecode (JBC) executions as "computation graphs" from which we obtain a novel representation of JBC executions as "constrained rewrite systems". We prove non-termination and complexity preservation of the transformation. We restrict to well-formed JBC programs that only make use of non-recursive methods and expect tree-shaped objects as input. Our approach allows for simplified correctness proofs and provides a framework for the combination of the computation graph method with standard techniques from static program analysis like for example "reachability analysis".


Development of knowledge Base Expert System for Natural treatment of Diabetes disease

Abstract: The development of expert system for treatment of Diabetes disease by using natural methods is new information technology derived from Artificial Intelligent research using ESTA (Expert System Text Animation) System. The proposed expert system contains knowledge about various methods of natural treatment methods (Massage, Herbal/Proper Nutrition, Acupuncture, Gems) for Diabetes diseases of Human Beings. The system is developed in the ESTA (Expert System shell for Text Animation) which is Visual Prolog 7.3 Application. The knowledge for the said system will be acquired from domain experts, texts and other related sources.


A new approach of designing Multi-Agent Systems

Abstract: Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist analyzing, conception and development or implementation phases of multi-agent systems, we've tried to present a practical application of a generic and scalable method of a MAS with a component-oriented architecture and agent-based approach that allows MDA to generate source code from a given model. We've designed on AUML the class diagrams as a class meta-model of different agents of a MAS. Then we generated the source code of the models developed using an open source tool called AndroMDA. This agent-based and evolutive approach enhances the modularity and genericity developments and promotes their reusability in future developments. This property distinguishes our design methodology of existing methodologies in that it is constrained by any particular agent-based model while providing a library of generic models


Cloud Computing Through Mobile-Learning

Abstract: Cloud computing is the new technology that has various advantages and it is an adoptable technology in this present scenario. The main advantage of the cloud computing is that this technology reduces the cost effectiveness for the implementation of the Hardware, software and License for all. This is the better peak time to analyze the cloud and its implementation and better use it for the development of the quality and low cost education for all over the world. In this paper, we discuss how to influence on cloud computing and influence on this technology to take education to a wider mass of students over the country. We believe cloud computing will surely improve the current system of education and improve quality at an affordable cost.


An Intelligent Location Management approaches in GSM Mobile Network

Abstract: Location management refers to the problem of updating and searching the current location of mobile nodes in a wireless network. To make it efficient, the sum of update costs of location database must be minimized. Previous work relying on fixed location databases is unable to fully exploit the knowledge of user mobility patterns in the system so as to achieve this minimization. The study presents an intelligent location management approach which has interacts between intelligent information system and knowledge-base technologies, so we can dynamically change the user patterns and reduce the transition between the VLR and HLR. The study provides algorithms are ability to handle location registration and call delivery


An Intelligent Software Workflow Process Design for Location Management on Mobile Devices

Abstract: Advances in the technologies of networking, wireless communication and trimness of computers lead to the rapid development in mobile communication infrastructure, and have drastically changed information processing on mobile devices. Users carrying portable devices can freely move around, while still connected to the network. This provides flexibility in accessing information anywhere at any time. For improving more flexibility on mobile device, the new challenges in designing software systems for mobile networks include location and mobility management, channel allocation, power saving and security. In this paper, we are proposing intelligent software tool for software design on mobile devices to fulfill the new challenges on mobile location and mobility management. In this study, the proposed Business Process Redesign (BPR) concept is aims at an extension of the capabilities of an existing, widely used process modeling tool in industry with 'Intelligent' capabilities to suggest favorable alternatives to an existing software workflow design for improving flexibilities on mobile devices.


Improving Seek Time for Column Store Using MMH Algorithm

Abstract: Hash based search has, proven excellence on large data warehouses stored in column store. Data distribution has significant impact on hash based search. To reduce impact of data distribution, we have proposed Memory Managed Hash (MMH) algorithm that uses shift XOR group for Queries and Transactions in column store. Our experiments show that MMH improves read and write throughput by 22% for TPC-H distribution.


Handsets Malware Threats and Facing Techniques

Abstract: Nowadays, mobile handsets combine the functionality of mobile phones and PDAs. Unfortunately, mobile handsets development process has been driven by market demand, focusing on new features and neglecting security. So, it is imperative to study the existing challenges that facing the mobile handsets threat containment process, and the different techniques and methodologies that used to face those challenges and contain the mobile handsets malwares. This paper also presents a new approach to group the different malware containment systems according to their typologies.


Design and Analysis of a Novel Digital Image Encryption Scheme

Abstract: In this paper, a new image encryption scheme using a secret key of 144-bits is proposed. In the substitution process of the scheme, image is divided into blocks and subsequently into color components. Each color component is modified by performing bitwise operation which depends on secret key as well as a few most significant bits of its previous and next color component. Three rounds are taken to complete substitution process. To make cipher more robust, a feedback mechanism is also applied by modifying used secret key after encrypting each block. Further, resultant image is partitioned into several key based dynamic sub-images. Each sub-image passes through the scrambling process where pixels of sub-image are reshuffled within itself by using a generated magic square matrix. Five rounds are taken for scrambling process. The propose scheme is simple, fast and sensitive to the secret key. Due to high order of substitution and permutation, common attacks like linear and differential cryptanalysis are infeasible. The experimental results show that the proposed encryption technique is efficient and has high security features.


Vision-based Human Gender Recognition: A Survey

Abstract: Gender is an important demographic attribute of people. This paper provides a survey of human gender recognition in computer vision. A review of approaches exploiting information from face and whole body (either from a still image or gait sequence) is presented. We highlight the challenges faced and survey the representative methods of these approaches. Based on the results, good performance have been achieved for datasets captured under controlled environments, but there is still much work that can be done to improve the robustness of gender recognition under real-life environments.


