Anomaly Detection with Score functions based on Nearest Neighbor Graphs

Abstract: We propose a novel non-parametric adaptive anomaly detection algorithm for high dimensional data based on score functions derived from nearest neighbor graphs on $n$-point nominal data. Anomalies are declared whenever the score of a test sample falls below $\alpha$, which is supposed to be the desired false alarm level. The resulting anomaly detector is shown to be asymptotically optimal in that it is uniformly most powerful for the specified false alarm level, $\alpha$, for the case when the anomaly density is a mixture of the nominal and a known density. Our algorithm is computationally efficient, being linear in dimension and quadratic in data size. It does not require choosing complicated tuning parameters or function approximation classes and it can adapt to local structure such as local change in dimensionality. We demonstrate the algorithm on both artificial and real data sets in high dimensional feature spaces.


Maximum Matchings in Random Bipartite Graphs and the Space Utilization of Cuckoo Hashtables

Abstract: We study the the following question in Random Graphs. We are given two disjoint sets $L,R$ with $|L|=n=\alpha m$ and $|R|=m$. We construct a random graph $G$ by allowing each $x\in L$ to choose $d$ random neighbours in $R$. The question discussed is as to the size $\mu(G)$ of the largest matching in $G$. When considered in the context of Cuckoo Hashing, one key question is as to when is $\mu(G)=n$ whp? We answer this question exactly when $d$ is at least four. We also establish a precise threshold for when Phase 1 of the Karp-Sipser Greedy matching algorithm suffices to compute a maximum matching whp.


Forced Evolution in Silico by Artificial Transposons and their Genetic Operators: The John Muir Ant Problem

Abstract: Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. We believe that a vital direction in this field must be algorithms that model the activity of genomic parasites, such as transposons, in biological evolution. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. We define these artificial transposons as a fragment of an ant's code that possesses properties that cause it to stand apart from the rest. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts.


On the characterization of the regions of feasible trajectories in the workspace of parallel manipulators

Abstract: It was shown recently that parallel manipulators with several inverse kinematic solutions have the ability to avoid parallel singularities [Chablat 1998a] and self-collisions [Chablat 1998b] by choosing appropriate joint configurations for the legs. In effect, depending on the joint configurations of the legs, a given configuration of the end-effector may or may not be free of singularity and collision. Characterization of the collision/singularity-free workspace is useful but may be insufficient since two configurations can be accessible without collisions nor singularities but it may not exist a feasible trajectory between them. The goal of this paper is to define the maximal regions of the workspace where it is possible to execute trajectories. Twodifferent families of regions are defined : 1. those regions where the end-effector can move between any set of points, and 2. the regions where any continuous path can be tracked. These regions are characterized from the notion of aspects and free-aspects recently defined for parallel manipulators [Chablat 1998b]. The construction of these regions is achieved by enrichment techniques and using an extension of the octree structures to spaces of dimension greater than three. Illustrative examples show the interest of this study to the optimization of trajectories and the design of parallel manipulators.


Instruction sequence processing operators

Abstract: Instruction sequence is a key concept in practice, but it has as yet not come prominently into the picture in theoretical circles. This paper concerns instruction sequences, the behaviours produced by them under execution, the interaction between these behaviours and components of the execution environment, and two issues relating to computability theory. Positioning Turing's result regarding the undecidability of the halting problem as a result about programs rather than machines, and taking instruction sequences as programs, we analyse the autosolvability requirement that a program of a certain kind must solve the halting problem for all programs of that kind. We present novel results concerning this autosolvability requirement. The analysis is streamlined by using the notion of a functional unit, which is an abstract state-based model of a machine. In the case where the behaviours exhibited by a component of an execution environment can be viewed as the behaviours of a machine in its different states, the behaviours concerned are completely determined by a functional unit. The above-mentioned analysis involves functional units whose possible states represent the possible contents of the tapes of Turing machines with a particular tape alphabet. We also investigate functional units whose possible states are the natural numbers. This investigation yields a novel computability result, viz. the existence of a universal computable functional unit for natural numbers.


An Improved Implementation of Grain

Abstract: A common approach to protect confidential information is to use a stream cipher which combines plain text bits with a pseudo-random bit sequence. Among the existing stream ciphers, Non-Linear Feedback Shift Register (NLFSR)-based ones provide the best trade-off between cryptographic security and hardware efficiency. In this paper, we show how to further improve the hardware efficiency of Grain stream cipher. By transforming the NLFSR of Grain from its original Fibonacci configuration to the Galois configuration and by introducing a clock division block, we double the throughput of the 80 and 128-bit key 1bit/cycle architectures of Grain with no area penalty.


Vector Bin Packing with Multiple-Choice

Abstract: We consider a variant of bin packing called multiple-choice vector bin packing. In this problem we are given a set of items, where each item can be selected in one of several $D$-dimensional incarnations. We are also given $T$ bin types, each with its own cost and $D$-dimensional size. Our goal is to pack the items in a set of bins of minimum overall cost. The problem is motivated by scheduling in networks with guaranteed quality of service (QoS), but due to its general formulation it has many other applications as well. We present an approximation algorithm that is guaranteed to produce a solution whose cost is about $\ln D$ times the optimum. For the running time to be polynomial we require $D=O(1)$ and $T=O(\log n)$. This extends previous results for vector bin packing, in which each item has a single incarnation and there is only one bin type. To obtain our result we also present a PTAS for the multiple-choice version of multidimensional knapsack, where we are given only one bin and the goal is to pack a maximum weight set of (incarnations of) items in that bin.


Magnetworks: how mobility impacts the design of Mobile Networks

Abstract: In this paper we study the optimal placement and optimal number of active relay nodes through the traffic density in mobile sensor ad-hoc networks. We consider a setting in which a set of mobile sensor sources is creating data and a set of mobile sensor destinations receiving that data. We make the assumption that the network is massively dense, i.e., there are so many sources, destinations, and relay nodes, that it is best to describe the network in terms of macroscopic parameters, such as their spatial density, rather than in terms of microscopic parameters, such as their individual placements. We focus on a particular physical layer model that is characterized by the following assumptions: i) the nodes must only transport the data from the sources to the destinations, and do not need to sense the data at the sources, or deliver them at the destinations once the data arrive at their physical locations, and ii) the nodes have limited bandwidth available to them, but they use it optimally to locally achieve the network capacity. In this setting, the optimal distribution of nodes induces a traffic density that resembles the electric displacement that will be created if we substitute the sources and destinations with positive and negative charges respectively. The analogy between the two settings is very tight and have a direct interpretation in wireless sensor networks.


Word Sense Disambiguation Using English-Spanish Aligned Phrases over Comparable Corpora

Abstract: In this paper we describe a WSD experiment based on bilingual English-Spanish comparable corpora in which individual noun phrases have been identified and aligned with their respective counterparts in the other language. The evaluation of the experiment has been carried out against SemCor. We show that, with the alignment algorithm employed, potential precision is high (74.3%), however the coverage of the method is low (2.7%), due to alignments being far less frequent than we expected. Contrary to our intuition, precision does not rise consistently with the number of alignments. The coverage is low due to several factors; there are important domain differences, and English and Spanish are too close languages for this approach to be able to discriminate efficiently between senses, rendering it unsuitable for WSD, although the method may prove more productive in machine translation.


Approximate Privacy: Foundations and Quantification

Abstract: Increasing use of computers and networks in business, government, recreation, and almost all aspects of daily life has led to a proliferation of online sensitive data about individuals and organizations. Consequently, concern about the privacy of these data has become a top priority, particularly those data that are created and used in electronic commerce. There have been many formulations of privacy and, unfortunately, many negative results about the feasibility of maintaining privacy of sensitive data in realistic networked environments. We formulate communication-complexity-based definitions, both worst-case and average-case, of a problem's privacy-approximation ratio. We use our definitions to investigate the extent to which approximate privacy is achievable in two standard problems: the second-price Vickrey auction and the millionaires problem of Yao. For both the second-price Vickrey auction and the millionaires problem, we show that not only is perfect privacy impossible or infeasibly costly to achieve, but even close approximations of perfect privacy suffer from the same lower bounds. By contrast, we show that, if the values of the parties are drawn uniformly at random from {0,...,2^k-1}, then, for both problems, simple and natural communication protocols have privacy-approximation ratios that are linear in k (i.e., logarithmic in the size of the space of possible inputs). We conjecture that this improved privacy-approximation ratio is achievable for any probability distribution.


Exact algorithms for OWA-optimization in multiobjective spanning tree problems

Abstract: This paper deals with the multiobjective version of the optimal spanning tree problem. More precisely, we are interested in determining the optimal spanning tree according to an Ordered Weighted Average (OWA) of its objective values. We first show that the problem is weakly NP-hard. In the case where the weights of the OWA are strictly decreasing, we then propose a mixed integer programming formulation, and provide dedicated optimality conditions yielding an important reduction of the size of the program. Next, we present two bounds that can be used to prune subspaces of solutions either in a shaving phase or in a branch and bound procedure. The validity of these bounds does not depend on specific properties of the weights (apart from non-negativity). All these exact resolution algorithms are compared on the basis of numerical experiments, according to their respective validity scopes.


