Directional Dynamics along Arbitrary Curves in Cellular Automata

Abstract: This paper studies directional dynamics in cellular automata, a formalism previously introduced by the third author. The central idea is to study the dynamical behaviour of a cellular automaton through the conjoint action of its global rule (temporal action) and the shift map (spacial action): qualitative behaviours inherited from topological dynamics (equicontinuity, sensitivity, expansivity) are thus considered along arbitrary curves in space-time. The main contributions of the paper concern equicontinuous dynamics which can be connected to the notion of consequences of a word. We show that there is a cellular automaton with an equicontinuous dynamics along a parabola, but which is sensitive along any linear direction. We also show that real numbers that occur as the slope of a limit linear direction with equicontinuous dynamics in some cellular automaton are exactly the computably enumerable numbers.


Bulking II: Classifications of Cellular Automata

Abstract: This paper is the second part of a series of two papers dealing with bulking: a way to define quasi-order on cellular automata by comparing space-time diagrams up to rescaling. In the present paper, we introduce three notions of simulation between cellular automata and study the quasi-order structures induced by these simulation relations on the whole set of cellular automata. Various aspects of these quasi-orders are considered (induced equivalence relations, maximum elements, induced orders, etc) providing several formal tools allowing to classify cellular automata.


Structure of Extreme Correlated Equilibria: a Zero-Sum Example and its Implications

Abstract: We exhibit the rich structure of the set of correlated equilibria by analyzing the simplest of polynomial games: the mixed extension of matching pennies. We show that while the correlated equilibrium set is convex and compact, the structure of its extreme points can be quite complicated. In finite games the ratio of extreme correlated to extreme Nash equilibria can be greater than exponential in the size of the strategy spaces. In polynomial games there can exist extreme correlated equilibria which are not finitely supported; we construct a large family of examples using techniques from ergodic theory. We show that in general the set of correlated equilibrium distributions of a polynomial game cannot be described by conditions on finitely many moments (means, covariances, etc.), in marked contrast to the set of Nash equilibria which is always expressible in terms of finitely many moments.


Multi-dimensional Boltzmann Sampling of Languages

Abstract: This paper addresses the uniform random generation of words from a context-free language (over an alphabet of size $k$), while constraining every letter to a targeted frequency of occurrence. Our approach consists in a multidimensional extension of Boltzmann samplers \cite{Duchon2004}. We show that, under mostly \emph{strong-connectivity} hypotheses, our samplers return a word of size in $[(1-\varepsilon)n, (1+\varepsilon)n]$ and exact frequency in $\mathcal{O}(n^{1+k/2})$ expected time. Moreover, if we accept tolerance intervals of width in $\Omega(\sqrt{n})$ for the number of occurrences of each letters, our samplers perform an approximate-size generation of words in expected $\mathcal{O}(n)$ time. We illustrate these techniques on the generation of Tetris tessellations with uniform statistics in the different types of tetraminoes.


Solar Still Coupled With Solar Collector and Storage Tank

Abstract: Acute shortage of good, clean drinking water is a major problem for most developing countries of the world. In most cases, ponds, streams, wells and rivers are often polluted that they are unsafe for direct use as drinking water >.Often water sources are brackish and or contain harmful bacteria. Therefore cannot be used for drinking .In addition there are many coastal locations where sea water is abundant but potable water is not available. Solar distillation is one of the important methods of utilizing solar energy for the supply of potable water to small communities where natural supply of fresh water is inadequate or of poor quality .In this direction an experimental performance analysis was carried out on a single basin still compared with FPC coupled one. Test were carried out for different water samples namely borewell water, sea water, river water for a water depth of 20 mm


Enumeration Order Reducibility

Abstract: In this article we define a new reducibility based on the enumeration orders of r.e. sets.


$\alpha$-Discounting Multi-Criteria Decision Making ($\alpha$-D MCDM)

Abstract: In this book we introduce a new procedure called \alpha-Discounting Method for Multi-Criteria Decision Making (\alpha-D MCDM), which is as an alternative and extension of Saaty Analytical Hierarchy Process (AHP). It works for any number of preferences that can be transformed into a system of homogeneous linear equations. A degree of consistency (and implicitly a degree of inconsistency) of a decision-making problem are defined. \alpha-D MCDM is afterwards generalized to a set of preferences that can be transformed into a system of linear and or non-linear homogeneous and or non-homogeneous equations and or inequalities. The general idea of \alpha-D MCDM is to assign non-null positive parameters \alpha_1, \alpha_2, and so on \alpha_p to the coefficients in the right-hand side of each preference that diminish or increase them in order to transform the above linear homogeneous system of equations which has only the null-solution, into a system having a particular non-null solution. After finding the general solution of this system, the principles used to assign particular values to all parameters \alpha is the second important part of \alpha-D, yet to be deeper investigated in the future. In the current book we propose the Fairness Principle, i.e. each coefficient should be discounted with the same percentage (we think this is fair: not making any favoritism or unfairness to any coefficient), but the reader can propose other principles. For consistent decision-making problems with pairwise comparisons, \alpha-Discounting Method together with the Fairness Principle give the same result as AHP. But for weak inconsistent decision-making problem, \alpha-Discounting together with the Fairness Principle give a different result from AHP. Many consistent, weak inconsistent, and strong inconsistent examples are given in this book.