Cross Layer QoS Support Architecture with Integrated CAC and Scheduling Algorithms for WiMAX BWA Networks

Abstract: In this paper, a new technique for cross layer design, based on present Eb/N0 (bit energy per noise density) ratio of the connections and target values of the Quality of Service (QoS) information parameters from MAC layer, is proposed to dynamically select the Modulation and Coding Scheme (MCS) at the PHY layer for WiMAX Broadband Wireless Access (BWA) networks. The QoS information parameter includes New Connection Blocking Probability (NCBP), Hand off Connection Dropping Probability (HCDP) and Connection Outage Probability (COP). In addition, a Signal to Interference plus Noise Ratio (SINR) based Call Admission Control (CAC) algorithm and Queue based Scheduling algorithm are integrated for the cross layer design. An analytical model using the Continuous Time Markov Chain (CTMC) is developed for performance evaluation of the algorithms under various MCS. The effect of Eb/No is observed for QoS information parameters in order to determine its optimum range. Simulation results show that the integrated CAC and packet Scheduling model maximizes the bandwidth utilization and fair allocation of the system resources for all types of MCS and guarantees the QoS to the connections.


Discrimination between Arabic and Latin from bilingual documents

Abstract: 2011 International Conference on Communications, Computing and Control Applications (CCCA)


Algorithmic Applications of Baur-Strassen's Theorem: Shortest Cycles, Diameter and Matchings

Abstract: Consider a directed or an undirected graph with integral edge weights from the set [-W, W], that does not contain negative weight cycles. In this paper, we introduce a general framework for solving problems on such graphs using matrix multiplication. The framework is based on the usage of Baur-Strassen's theorem and of Strojohann's determinant algorithm. It allows us to give new and simple solutions to the following problems: * Finding Shortest Cycles -- We give a simple \tilde{O}(Wn^{\omega}) time algorithm for finding shortest cycles in undirected and directed graphs. For directed graphs (and undirected graphs with non-negative weights) this matches the time bounds obtained in 2011 by Roditty and Vassilevska-Williams. On the other hand, no algorithm working in \tilde{O}(Wn^{\omega}) time was previously known for undirected graphs with negative weights. Furthermore our algorithm for a given directed or undirected graph detects whether it contains a negative weight cycle within the same running time. * Computing Diameter and Radius -- We give a simple \tilde{O}(Wn^{\omega}) time algorithm for computing a diameter and radius of an undirected or directed graphs. To the best of our knowledge no algorithm with this running time was known for undirected graphs with negative weights. * Finding Minimum Weight Perfect Matchings -- We present an \tilde{O}(Wn^{\omega}) time algorithm for finding minimum weight perfect matchings in undirected graphs. This resolves an open problem posted by Sankowski in 2006, who presented such an algorithm but only in the case of bipartite graphs. In order to solve minimum weight perfect matching problem we develop a novel combinatorial interpretation of the dual solution which sheds new light on this problem. Such a combinatorial interpretation was not know previously, and is of independent interest.


Stable marriage and roommate problems with individual-based stability

Abstract: Research regarding the stable marriage and roommate problem has a long and distinguished history in mathematics, computer science and economics. Stability in this context is predominantly core stability or one of its variants in which each deviation is by a group of players. There has been little focus in matching theory on stability concepts such as Nash stability and individual stability in which the deviation is by a single player. Such stability concepts are suitable especially when trust for the other party is limited, complex coordination is not feasible, or when only unmatched agents can be approached. Furthermore, weaker stability notions such as individual stability may in principle circumvent the negative existence and computational complexity results in matching theory. We characterize the computational complexity of checking the existence and computing individual-based stable matchings for the marriage and roommate settings. One of our key computational results for the stable marriage setting also carries over to different classes of hedonic games for which individual-based stability has already been of much interest.


Image segmentation by adaptive distance based on EM algorithm

Abstract: This paper introduces a Bayesian image segmentation algorithm based on finite mixtures. An EM algorithm is developed to estimate parameters of the Gaussian mixtures. The finite mixture is a flexible and powerful probabilistic modeling tool. It can be used to provide a model-based clustering in the field of pattern recognition. However, the application of finite mixtures to image segmentation presents some difficulties; especially it's sensible to noise. In this paper we propose a variant of this method which aims to resolve this problem. Our approach proceeds by the characterization of pixels by two features: the first one describes the intrinsic properties of the pixel and the second characterizes the neighborhood of pixel. Then the classification is made on the base on adaptive distance which privileges the one or the other features according to the spatial position of the pixel in the image. The obtained results have shown a significant improvement of our approach compared to the standard version of EM algorithm.


New approach using Bayesian Network to improve content based image classification systems

Abstract: This paper proposes a new approach based on augmented naive Bayes for image classification. Initially, each image is cutting in a whole of blocks. For each block, we compute a vector of descriptors. Then, we propose to carry out a classification of the vectors of descriptors to build a vector of labels for each image. Finally, we propose three variants of Bayesian Networks such as Naive Bayesian Network (NB), Tree Augmented Naive Bayes (TAN) and Forest Augmented Naive Bayes (FAN) to classify the image using the vector of labels. The results showed a marked improvement over the FAN, NB and TAN.


Automatic liver segmentation method in CT images

Abstract: The aim of this work is to develop a method for automatic segmentation of the liver based on a priori knowledge of the image, such as location and shape of the liver.


Characterization of Dynamic Bayesian Network

Abstract: In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and Learning concepts and algorithms. Then we will present different levels and methods of creating DBNs as well as approaches of incorporating temporal dimension in static Bayesian network.