Quantifying pervasive authentication: the case of the Hancke-Kuhn protocol

Abstract: As mobile devices pervade physical space, the familiar authentication patterns are becoming insufficient: besides entity authentication, many applications require, e.g., location authentication. Many interesting protocols have been proposed and implemented to provide such strengthened forms of authentication, but there are very few proofs that such protocols satisfy the required security properties. The logical formalisms, devised for reasoning about security protocols on standard computer networks, turn out to be difficult to adapt for reasoning about hybrid protocols, used in pervasive and heterogenous networks. <p> We refine the Dolev-Yao-style algebraic method for protocol analysis by a probabilistic model of guessing, needed to analyze protocols that mix weak cryptography with physical properties of nonstandard communication channels. Applying this model, we provide a precise security proof for a proximity authentication protocol, due to Hancke and Kuhn, that uses a subtle form of probabilistic reasoning to achieve its goals.


Calibration of 3-d.o.f. Translational Parallel Manipulators Using Leg Observations

Abstract: The paper proposes a novel approach for the geometrical model calibration of quasi-isotropic parallel kinematic mechanisms of the Orthoglide family. It is based on the observations of the manipulator leg parallelism during motions between the specific test postures and employs a low-cost measuring system composed of standard comparator indicators attached to the universal magnetic stands. They are sequentially used for measuring the deviation of the relevant leg location while the manipulator moves the TCP along the Cartesian axes. Using the measured differences, the developed algorithm estimates the joint offsets and the leg lengths that are treated as the most essential parameters. Validity of the proposed calibration technique is confirmed by the experimental results.


Distributed Abstract Optimization via Constraints Consensus: Theory and Applications

Abstract: Distributed abstract programs are a novel class of distributed optimization problems where (i) the number of variables is much smaller than the number of constraints and (ii) each constraint is associated to a network node. Abstract optimization programs are a generalization of linear programs that captures numerous geometric optimization problems. We propose novel constraints consensus algorithms for distributed abstract programs: as each node iteratively identifies locally active constraints and exchanges them with its neighbors, the network computes the active constraints determining the global optimum. The proposed algorithms are appropriate for networks with weak time-dependent connectivity requirements and tight memory constraints. We show how suitable target localization and formation control problems can be tackled via constraints consensus.


Undecidability of performance equivalence of Petri nets

Abstract: We investigate bisimulation equivalence on Petri nets under durational semantics. Our motivation was to verify the conjecture that in durational setting, the bisimulation equivalence checking problem becomes more tractable than in ordinary setting (which is the case, e.g., over communication-free nets). We disprove this conjecture in three of four proposed variants of durational semantics. The fourth variant remains an intriguing open problem.


From Single-thread to Multithreaded: An Efficient Static Analysis Algorithm

Abstract: A great variety of static analyses that compute safety properties of single-thread programs have now been developed. This paper presents a systematic method to extend a class of such static analyses, so that they handle programs with multiple POSIX-style threads. Starting from a pragmatic operational semantics, we build a denotational semantics that expresses reasoning a la assume-guarantee. The final algorithm is then derived by abstract interpretation. It analyses each thread in turn, propagating interferences between threads, in addition to other semantic information. The combinatorial explosion, ensued from the explicit consideration of all interleavings, is thus avoided. The worst case complexity is only increased by a factor n compared to the single-thread case, where n is the number of instructions in the program. We have implemented prototype tools, demonstrating the practicality of the approach.


On Pebble Automata for Data Languages with Decidable Emptiness Problem

Abstract: In this paper we study a subclass of pebble automata (PA) for data languages for which the emptiness problem is decidable. Namely, we introduce the so-called top view weak PA. Roughly speaking, top view weak PA are weak PA where the equality test is performed only between the data values seen by the two most recently placed pebbles. The emptiness problem for this model is decidable. We also show that it is robust: alternating, nondeterministic and deterministic top view weak PA have the same recognition power. Moreover, this model is strong enough to accept all data languages expressible in Linear Temporal Logic with the future-time operators, augmented with one register freeze quantifier.


Evaluating Trust in Grid Certificates

Abstract: Digital certificates are used to secure international computation and data storage grids used for e-Science projects, like the Worldwide Large Hadron Collider Computing Grid. The International Grid Trust Federation has defined the Grid Certificate Profile: a set of guidelines for digital certificates used for grid authentication. We have designed and implemented a program and related test suites for checking X.509 certificates against the certificate profiles and policies relevant for use on the Grid. The result is a practical tool that assists implementers and users of public key infrastructures to reach appropriate trust decisions.


Metric and Kernel Learning using a Linear Transformation

Abstract: Metric and kernel learning are important in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional data, while existing kernel learning algorithms are often limited to the transductive setting and do not generalize to new data points. In this paper, we study metric learning as a problem of learning a linear transformation of the input data. We show that for high-dimensional data, a particular framework for learning a linear transformation of the data based on the LogDet divergence can be efficiently kernelized to learn a metric (or equivalently, a kernel function) over an arbitrarily high dimensional space. We further demonstrate that a wide class of convex loss functions for learning linear transformations can similarly be kernelized, thereby considerably expanding the potential applications of metric learning. We demonstrate our learning approach by applying it to large-scale real world problems in computer vision and text mining.


Topological De-Noising: Strengthening the Topological Signal

Abstract: Topological methods, including persistent homology, are powerful tools for analysis of high-dimensional data sets but these methods rely almost exclusively on thresholding techniques. In noisy data sets, thresholding does not always allow for the recovery of topological information. We present an easy to implement, computationally efficient pre-processing algorithm to prepare noisy point cloud data sets for topological data analysis. The topological de-noising algorithm allows for the recovery of topological information that is inaccessible by thresholding methods. We apply the algorithm to synthetically-generated noisy data sets and show the recovery of topological information which is impossible to obtain by thresholding. We also apply the algorithm to natural image data in R^8 and show a very clean recovery of topological information previously only available with large amounts of thresholding. Finally, we discuss future directions for improving this algorithm using zig-zag persistence methods.


Knowledge Extraction for Discriminating Male and Female in Logical Reasoning from Student Model

Abstract: The learning process is a process of communication and interaction between the teacher and his students on one side and between the students and each others on the other side. Interaction of the teacher with his students has a great importance in the process of learning and education. The pattern and style of this interaction is determined by the educational situation, trends and concerns, and educational characteristics. Classroom interaction has an importance and a big role in increasing the efficiency of the learning process and raising the achievement levels of students. Students need to learn skills and habits of study, especially at the university level. The effectiveness of learning is affected by several factors that include the prevailing patterns of interactive behavior in the classroom. These patterns are reflected in the activities of teacher and learners during the learning process. The effectiveness of learning is also influenced by the cognitive and non cognitive characteristics of teacher that help him to succeed, the characteristics of learners, teaching subject, and the teaching methods. This paper presents a machine learning algorithm for extracting knowledge from student model. The proposed algorithm utilizes the inherent characteristic of genetic algorithm and neural network for extracting comprehensible rules from the student database. The knowledge is used for discriminating male and female levels in logical reasoning as a part of an expert system course.


Beyond the Drawing Board: Toward More Effective Use of Whiteboard Content

Abstract: We developed a system that augments traditional office whiteboards with computation for the purposes of retrieving, reusing, and sharing whiteboard content. Our system automatically captures changes to whiteboard images, detects significant changes, and identifies potential collaborative activities. Users then browse and search the collection of images captured from their camera or shared from other users' cameras based on aspects such as location, time, collaboration, etc. We report on the results of a formative study and on an evaluation of effectiveness of our system, and discuss additional functionality that can be built on our framework.


How to Compare the Scientific Contributions between Research Groups

Abstract: We present a method to analyse the scientific contributions between research groups. Given multiple research groups, we construct their journal/proceeding graphs and then compute the similarity/gap between them using network analysis. This analysis can be used for measuring similarity/gap of the topics/qualities between research groups' scientific contributions. We demonstrate the practicality of our method by comparing the scientific contributions by Korean researchers with those by the global researchers for information security in 2006 - 2008. The empirical analysis shows that the current security research in South Korea has been isolated from the global research trend.


Sorting under Partial Information (without the Ellipsoid Algorithm)

Abstract: We revisit the well-known problem of sorting under partial information: sort a finite set given the outcomes of comparisons between some pairs of elements. The input is a partially ordered set P, and solving the problem amounts to discovering an unknown linear extension of P, using pairwise comparisons. The information-theoretic lower bound on the number of comparisons needed in the worst case is log e(P), the binary logarithm of the number of linear extensions of P. In a breakthrough paper, Jeff Kahn and Jeong Han Kim (J. Comput. System Sci. 51 (3), 390-399, 1995) showed that there exists a polynomial-time algorithm for the problem achieving this bound up to a constant factor. Their algorithm invokes the ellipsoid algorithm at each iteration for determining the next comparison, making it impractical. We develop efficient algorithms for sorting under partial information. Like Kahn and Kim, our approach relies on graph entropy. However, our algorithms differ in essential ways from theirs. Rather than resorting to convex programming for computing the entropy, we approximate the entropy, or make sure it is computed only once, in a restricted class of graphs, permitting the use of a simpler algorithm. Specifically, we present: - an O(n^2) algorithm performing O(log n log e(P)) comparisons; - an O(n^2.5) algorithm performing at most (1+ epsilon) log e(P) + O_epsilon (n) comparisons; - an O(n^2.5) algorithm performing O(log e(P)) comparisons. All our algorithms can be implemented in such a way that their computational bottleneck is confined in a preprocessing phase, while the sorting phase is completed in O(q) + O(n) time, where q denotes the number of comparisons performed.