Local algorithms in (weakly) coloured graphs

Abstract: A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum dominating set problem and the maximum matching problem in 2-coloured and weakly 2-coloured graphs. In a weakly 2-coloured graph, both problems admit a local algorithm with the approximation factor $(\Delta+1)/2$, where $\Delta$ is the maximum degree of the graph. We also give a matching lower bound proving that there is no local algorithm with a better approximation factor for either of these problems. Furthermore, we show that the stronger assumption of a 2-colouring does not help in the case of the dominating set problem, but there is a local approximation scheme for the maximum matching problem in 2-coloured graphs.


Constraint solvers: An empirical evaluation of design decisions

Abstract: This paper presents an evaluation of the design decisions made in four state-of-the-art constraint solvers; Choco, ECLiPSe, Gecode, and Minion. To assess the impact of design decisions, instances of the five problem classes n-Queens, Golomb Ruler, Magic Square, Social Golfers, and Balanced Incomplete Block Design are modelled and solved with each solver. The results of the experiments are not meant to give an indication of the performance of a solver, but rather investigate what influence the choice of algorithms and data structures has. The analysis of the impact of the design decisions focuses on the different ways of memory management, behaviour with increasing problem size, and specialised algorithms for specific types of variables. It also briefly considers other, less significant decisions.


Dominion -- A constraint solver generator

Abstract: This paper proposes a design for a system to generate constraint solvers that are specialised for specific problem models. It describes the design in detail and gives preliminary experimental results showing the feasibility and effectiveness of the approach.


Extraction of Flat and Nested Data Records from Web Pages

Abstract: This paper studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, it is useful to mine such data regions and data records in order to extract information from such web pages to provide value-added services. Currently available automatic techniques to mine data regions and data records from web pages are still unsatisfactory because of their poor performance. In this paper a novel method to identify and extract the flat and nested data records from the web pages automatically is proposed. It comprises of two steps : (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification and extraction of flat and nested data records from the data region of a web page automatically. For step1, a novel and more effective method is proposed, which finds the data regions formed by all types of tags using visual clues. For step2, a more effective and efficient method namely, Visual Clue based Extraction of web Data (VCED), is proposed, which extracts each record from the data region and identifies it whether it is a flat or nested data record based on visual clue information the area covered by and the number of data items present in each record. Our experimental results show that the proposed technique is effective and better than existing techniques.


From Sylvester-Gallai Configurations to Rank Bounds: Improved Black-box Identity Test for Depth-3 Circuits

Abstract: We study the problem of identity testing for depth-3 circuits of top fanin k and degree d. We give a new structure theorem for such identities. A direct application of our theorem improves the known deterministic d^{k^k}-time black-box identity test over rationals (Kayal-Saraf, FOCS 2009) to one that takes d^{k^2}-time. Our structure theorem essentially says that the number of independent variables in a real depth-3 identity is very small. This theorem settles affirmatively the stronger rank conjectures posed by Dvir-Shpilka (STOC 2005) and Kayal-Saraf (FOCS 2009). Our techniques provide a unified framework that actually beats all known rank bounds and hence gives the best running time (for every field) for black-box identity tests. Our main theorem (almost optimally) pins down the relation between higher dimensional Sylvester-Gallai theorems and the rank of depth-3 identities in a very transparent manner. The existence of this was hinted at by Dvir-Shpilka (STOC 2005), but first proven, for reals, by Kayal-Saraf (FOCS 2009). We introduce the concept of Sylvester-Gallai rank bounds for any field, and show the intimate connection between this and depth-3 identity rank bounds. We also prove the first ever theorem about high dimensional Sylvester-Gallai configurations over any field. Our proofs and techniques are very different from previous results and devise a very interesting ensemble of combinatorics and algebra. The latter concepts are ideal theoretic and involve a new Chinese remainder theorem. Our proof methods explain the structure of any depth-3 identity C: there is a nucleus of C that forms a low rank identity, while the remainder is a high dimensional Sylvester-Gallai configuration.