Functions Definable by Numerical Set-Expressions

Abstract: A "numerical set-expression" is a term specifying a cascade of arithmetic and logical operations to be performed on sets of non-negative integers. If these operations are confined to the usual Boolean operations together with the result of lifting addition to the level of sets, we speak of "additive circuits". If they are confined to the usual Boolean operations together with the result of lifting addition and multiplication to the level of sets, we speak of "arithmetic circuits". In this paper, we investigate the definability of sets and functions by means of additive and arithmetic circuits, occasionally augmented with additional operations.


(RCFT) ReClustering Formation Technique in Hierarchical Sensor Network

Abstract: TBecause of limited energy of nodes, an important issue for sensor network is efficient use of the energy. The clustering technique reduces energy consumption as cluster head sends sensed information to a sink node. Because of such character of clustering technique, electing cluster head is an important element for networks. This paper proposes RCFT (ReClustering Formation Technique) that reconstruct clusters in hierarchical sensor networks. RCFT is a protocol that reconstructed clusters considering position of a cluster head and nodes in randomly constructed clusters. And this paper demonstrated that clusters are composed evenly through simulation, accordingly this simulation shows the result reducing energy consumption.


Checking Behavioral Consistency Constraints for Pervasive Context in Asynchronous Environments

Abstract: Context consistency checking, the checking of specified constraint on properties of contexts, is essential to context-aware applications. In order to delineate and adapt to dynamic changes in the pervasive computing environment, context-aware applications often need to specify and check behavioral consistency constraints over the contexts. This problem is challenging mainly due to the distributed and asynchronous nature of pervasive computing environments. Specifically, the critical issue in checking behavioral constraints is the temporal ordering of contextual activities. The contextual activities usually involve multiple context collecting devices, which are fully-decentralized and interact in an asynchronous manner. However, existing context consistency checking schemes do not work in asynchronous environments, since they implicitly assume the availability of a global clock or relay on synchronized interactions. To this end, we propose the Ordering Global Activity (OGA) algorithm, which detects the ordering of the global activities based on predicate detection in asynchronous environments. The essence of our approach is the message causality and its on-the-fly coding as logic vector clocks in asynchronous environments. We implement the Middleware Infrastructure for Predicate detection in Asynchronous environments (MIPA), over which the OGA algorithm is implemented and evaluated. The evaluation results show the impact of asynchrony on the checking of behavioral consistency constraints, which justifies the primary motivation of our work. They also show that OGA can achieve accurate checking of behavioral consistency constraints in dynamic pervasive computing environments.


Impact of Obstacles on the Degree of Mobile Ad Hoc Connection Graphs

Abstract: What is the impact of obstacles on the graphs of connections between stations in Mobile Ad hoc Networks? In order to answer, at least partially, this question, the first step is to define both an environment with obstacles and a mobility model for the stations in such an environment. The present paper focuses on a new way of considering the mobility within environments with obstacles, while keeping the core ideas of the well-known Random WayPoint mobility model (a.k.a RWP). Based on a mesh-partitioning of the space, we propose a new model called RSP-O-G for which we compute the spatial distribution of stations and analyse how the presence of obstacles impacts this distribution compared to the distribution when no obstacles are present. Coupled with a simple model of radio propagation, and according to the density of stations in the environment, we study the mean degree of the connection graphs corresponding to such mobile ad hoc networks.


An Alternative To Common Content Management Techniques

Abstract: Content management systems use various strategies to store and manage information. One of the most usual methods encountered in commercial products is to make use of the file system to store the raw content information, while the associated metadata is kept synchronized in a relational database management system. This strategy has its advantages but we believe it also has significant limitations which should be addressed and eventually solved. In this paper we propose an alternative method of storing and managing content aiming at finding solutions for current limitations both in terms of functional and nonfunctional requirements.


A O(E) Time Shortest Path Algorithm For Non Negative Weighted Undirected Graphs

Abstract: In most of the shortest path problems like vehicle routing problems and network routing problems, we only need an efficient path between two points source and destination, and it is not necessary to calculate the shortest path from source to all other nodes. This paper concentrates on this very idea and presents an algorithm for calculating shortest path for (i) nonnegative weighted undirected graphs (ii) unweighted undirected graphs. The algorithm completes its execution in O(E) for all graphs except few in which longer path (in terms of number of edges) from source to some node makes it best selection for that node. The main advantage of the algorithms is its simplicity and it does not need complex data structures for implementations.


A Mirroring Theorem and its Application to a New Method of Unsupervised Hierarchical Pattern Classification

Abstract: In this paper, we prove a crucial theorem called Mirroring Theorem which affirms that given a collection of samples with enough information in it such that it can be classified into classes and subclasses then (i) There exists a mapping which classifies and subclassifies these samples (ii) There exists a hierarchical classifier which can be constructed by using Mirroring Neural Networks (MNNs) in combination with a clustering algorithm that can approximate this mapping. Thus, the proof of the Mirroring theorem provides a theoretical basis for the existence and a practical feasibility of constructing hierarchical classifiers, given the maps. Our proposed Mirroring Theorem can also be considered as an extension to Kolmogrovs theorem in providing a realistic solution for unsupervised classification. The techniques we develop, are general in nature and have led to the construction of learning machines which are (i) tree like in structure, (ii) modular (iii) with each module running on a common algorithm (tandem algorithm) and (iv) selfsupervised. We have actually built the architecture, developed the tandem algorithm of such a hierarchical classifier and demonstrated it on an example problem.


Synchronized Task Decomposition for Cooperative Multi-agent Systems

Abstract: It is an amazing fact that remarkably complex behaviors could emerge from a large collection of very rudimentary dynamical agents through very simple local interactions. However, it still remains elusive on how to design these local interactions among agents so as to achieve certain desired collective behaviors. This paper aims to tackle this challenge and proposes a divide-and-conquer approach to guarantee specified global behaviors through local coordination and control design for multi-agent systems. The basic idea is to decompose the requested global specification into subtasks for each individual agent. It should be noted that the decomposition is not arbitrary. The global specification should be decomposed in such a way that the fulfilment of these subtasks by each individual agent will imply the satisfaction of the global specification as a team. First, it is shown by a counterexample that not all specifications can be decomposed in this sense. Then, a natural follow-up question is what the necessary and sufficient condition should be for the proposed decomposability of a global specification. The main part of the paper is set to answer this question. The case of two cooperative agents is investigated first, and a necessary and sufficient condition is presented and proven. Later on, the result is generalized to the case of arbitrary finite number of agents, and a hierarchical algorithm is proposed, which is shown to be a sufficient condition. Finally, a cooperative control scenario for a team of three robots is developed to illustrate the task decomposition procedure.


Spatial games and global optimization for mobile association problems

Abstract: The basic optimal transportation problem consists in finding the most effective way of moving masses from one location to another, while minimizing the transportation cost. Such concept has been found to be useful to understand various mathematical, economical, and control theory phenomena, such as Witsenhausen's counterexam-ple in stochastic control theory, principal-agent problem in microeco- nomic theory, location and planning problems, etc. In this work, we focus on mobile association problems: the determina-tion of the cells corresponding to each base station, i.e., the locations at which intelligent mobile terminals prefer to connect to a given base station rather than to others. This work combines game theory and optimal transport theory to characterize the solution based on fluid approximations. We characterize the optimal solution from both the global network and the mobile user points of view.


Knowledge Management Concepts For Training By Project An observation of the case of project management education

Abstract: Project management education programmes are often proposed in higher education to give students competences in project planning (Gantt's chart), project organizing, human and technical resource management, quality control and also social competences (collaboration, communication), emotional ones (empathy, consideration of the other, humour, ethics), and organizational ones (leadership, political vision, and so on). This training is often given according a training-by-project type of learning with case studies. This article presents one course characterized by a pedagogical organization based upon Knowledge Management (KM) concepts: knowledge transfer and construction throughout a learning circle and social interactions. The course is supported by a rich and complex tutor organization. We have observed this course by using another KM method inspired from KADS with various return of experience formalized into cards and charts. Our intention is, according to the model of Argyris and Sch\"on (Smith, 2001), to gain feedback information about local and global processes and about actors' experience in order to improve the course. This paper describes precisely the course (pedagogical method and tutor activity) and the KM observation method permitting to identify problem to solve. In our case, we observe problem of pedacogical coordination and skills acquisition. We propose to design a metacognitive tool for tutors and students, usable for improving knowledge construction and learning process organisation


Meshat: Monitoring and Experience Sharing Tool for Project-Based Learning

Abstract: Our work aims at studying tools offered to learners and tutors involved in face-to-face or blended project-based learning activities. To understand better the needs and expectations of each actor, we are especially interested in the specific case of project management training. The results of a course observation show that the lack of monitoring and expertise transfer tools involves important dysfunctions in the course organisation and therefore dissatisfaction for tutors and students (in particular about the acquisition of knowledge and expertise). So as to solve this problem, we propose a personalised platform (according to the actor: project group, student or tutor) which gives information to monitor activities and supports the acquisition and transfer of expertise. This platform is meant for the complex educational context of project-based learning. Indeed, as for the majority of project-based learning activities, the articulation conceptualisation-experiment is an important part of the process. The originality of our approach relies on also supporting the articulation between action (experiment or conceptualisation) and reflection. This approach so improves the acquisition of complex skills (e.g. management, communication and collaboration), which requires a behavioural evolution. We aim at making the students become able ?to learn to learn' and evolve according to contexts. We facilitate their ability to have a critical analysis of their actions according to the situations they encounter.


Algorithm as Defining Dynamic Systems

Abstract: This paper proposes a new view to algorithms, Algorithms as defining dynamic systems. This view extends the traditional, deterministic view that an algorithm is a step by step procedure with nondeterminism. As a dynamic system can be designed by a set of its defining laws, it is also desirable to design an algorithm by a (possibly nondeterministic) set of defining laws. This observation requires some changes to algorithm development. We propose a two step approach, the first step is to design an algorithm via a set of defining laws of dynamic system. The second step is to translate these laws (written in a natural language) into a formal language such as linear logic.


A Wavelet-Based Digital Watermarking for Video

Abstract: A novel video watermarking system operating in the three dimensional wavelet transform is here presented. Specifically the video sequence is partitioned into spatio temporal units and the single shots are projected onto the 3D wavelet domain. First a grayscale watermark image is decomposed into a series of bitplanes that are preprocessed with a random location matrix. After that the preprocessed bitplanes are adaptively spread spectrum and added in 3D wavelet coefficients of the video shot. Our video watermarking algorithm is robust against the attacks of frame dropping, averaging and swapping. Furthermore, it allows blind retrieval of embedded watermark which does not need the original video and the watermark is perceptually invisible. The algorithm design, evaluation, and experimentation of the proposed scheme are described in this paper.


A Cost Effective RFID Based Customized DVD-ROM to Thwart Software Piracy

Abstract: Software piracy has been a very perilous adversary of the software based industry, from the very beginning of the development of the latter into a significant business. There has been no developed foolproof system that has been developed to appropriately tackle this vile issue. We have in our scheme tried to develop a way to embark upon this problem using a very recently developed technology of RFID.


Biologically Inspired Execution Framework for Vulnerable Workflow Systems

Abstract: The main objective of the research is to introduce a biologically inspired execution framework for workflow systems under threat due to some intrusion attack. Usually vulnerable systems need to be stop and put into wait state, hence to insure the data security and privacy while being recovered. This research ensures the availability of services and data to the end user by keeping the data security, privacy and integrity intact. To achieve the specified goals, the behavior of chameleons and concept of hibernation has been considered in combination. Hence the workflow systems become more robust using biologically inspired methods and remain available to the business consumers safely even in a vulnerable state.


From Method Fragments to Method Services

Abstract: In Method Engineering (ME) science, the key issue is the consideration of information system development methods as fragments. Numerous ME approaches have produced several definitions of method parts. Different in nature, these fragments have nevertheless some common disadvantages: lack of implementation tools, insufficient standardization effort, and so on. On the whole, the observed drawbacks are related to the shortage of usage orientation. We have proceeded to an in-depth analysis of existing method fragments within a comparison framework in order to identify their drawbacks. We suggest overcoming them by an improvement of the ?method service? concept. In this paper, the method service is defined through the service paradigm applied to a specific method fragment ? chunk. A discussion on the possibility to develop a unique representation of method fragment completes our contribution.


Enhancing the Guidance of the Intentional Model "MAP": Graph Theory Application

Abstract: The MAP model was introduced in information system engineering in order to model processes on a flexible way. The intentional level of this model helps an engineer to execute a process with a strong relationship to the situation of the project at hand. In the literature, attempts for having a practical use of maps are not numerous. Our aim is to enhance the guidance mechanisms of the process execution by reusing graph algorithms. After clarifying the existing relationship between graphs and maps, we improve the MAP model by adding qualitative criteria. We then offer a way to express maps with graphs and propose to use Graph theory algorithms to offer an automatic guidance of the map. We illustrate our proposal by an example and discuss its limitations.


Feature-Weighted Linear Stacking

Abstract: Ensemble methods, such as stacking, are designed to boost predictive accuracy by blending the predictions of multiple machine learning models. Recent work has shown that the use of meta-features, additional inputs describing each example in a dataset, can boost the performance of ensemble methods, but the greatest reported gains have come from nonlinear procedures requiring significant tuning and training time. Here, we present a linear technique, Feature-Weighted Linear Stacking (FWLS), that incorporates meta-features for improved accuracy while retaining the well-known virtues of linear regression regarding speed, stability, and interpretability. FWLS combines model predictions linearly using coefficients that are themselves linear functions of meta-features. This technique was a key facet of the solution of the second place team in the recently concluded Netflix Prize competition. Significant increases in accuracy over standard linear stacking are demonstrated on the Netflix Prize collaborative filtering dataset.


A Simple Conceptual Generator for the Internet Graph

Abstract: The evolution of the Internet during the last years, has lead to a dramatic increase of the size of its graph at the Autonomous System (AS) level. Soon - if not already - its size will make the latter impractical for use from the research community, e.g. for protocol testing. Reproducing a smaller size, snapshot of the AS graph is thus important. However, the first step towards this direction is to obtain the ability to faithfully reproduce the full AS topology. The objective of our work, is to create a generator able to accurately emulate and reproduce the distinctive properties of the Internet graph. Our approach is based on (a) the identification of the jellyfish-like structure [1] of the Internet and (b) the consideration of the peer-to-peer and customer-provider relations between ASs. We are the first to exploit the distinctive structure of the Internet graph together with utilizing the information provided by the AS relationships in order to create a tool with the aforementioned capabilities. Comparing our generator with the existing ones in the literature, the main difference is found on the fact that our tool does not try to satisfy specific metrics, but tries to remain faithful to the conceptual model of the Internet structure. In addition, our approach can lead to (i) the identification of important attributes and patterns in the Internet AS topology, as well as, (ii) the extraction of valuable information on the various relationships between ASs and their effect on the formulation of the Internet structure. We implement our graph generator and we evaluate it using the largest and most recent available dataset for the AS topology. Our evaluations, clearly show the ability of our tool to capture the structural properties of the Internet topology at the AS level with high accuracy.


Routing Technique Based on Clustering for Data Duplication Prevention in Wireless Sensor Network

Abstract: Wireless Sensor Networks is important to nodes energy consumption for long activity of sensor nodes because nodes that compose sensor network are small size, and battery capacity is limited. For energy consumption decrease of sensor nodes, sensor networks routing technique is divided by flat routing and hierarchical routing technique. Specially, hierarchical routing technique is energy efficient routing protocol to pare down energy consumption of whole sensor nodes and to scatter energy consumption of sensor nodes by forming cluster and communicating with cluster head. but though hierarchical routing technique based on clustering is advantage more than flat routing technique, this is not used for reason that is not realistic. The reason that is not realistic is because hierarchical routing technique does not consider data transmission radius of sensor node in actually. so this paper propose realistic routing technique base on clustering.


An Optimal Method For Wake Detection In SAR Images Using Radon Transformation Combined With Wavelet Filters

Abstract: A new fangled method for ship wake detection in synthetic aperture radar (SAR) images is explored here. Most of the detection procedure applies the Radon transform as its properties outfit more than any other transformation for the detection purpose. But still it holds problems when the transform is applied to an image with a high level of noise. Here this paper articulates the combination between the radon transformation and the shrinkage methods which increase the mode of wake detection process. The latter shrinkage method with RT maximize the signal to noise ratio hence it leads to most optimal detection of lines in the SAR images. The originality mainly works on the denoising segment of the proposed algorithm. Experimental work outs are carried over both in simulated and real SAR images. The detection process is more adequate with the proposed method and improves better than the conventional methods.


AES Implementation and Performance Evaluation on 8-bit Microcontrollers

Abstract: The sensor network is a network technique for the implementation of Ubiquitous computing environment. It is wireless network environment that consists of the many sensors of lightweight and low power. Though sensor network provides various capabilities, it is unable to ensure the secure authentication between nodes. Eventually it causes the losing reliability of the entire network and many secure problems. Therefore, encryption algorithm for the implementation of reliable sensor network environments is required to the applicable sensor network. In this paper, we proposed the solution of reliable sensor network to analyze the communication efficiency through measuring performance of AES encryption algorithm by plaintext size, and cost of operation per hop according to the network scale.


GoS Proposal to Improve Trust and Delay of MPLS Flows for MCN Services

Abstract: In this article, Guarantee of Service (GoS) is defined as a proposal to improve the integration of Mission Critical Networking (MCN) services in the Internet, analyzing the congestion impact on those privileged flows with high requirements of trust and delay. Multiprotocol Label Switching (MPLS) is a technology that offers flow differentiation and QoS in the Internet. Therefore, in order to improve network performance in case of congested domains, GoS is proposed as a technique that allows the local recovering of lost packets of MPLS privileged flows. To fulfill the GoS requirements for integration of MCN in MPLS, a minimum set of extensions to RSVPTE has been proposed to provide GoS capable routes. Moreover, we have carried out an analytical study of GoS scalability and a performance improvement analysis by means of simulations.


Novel Intrusion Detection using Probabilistic Neural Network and Adaptive Boosting

Abstract: This article applies Machine Learning techniques to solve Intrusion Detection problems within computer networks. Due to complex and dynamic nature of computer networks and hacking techniques, detecting malicious activities remains a challenging task for security experts, that is, currently available defense systems suffer from low detection capability and high number of false alarms. To overcome such performance limitations, we propose a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), which integrates an adaptive boosting technique and a semi parametric neural network to obtain good tradeoff between accuracy and generality. As the result, learning bias and generalization variance can be significantly minimized. Substantial experiments on KDD 99 intrusion benchmark indicate that our model outperforms other state of the art learning algorithms, with significantly improved detection accuracy, minimal false alarms and relatively small computational complexity.


Building a Vietnamese Language Query Processing Framework for ELibrary Searching Systems

Abstract: In the objective of building intelligent searching systems for Elibraries or online bookstores, we have proposed a searching system model based on a Vietnamese language query processing component. Such document searching systems based on this model can allow users to use Vietnamese queries that represent content information as input, instead of entering keywords for searching in specific fields in database. To simplify the realization process of system based on this searching system model, we set a target of building a framework to support the rapid development of Vietnamese language query processing components. Such framework let the implementation of Vietnamese language query processing component in similar systems in this domain to be done more easily.


Detecting Botnet Activities Based on Abnormal DNS traffic

Abstract: IThe botnet is considered as a critical issue of the Internet due to its fast growing mechanism and affect. Recently, Botnets have utilized the DNS and query DNS server just like any legitimate hosts. In this case, it is difficult to distinguish between the legitimate DNS traffic and illegitimate DNS traffic. It is important to build a suitable solution for botnet detection in the DNS traffic and consequently protect the network from the malicious Botnets activities. In this paper, a simple mechanism is proposed to monitors the DNS traffic and detects the abnormal DNS traffic issued by the botnet based on the fact that botnets appear as a group of hosts periodically. The proposed mechanism is also able to classify the DNS traffic requested by group of hosts (group behavior) and single hosts (individual behavior), consequently detect the abnormal domain name issued by the malicious Botnets. Finally, the experimental results proved that the proposed mechanism is robust and able to classify DNS traffic, and efficiently detects the botnet activity with average detection rate of 89 percent.


SOAP Serialization Performance Enhancement, Design And Implementation Of A Middleware

Abstract: The most straightforward way to improve performance of any system is to define the bottlenecks and think of ways to remove them. Web services are the inseparable part of any web application, as a result enhancing performance of web services will have a great effect on the overall performance of the system. The most widely used communication protocol in the web services model, SOAP, is a simple protocol for the exchange of messages. The serialization of large SOAP responses is a major performance bottleneck in a SOAP message exchange. Clearly, some web servers can expect to receive many similar messages for a particular web service as they share the same signature. The idea behind this paper is to avoid the redundant serialization stage of SOAP responses for request which have the same call parameters. The technique exploits the similarities between call parameters to improve web service Response Time by avoiding redundant serialization of the same response with the help of a middleware running on top of web server. The middleware will maintain a trie of incoming parameters for every set of current requests. This way request processing and serialization of the response of same requests will be done only once. In a nutshell, to serialize only the different responses is the simplest way to avoid extra work done by a serializer. It might worth noting that although our approach is to utilize the exact repeating portion parameters, the middleware can be configured to apply changes made to the result set of response to the serialized response being maintained in a trie to generate valid results.


Breast Cancer Detection Using Multilevel Thresholding

Abstract: This paper presents an algorithm which aims to assist the radiologist in identifying breast cancer at its earlier stages. It combines several image processing techniques like image negative, thresholding and segmentation techniques for detection of tumor in mammograms. The algorithm is verified by using mammograms from Mammographic Image Analysis Society. The results obtained by applying these techniques are described.


Energy Efficient Security Architecture for Wireless BioMedical Sensor Networks

Abstract: Latest developments in VLSI, wireless communications, and biomedical sensing devices allow very small, lightweight, low power, intelligent sensing devices called biosensors. A set of these devices can be integrated into a Wireless Biomedical Sensor Network (WBSN), a new breakthrough technology used in telemedicine for monitoring the physiological condition of an individual. The biosensor nodes in WBSN has got resource limitations in terms of battery lifetime, CPU processing capability, and memory capacity. Replacement or recharging of batteries on thousands of biosensor nodes is quiet difficult or too costly. So, a key challenge in wireless biomedical sensor networks is the reduction of energy and memory consumption. Considering, the sensitivity of information in WBSN, we must provide security and patient privacy, as it is an important issue in the design of such systems. Hence this paper proposes an energy efficient security protocol for WBSN where security is provided to the physiological data, which is being transmitted from the sensor node to the sink device. This is achieved by authenticating the data using patients biometric, encrypting the data using Quasi Group cryptography after compressing the image data using an energy efficient number theory based technique.


Software Security Rules, SDLC Perspective

Abstract: Software has become an integral part of everyday life. Everyday, millions of people perform transaction through internet, ATM, mobile phone, they send email and Egreetings, and use word processing and spreadsheet for various purpose. People use software bearing in mind that it is reliable and can be trust upon and the operation they perform is secured. Now, if these software have exploitable security hole then how can they be safe for use. Security brings value to software in terms of peoples trust. The value provided by secure software is of vital importance because many critical functions are entirely dependent on the software. That is why security is a serious topic which should be given proper attention during the entire SDLC, right from the beginning. For the proper implementation of security in the software, twenty one security rules are proposed in this paper along with validation results. It is found that by applying these rules as per given implementation mechanism, most of the vulnerabilities are eliminated in the software and a more secure software can be built.


A Context-based Trust Management Model for Pervasive Computing Systems

Abstract: Trust plays an important role in making collaborative decisions about service evaluation and service selection in pervasive computing. Context is a fundamental concept in pervasive systems, which is based on the interpretation of environment and systems. The dynamic nature of context can strongly affect trust management and service selection. In this paper, we present a context-based trust management model for pervasive computing systems. The concept of context is considered in basic components of the model such as trust computation module, recommender assessment module, transaction management module, and request responder. In order to measure a predicted trustworthiness according to the fuzzy nature of trust in pervasive environments, fuzzy concepts are integrated in the proposed model.


Proposed platform for improving grid security by trust management system

Abstract: With increasing the applications of grid system, the risk in security field is enhancing too. Recently Trust management system has been recognized as a noticeable approach in enhancing of security in grid systems. In this article due to improve the grid security a new trust management system with two levels is proposed. The benefits of this platform are adding new domain in grid system, selecting one service provider which has closest adaption with user requests and using from domains security attribute as an important factor in computing the trust value.


An Innovative Scheme For Effectual Fingerprint Data Compression Using Bezier Curve Representations

Abstract: Naturally, with the mounting application of biometric systems, there arises a difficulty in storing and handling those acquired biometric data. Fingerprint recognition has been recognized as one of the most mature and established technique among all the biometrics systems. In recent times, with fingerprint recognition receiving increasingly more attention the amount of fingerprints collected has been constantly creating enormous problems in storage and transmission. Henceforth, the compression of fingerprints has emerged as an indispensable step in automated fingerprint recognition systems. Several researchers have presented approaches for fingerprint image compression. In this paper, we propose a novel and efficient scheme for fingerprint image compression. The presented scheme utilizes the Bezier curve representations for effective compression of fingerprint images. Initially, the ridges present in the fingerprint image are extracted along with their coordinate values using the approach presented. Subsequently, the control points are determined for all the ridges by visualizing each ridge as a Bezier curve. The control points of all the ridges determined are stored and are used to represent the fingerprint image. When needed, the fingerprint image is reconstructed from the stored control points using Bezier curves. The quality of the reconstructed fingerprint is determined by a formal evaluation. The proposed scheme achieves considerable memory reduction in storing the fingerprint.


Exception Agent Detection System for IP Spoofing Over Online Environments

Abstract: Over the recent years, IP and email spoofing gained much importance for security concerns due to the current changes in manipulating the system performance in different online environments. Intrusion Detection System (IDS) has been used to secure these environments for sharing their data over network and host based IDS approaches. However, the rapid growth of intrusion events over Internet and local area network become responsible for the distribution of different threats and vulnerabilities in the computing systems. The current signature detection approach used by IDS, detects unclear actions based on analyzing and describing the action patterns such as time, text, password etc and has been faced difficulties in updating information, detect unknown novel attacks, maintenance of an IDS which is necessarily connected with analyzing and patching of security holes, and the lack of information on user privileges and attack signature structure. Thus, this paper proposes an EADS (Exception agent detection system) for securing the header information carried by IP over online environments. The study mainly concerns with the deployment of new technique for detecting and eliminating the unknown threats attacks during the data sharing over online environments.


A Trust Based Cross Layer Security Protocol for Mobile Ad hoc Networks

Abstract: In this paper, we develop a trust based security protocol based on a cross layer approach which attains confidentiality and authentication of packets in both routing and link layers of MANETs. In the first phase of the protocol, we design a trust based packet forwarding scheme for detecting and isolating the malicious nodes using the routing layer information. It uses trust values to favor packet forwarding by maintaining a trust counter for each node. A node is punished or rewarded by decreasing or increasing the trust counter. If the trust counter value falls below a trust threshold, the corresponding intermediate node is marked as malicious. In the next phase of the protocol, we provide link layer security using the CBCX mode of authentication and encryption. By simulation results, we show that the proposed cross layer security protocol achieves high packet delivery ratio while attaining low delay and overhead.


Optimization and Evaluation of Nested Queries and Procedures

Abstract: Many database applications perform complex data retrieval and update tasks. Nested queries, and queries that invoke user-defined functions, which are written using a mix of procedural and SQL constructs, are often used in such applications. A straight-forward evaluation of such queries involves repeated execution of parameterized sub-queries or blocks containing queries and procedural code. An important problem that arises while optimizing nested queries as well as queries with joins, aggregates and set operations is the problem of finding an optimal sort order from a factorial number of possible sort orders. We show that even a special case of this problem is NP-Hard, and present practical heuristics that are effective and easy to incorporate in existing query optimizers. We also consider iterative execution of queries and updates inside complex procedural blocks such as user-defined functions and stored procedures. Parameter batching is an important means of improving performance as it enables set-orientated processing. The key challenge to parameter batching lies in rewriting a given procedure/function to process a batch of parameter values. We propose a solution, based on program analysis and rewrite rules, to automate the generation of batched forms of procedures and replace iterative database calls within imperative loops with a single call to the batched form. We present experimental results for the proposed techniques, and the results show significant gains in performance.


Radio Transmission Performance of EPCglobal Gen-2 RFID System

Abstract: In this paper, we analyze the performance of the encoding and the modulation processes in the downlink and uplink of the EPCglobal Gen2 system through the analysis and simulation. Furthermore, the synchronization issues on time and frequency domain and the preamble architecture are evaluated. Through the simulation in the uplink, we find that the detection probability of FM0 and Miller coding approaches 1 at 13dB Eb/N0.


On Element SDD Approximability

Abstract: This short communication shows that in some cases scalar elliptic finite element matrices cannot be approximated well by an SDD matrix. We also give a theoretical analysis of a simple heuristic method for approximating an element by an SDD matrix.


Fast Arc-Annotated Subsequence Matching in Linear Space

Abstract: An arc-annotated string is a string of characters, called bases, augmented with a set of pairs, called arcs, each connecting two bases. Given arc-annotated strings $P$ and $Q$ the arc-preserving subsequence problem is to determine if $P$ can be obtained from $Q$ by deleting bases from $Q$. Whenever a base is deleted any arc with an endpoint in that base is also deleted. Arc-annotated strings where the arcs are ``nested'' are a natural model of RNA molecules that captures both the primary and secondary structure of these. The arc-preserving subsequence problem for nested arc-annotated strings is basic primitive for investigating the function of RNA molecules. Gramm et al. [ACM Trans. Algorithms 2006] gave an algorithm for this problem using $O(nm)$ time and space, where $m$ and $n$ are the lengths of $P$ and $Q$, respectively. In this paper we present a new algorithm using $O(nm)$ time and $O(n + m)$ space, thereby matching the previous time bound while significantly reducing the space from a quadratic term to linear. This is essential to process large RNA molecules where the space is likely to be a bottleneck. To obtain our result we introduce several novel ideas which may be of independent interest for related problems on arc-annotated strings.


Visualizing Graphs with Node and Edge Labels

Abstract: When drawing graphs whose edges and nodes contain text or graphics, such informa tion needs to be displayed without overlaps, either as part of the initial layout or as a post-processing step. The core problem in removing overlaps lies in retaining the structural information inherent in a layout, minimizing the additional area required, and keeping edges as straight as possible. This paper presents a unified node and edge overlap removal algorithm that does well at solving this problem.


Bounds on monotone switching networks for directed connectivity

Abstract: We separate monotone analogues of L and NL by proving that any monotone switching network solving directed connectivity on $n$ vertices must have size at least $n^(\Omega(\lg(n)))$.


GSM Security Using Identity-based Cryptography

Abstract: Current security model in Global System for Mobile Communications (GSM) predominantly use symmetric key cryptography. The rapid advancement of Internet technology facilitates online trading, banking, downloading, emailing using resource-constrained handheld devices such as personal digital assistants and cell phones. However, these applications require more security than the present GSM supports. Consequently, a careful design of GSM security using both symmetric and asymmetric key cryptography would make GSM security more adaptable in security intensive applications. This paper presents a secure and efficient protocol for GSM security using identity based cryptography. The salient features of the proposed protocol are (i) authenticated key exchange; (ii) mutual authentication amongst communicating entities; and (iii) user anonymity. The security analysis of the protocol shows its strength against some known threats observed in conventional GSM security.


An XML-based Multi-Agent System for Supporting Online Recruitment Services

Abstract: In this paper we propose an XML-based multi-agent recommender system for supporting online recruitment services. Our system is characterized by the following features: {\em (i)} it handles user profiles for personalizing the job search over the Internet; {\em (ii)} it is based on the Intelligent Agent Technology; {\em (iii)} it uses XML for guaranteeing a light, versatile and standard mechanism for information representation, storing and exchange. The paper discusses the basic features of the proposed system, presents the results of an experimental study we have carried out for evaluating its performance, and makes a comparison between the proposed system and other e-recruitment systems already presented in the past.


A Way to Understand Various Patterns of Data Mining Techniques for Selected Domains

Abstract: This has much in common with traditional work in statistics and machine learning. However, there are important new issues which arise because of the sheer size of the data. One of the important problem in data mining is the Classification-rule learning which involves finding rules that partition given data into predefined classes. In the data mining domain where millions of records and a large number of attributes are involved, the execution time of existing algorithms can become prohibitive, particularly in interactive applications.


Management of Location Based Advertisement Services using Spatial Triggers in Cellular Networks

Abstract: This paper discusses the advent of new technologies which have emerged under the area of Location Based Services (LBS). An innovative implementation and approach has been presented for design of applications which are inventive and attractive towards the user. Spatial Trigger is one of the most promising additions to the LBS technologies. This paper describes ways in which mobile advertisement services can be introduced effectively in the cellular market by bringing innovation in them through effective usage of Spatial Triggers. Hence, opening new horizons to make the consumer cellular networks, commercially, more effective and informative.


Generalized Discriminant Analysis algorithm for feature reduction in Cyber Attack Detection System

Abstract: This Generalized Discriminant Analysis (GDA) has provided an extremely powerful approach to extracting non linear features. The network traffic data provided for the design of intrusion detection system always are large with ineffective information, thus we need to remove the worthless information from the original high dimensional database. To improve the generalization ability, we usually generate a small set of features from the original input variables by feature extraction. The conventional Linear Discriminant Analysis (LDA) feature reduction technique has its limitations. It is not suitable for non linear dataset. Thus we propose an efficient algorithm based on the Generalized Discriminant Analysis (GDA) feature reduction technique which is novel approach used in the area of cyber attack detection. This not only reduces the number of the input features but also increases the classification accuracy and reduces the training and testing time of the classifiers by selecting most discriminating features. We use Artificial Neural Network (ANN) and C4.5 classifiers to compare the performance of the proposed technique. The result indicates the superiority of algorithm.


Solution of Non-Square Fuzzy Linear Systems

Abstract: In this paper, a linear system of equations with crisp coefficients and fuzzy right-hand sides is investigated. All possible cases pertaining to the number of variables, n, and the number of equations, m, are dealt with. A solution is sought not as a fuzzy vector, as usual, but as a fuzzy set of vectors. Each vector in the solution set solves the given fuzzy linear system with a certain possibility. Assuming that the coefficient matrix is a full rank matrix, three cases are considered: For m = n (square system), the solution set is shown to be a parallelepiped in coordinate space and is expressed by an explicit formula. For m > n (overdetermined system), the solution set is proved to be a convex polyhedron and a novel geometric method is proposed to compute it. For m < n (underdetermined system), by determining the contribution of free variables, general solution is computed. From the results of three cases mentioned above, a method is proposed to handle the general case, in which the coefficient matrix is not necessarily a full rank matrix. Comprehensive examples are provided and investigated in depth to illustrate each case and suggested method.


Tractable hypergraph properties for constraint satisfaction and conjunctive queries

Abstract: An important question in the study of constraint satisfaction problems (CSP) is understanding how the graph or hypergraph describing the incidence structure of the constraints influences the complexity of the problem. For binary CSP instances (i.e., where each constraint involves only two variables), the situation is well understood: the complexity of the problem essentially depends on the treewidth of the graph of the constraints. However, this is not the correct answer if constraints with unbounded number of variables are allowed, and in particular, for CSP instances arising from query evaluation problems in database theory. Formally, if H is a class of hypergraphs, then let CSP(H) be CSP restricted to instances whose hypergraph is in H. Our goal is to characterize those classes of hypergraphs for which CSP(H) is polynomial-time solvable or fixed-parameter tractable, parameterized by the number of variables. Note that in the applications related to database query evaluation, we usually assume that the number of variables is much smaller than the size of the instance, thus parameterization by the number of variables is a meaningful question. The most general known property of H that makes CSP(H) polynomial-time solvable is bounded fractional hypertree width. Here we introduce a new hypergraph measure called submodular width, and show that bounded submodular width of H implies that CSP(H) is fixed-parameter tractable. In a matching hardness result, we show that if H has unbounded submodular width, then CSP(H) is not fixed-parameter tractable, unless the Exponential Time Hypothesis fails.


Research report : Collaborative Peer 2 Peer Edition: Avoiding Conflicts is Better than Solving Conflicts

Abstract: Collaborative edition is achieved by distinct sites that work independently on (a copy of) a shared document. Conflicts may arise during this process and must be solved by the collaborative editor. In pure Peer to Peer collaborative editing, no centralization nor locks nor time-stamps are used which make conflict resolution difficult. We propose an algorithm which relies on the notion or semantics dependence and avoids the need of any integration transformation to solve conflicts. Furthermore, it doesn't use any history file recording operations performed since starting the edition process. We show how to define editing operations for semi-structured documents i.e. XML-like trees, that are enriched with informations derived for free from the editing process. Then we define the semantics dependence relation required by the algorithm and we present preliminary results obtained by a prototype implementation.


A New Computational Schema for Euphonic Conjunctions in Sanskrit Processing

Abstract: Automated language processing is central to the drive to enable facilitated referencing of increasingly available Sanskrit E texts. The first step towards processing Sanskrit text involves the handling of Sanskrit compound words that are an integral part of Sanskrit texts. This firstly necessitates the processing of euphonic conjunctions or sandhis, which are points in words or between words, at which adjacent letters coalesce and transform. The ancient Sanskrit grammarian Panini's codification of the Sanskrit grammar is the accepted authority in the subject. His famed sutras or aphorisms, numbering approximately four thousand, tersely, precisely and comprehensively codify the rules of the grammar, including all the rules pertaining to sandhis. This work presents a fresh new approach to processing sandhis in terms of a computational schema. This new computational model is based on Panini's complex codification of the rules of grammar. The model has simple beginnings and is yet powerful, comprehensive and computationally lean.


Construction of a Non-2-colorable k-uniform Hypergraph with Few Edges

Abstract: We show how to construct a non-2-colorable k-uniform hypergraph with (2^(1 + o(1)))^k edges. By the duality of hypergraphs and monotone k-CNF-formulas this gives an unsatisfiable monotone k-CNF with (2^(1 + o(1)))^k clauses


Digital Image Watermarking for Arbitrarily Shaped Objects Based On SA-DWT

Abstract: Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT) and a watermark is embedded by modifying the wavelet coefficients. In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy compression (e.g.JPEG, JPEG2000), scaling, adding noise, filtering, etc.


ANN-based Innovative Segmentation Method for Handwritten text in Assamese

Abstract: Artificial Neural Network (ANN) s has widely been used for recognition of optically scanned character, which partially emulates human thinking in the domain of the Artificial Intelligence. But prior to recognition, it is necessary to segment the character from the text to sentences, words etc. Segmentation of words into individual letters has been one of the major problems in handwriting recognition. Despite several successful works all over the work, development of such tools in specific languages is still an ongoing process especially in the Indian context. This work explores the application of ANN as an aid to segmentation of handwritten characters in Assamese- an important language in the North Eastern part of India. The work explores the performance difference obtained in applying an ANN-based dynamic segmentation algorithm compared to projection- based static segmentation. The algorithm involves, first training of an ANN with individual handwritten characters recorded from different individuals. Handwritten sentences are separated out from text using a static segmentation method. From the segmented line, individual characters are separated out by first over segmenting the entire line. Each of the segments thus obtained, next, is fed to the trained ANN. The point of segmentation at which the ANN recognizes a segment or a combination of several segments to be similar to a handwritten character, a segmentation boundary for the character is assumed to exist and segmentation performed. The segmented character is next compared to the best available match and the segmentation boundary confirmed.


Technology Integration around the Geographic Information: A State of the Art

Abstract: One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented.


Domain Decomposition Based High Performance Parallel Computing

Abstract: The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers. Parallel sparse direct solvers are not found to exhibit good scalability. Hence, the parallelization of sparse direct solvers is done using domain decomposition techniques. A highly efficient sparse direct solver PARDISO is used in this study. The scalability of both Newton and modified Newton algorithms are tested.


Multi-Agent System Interaction in Integrated SCM

Abstract: Coordination between organizations on strategic, tactical and operation levels leads to more effective and efficient supply chains. Supply chain management is increasing day by day in modern enterprises. The environment is becoming competitive and many enterprises will find it difficult to survive if they do not make their sourcing, production and distribution more efficient. Multi-agent supply chain management has recognized as an effective methodology for supply chain management. Multi-agent systems (MAS) offer new methods compared to conventional, centrally organized architectures in the scope of supply chain management (SCM). Since necessary data are not available within the whole supply chain, an integrated approach for production planning and control taking into account all the partners involved is not feasible. In this study we show how MAS architecture interacts in the integrated SCM architecture with the help of various intelligent agents to highlight the above problem.


Enhanced Trustworthy and High-Quality Information Retrieval System for Web Search Engines

Abstract: The WWW is the most important source of information. But, there is no guarantee for information correctness and lots of conflicting information is retrieved by the search engines and the quality of provided information also varies from low quality to high quality. We provide enhanced trustworthiness in both specific (entity) and broad (content) queries in web searching. The filtering of trustworthiness is based on 5 factors: Provenance, Authority, Age, Popularity, and Related Links. The trustworthiness is calculated based on these 5 factors and it is stored thereby increasing the performance in retrieving trustworthy websites. The calculated trustworthiness is stored only for static websites. Quality is provided based on policies selected by the user. Quality based ranking of retrieved trusted information is provided using WIQA (Web Information Quality Assessment) Framework.


Toward a Gigabit Wireless Communications System

Abstract: This paper presents the design and the realization of a hybrid wireless Gigabit Ethernet indoor communications system operating at 60 GHz. As the 60 GHz radio link operates only in a single-room configuration, an additional Radio over Fiber (RoF) link is used to ensure the communications within all the rooms of a residential environment. The system uses low complexity baseband processing modules. A byte synchronization technique is designed to provide a high value of the preamble detection probability and a very small value of the false detection probability. Conventional RS (255, 239) encoder and decoder are used for channel forward error correction (FEC). The FEC parameters are determined by the tradeoff between higher coding gain and hardware complexity. The results of bit error rate measurements at 875 Mbps are presented for various antennas configurations.


Hybrid, Optical and Wireless Near-Gigabit Communications System

Abstract: This paper presents the study and the realization of a hybrid 60 GHz wireless communications system. As the 60 GHz radio link operates only in a single-room configuration, an additional Radio over Fibre (RoF) link is used to ensure the communications in all the rooms of a residential environment. A single carrier architecture is adopted. The system uses low complexity baseband processing modules. A byte/frame synchronization technique is designed to provide a high value of the preamble detection probability and a very small value of the false alarm probability. Conventional RS (255, 239) encoder and decoder are used to correct errors in the transmission channel. Results of Bit Error Rate (BER) measurements are presented for various antennas configurations.


Let's Make a Difference!

Abstract: We study the behaviour of iterations of the difference operator delta on streams over {0,1}. In particular, we show that a stream sigma is eventually periodic if and only if the sequence of differences sigma, delta(sigma), delta(delta(sigma)), ..., the `delta-orbit' of sigma as we call it, is eventually periodic. Moreover, we generalise this result to operations delta_d that sum modulo 2 the elements of each consecutive block of length d+1 in a given 01-stream. Some experimentation with delta-orbits of well-known streams reveals a surprising connexion between the Sierpinski stream and the Mephisto Waltz.


Unique Normal Forms in Infinitary Weakly Orthogonal Term Rewriting

Abstract: The theory of finite and infinitary term rewriting is extensively developed for orthogonal rewrite systems, but to a lesser degree for weakly orthogonal rewrite systems. In this note we present some contributions to the latter case of weak orthogonality, where critial pairs are admitted provided they are trivial. We start with a refinement of the by now classical Compression Lemma, as a tool for establishing infinitary confluence, and hence the property of unique infinitary normal forms, for the case of weakly orthogonal TRSs that do not contain collapsing rewrite rules. That this restriction of collapse-freeness is crucial, is shown in a elaboration of a simple TRS which is weakly orthogonal, but has two collapsing rules. It turns out that all the usual theory breaks down dramatically. We conclude with establishing a positive fact: the diamond property for infinitary developments for weakly orthogonal TRSs, by means of a detailed analysis initiated by van Oostrom for the finite case.


Examples as Interaction: On Humans Teaching a Computer to Play a Game

Abstract: This paper reviews an experiment in human-computer interaction, where interaction takes place when humans attempt to teach a computer to play a strategy board game. We show that while individually learned models can be shown to improve the playing performance of the computer, their straightforward composition results in diluting what was earlier learned. This observation suggests that interaction cannot be easily distributed when one hopes to harness multiple human experts to develop a quality computer player. This is related to similar approaches in robot task learning and to classic approaches to human learning and reinforces the need to develop tools that facilitate the mix of human-based tuition and computer self-learning.


Syst\`eme de Communications Sans Fil Tr\`es Haut D\'ebit \`a 60 GHz

Abstract: This paper presents the study and the realization at IETR of a high data rate 60 GHz wireless communications system. The system uses a simple single carrier architecture. The receiver architecture is based on a differential demodulation which minimizes the intersymbol interference (ISI) effect and a signal processing unit composed of a joint frame and byte synchronization block and a conventional RS (255, 239) decoder. The byte synchronization technique provides a high preamble detection probability and a very small value of the false detection probability. First measurement results show a good communication link quality in line of sight environments with directional antennas.


Memento: Time Travel for the Web

Abstract: The Web is ephemeral. Many resources have representations that change over time, and many of those representations are lost forever. A lucky few manage to reappear as archived resources that carry their own URIs. For example, some content management systems maintain version pages that reflect a frozen prior state of their changing resources. Archives recurrently crawl the web to obtain the actual representation of resources, and subsequently make those available via special-purpose archived resources. In both cases, the archival copies have URIs that are protocol-wise disconnected from the URI of the resource of which they represent a prior state. Indeed, the lack of temporal capabilities in the most common Web protocol, HTTP, prevents getting to an archived resource on the basis of the URI of its original. This turns accessing archived resources into a significant discovery challenge for both human and software agents, which typically involves following a multitude of links from the original to the archival resource, or of searching archives for the original URI. This paper proposes the protocol-based Memento solution to address this problem, and describes a proof-of-concept experiment that includes major servers of archival content, including Wikipedia and the Internet Archive. The Memento solution is based on existing HTTP capabilities applied in a novel way to add the temporal dimension. The result is a framework in which archived resources can seamlessly be reached via the URI of their original: protocol-based time travel for the Web.


Sharp Dichotomies for Regret Minimization in Metric Spaces

Abstract: The Lipschitz multi-armed bandit (MAB) problem generalizes the classical multi-armed bandit problem by assuming one is given side information consisting of a priori upper bounds on the difference in expected payoff between certain pairs of strategies. Classical results of (Lai and Robbins 1985) and (Auer et al. 2002) imply a logarithmic regret bound for the Lipschitz MAB problem on finite metric spaces. Recent results on continuum-armed bandit problems and their generalizations imply lower bounds of $\sqrt{t}$, or stronger, for many infinite metric spaces such as the unit interval. Is this dichotomy universal? We prove that the answer is yes: for every metric space, the optimal regret of a Lipschitz MAB algorithm is either bounded above by any $f\in \omega(\log t)$, or bounded below by any $g\in o(\sqrt{t})$. Perhaps surprisingly, this dichotomy does not coincide with the distinction between finite and infinite metric spaces; instead it depends on whether the completion of the metric space is compact and countable. Our proof connects upper and lower bound techniques in online learning with classical topological notions such as perfect sets and the Cantor-Bendixson theorem. Among many other results, we show a similar dichotomy for the "full-feedback" (a.k.a., "best-expert") version.


Large-Scale Time-Shifted Streaming Delivery

Abstract: An attractive new feature of connected TV systems consists in allowing users to access past portions of the TV channel. This feature, called time-shifted streaming, is now used by millions of TV viewers. We address in this paper the design of a large-scale delivery system for time-shifted streaming. We highlight the characteristics of time-shifted streaming that prevent known video delivery systems to be used. Then, we present two proposals that meet the demand for two radically different types of TV operator. First, the Peer-Assisted Catch-Up Streaming system, namely PACUS, aims at reducing the load on the server of a large TV broadcasters without losing the control of the TV delivery. Second, the turntable structure, is an overlay of nodes that allow an independent content delivery network or a small independent TV broadcaster to ensure that all past TV programs are stored and as available as possible. We show through extensive simulations that our objectives are reached, with a reduction of up to three quarters of the traffic for PACUS and a 100\% guaranteed availability for the turntable structure. We also compare our proposals to the main previous works in the area.


Firewall Configuration Errors Revisited

Abstract: The first quantitative evaluation of the quality of corporate firewall configurations appeared in 2004, based on Check Point FireWall-1 rule-sets. In general that survey indicated that corporate firewalls were often enforcing poorly written rule-sets, containing many mistakes. The goal of this work is to revisit the first survey. The current study is much larger. Moreover, for the first time, the study includes configurations from two major vendors. The study also introduce a novel "Firewall Complexity" (FC) measure, that applies to both types of firewalls. The findings of the current study indeed validate the 2004 study's main observations: firewalls are (still) poorly configured, and a rule-set's complexity is (still) positively correlated with the number of detected risk items. Thus we can conclude that, for well-configured firewalls, ``small is (still) beautiful''. However, unlike the 2004 study, we see no significant indication that later software versions have fewer errors (for both vendors).


What is instrumentality in new digital msuical devices ? A contribution from cognitive linguistics and psychology

Abstract: As far as music is concerned, instruments have always been part of a cultural ?landscape? (on technical, expressive and symbolic levels). The present contribution explores the changes brought about by the shift that occurred during the 20th century, from mechanical to digital instruments (also named ?virtual instruments?). First and foremost, a short recall of some historical steps of the technological developments that have renewed our relationship to sound, music, and instruments will be presented. Second, an analysis of different discourses and terminologies presently used in the domains of musicology and computer music will account for the evolution of the notion of instrumentality.


Bounding the radii of balls meeting every connected component of semi-algebraic sets

Abstract: We prove explicit bounds on the radius of a ball centered at the origin which is guaranteed to contain all bounded connected components of a semi-algebraic set $S \subset \mathbbm{R}^k$ defined by a quantifier-free formula involving $s$ polynomials in $\mathbbm{Z}[X_1, ..., X_k]$ having degrees at most $d$, and whose coefficients have bitsizes at most $\tau$. Our bound is an explicit function of $s, d, k$ and $\tau$, and does not contain any undetermined constants. We also prove a similar bound on the radius of a ball guaranteed to intersect every connected component of $S$ (including the unbounded components). While asymptotic bounds of the form $2^{\tau d^{O (k)}}$ on these quantities were known before, some applications require bounds which are explicit and which hold for all values of $s, d, k$ and $\tau$. The bounds proved in this paper are of this nature.


Optimal Approximation Algorithms for Multi-agent Combinatorial Problems with Discounted Price Functions

Abstract: Submodular functions are an important class of functions in combinatorial optimization which satisfy the natural properties of decreasing marginal costs. The study of these functions has led to strong structural properties with applications in many areas. Recently, there has been significant interest in extending the theory of algorithms for optimizing combinatorial problems (such as network design problem of spanning tree) over submodular functions. Unfortunately, the lower bounds under the general class of submodular functions are known to be very high for many of the classical problems. In this paper, we introduce and study an important subclass of submodular functions, which we call discounted price functions. These functions are succinctly representable and generalize linear cost functions. In this paper we study the following fundamental combinatorial optimization problems: Edge Cover, Spanning Tree, Perfect Matching and Shortest Path, and obtain tight upper and lower bounds for these problems. The main technical contribution of this paper is designing novel adaptive greedy algorithms for the above problems. These algorithms greedily build the solution whist rectifying mistakes made in the previous steps.


On the maximal number of cubic subwords in a string

Abstract: We investigate the problem of the maximum number of cubic subwords (of the form $www$) in a given word. We also consider square subwords (of the form $ww$). The problem of the maximum number of squares in a word is not well understood. Several new results related to this problem are produced in the paper. We consider two simple problems related to the maximum number of subwords which are squares or which are highly repetitive; then we provide a nontrivial estimation for the number of cubes. We show that the maximum number of squares $xx$ such that $x$ is not a primitive word (nonprimitive squares) in a word of length $n$ is exactly $\lfloor \frac{n}{2}\rfloor - 1$, and the maximum number of subwords of the form $x^k$, for $k\ge 3$, is exactly $n-2$. In particular, the maximum number of cubes in a word is not greater than $n-2$ either. Using very technical properties of occurrences of cubes, we improve this bound significantly. We show that the maximum number of cubes in a word of length $n$ is between $(1/2)n$ and $(4/5)n$. (In particular, we improve the lower bound from the conference version of the paper.)