Usages et conception des TIC : Proposition d'un mod\`ele d'aide \`a la repr\'esentation de probl\`eme de conception

Abstract: This paper considers economic intelligence contribution to exploit individual and collective images of change, in ICT design decision-making. Technical devices meeting with real use situations often gives the opportunity to emerge mental images, that a innovation process, through its unprecedented nature, can not anticipate. Although methodologies exists for quality and design project management, the survey we conduct among small ICT publishers, show how they are not very suitable for small firms. This elements taken into account, we try to build a proposition of exploration ? analyze ? sum up process, adapted to this type of actors decisional process.


Maximal f-vectors of Minkowski sums of large numbers of polytopes

Abstract: It is known that in the Minkowski sum of $r$ polytopes in dimension $d$, with $r<d$, the number of vertices of the sum can potentially be as high as the product of the number of vertices in each summand. However, the number of vertices for sums of more polytopes was unknown so far. In this paper, we study sums of polytopes in general orientations, and show a linear relation between the number of faces of a sum of $r$ polytopes in dimension $d$, with $r\geq d$, and the number of faces in the sums of less than $d$ of the summand polytopes. We deduce from this exact formula a tight bound on the maximum possible number of vertices of the Minkowski sum of any number of polytopes in any dimension. In particular, the linear relation implies that a sum of $r$ polytopes in dimension $d$ has a number of vertices in $O(n^{d-1})$ of the total number of vertices in the summands, even when $r\geq d$. This bound is tight, in the sense that some sums do have that many vertices.


Optimal and Cut-free Tableaux for Propositional Dynamic Logic with Converse

Abstract: We give an optimal (EXPTIME), sound and complete tableau-based algorithm for deciding satisfiability for propositional dynamic logic with converse (CPDL) which does not require the use of analytic cut. Our main contribution is a sound methodto combine our previous optimal method for tracking least fix-points in PDL with our previous optimal method for handling converse in the description logic ALCI. The extension is non-trivial as the two methods cannot be combined naively. We give sufficient details to enable an implementation by others. Our OCaml implementation seems to be the first theorem prover for CPDL.


Logical Evaluation of Consciousness: For Incorporating Consciousness into Machine Architecture

Abstract: Machine Consciousness is the study of consciousness in a biological, philosophical, mathematical and physical perspective and designing a model that can fit into a programmable system architecture. Prime objective of the study is to make the system architecture behave consciously like a biological model does. Present work has developed a feasible definition of consciousness, that characterizes consciousness with four parameters i.e., parasitic, symbiotic, self referral and reproduction. Present work has also developed a biologically inspired consciousness architecture that has following layers: quantum layer, cellular layer, organ layer and behavioral layer and traced the characteristics of consciousness at each layer. Finally, the work has estimated physical and algorithmic architecture to devise a system that can behave consciously.


Modeling of 2D and 3D Assemblies Taking Into Account Form Errors of Plane Surfaces

Abstract: The tolerancing process links the virtual and the real worlds. From the former, tolerances define a variational geometrical language (geometric parameters). From the latter, there are values limiting those parameters. The beginning of a tolerancing process is in this duality. As high precision assemblies cannot be analyzed with the assumption that form errors are negligible, we propose to apply this process to assemblies with form errors through a new way of allowing to parameterize forms and solve their assemblies. The assembly process is calculated through a method of allowing to solve the 3D assemblies of pairs of surfaces having form errors using a static equilibrium. We have built a geometrical model based on the modal shapes of the ideal surface. We compute for the completely deterministic contact points between this pair of shapes according to a given assembly process. The solution gives an accurate evaluation of the assembly performance. Then we compare the results with or without taking into account the form errors. When we analyze a batch of assemblies, the problem is to compute for the nonconformity rate of a pilot production according to the functional requirements. We input probable errors of surfaces (position, orientation, and form) in our calculus and we evaluate the quality of the results compared with the functional requirements. The pilot production then can or cannot be validated.


Extraction de termes, reconnaissance et labellisation de relations dans un th\'esaurus

Abstract: Within the documentary system domain, the integration of thesauri for indexing and retrieval information steps is usual. In libraries, documents own rich descriptive information made by librarians, under descriptive notice based on Rameau thesaurus. We exploit two kinds of information in order to create a first semantic structure. A step of conceptualization allows us to define the various modules used to automatically build the semantic structure of the indexation work. Our current work focuses on an approach that aims to define an ontology based on a thesaurus. We hope to integrate new knowledge characterizing the territory of our structure (adding "toponyms" and links between concepts) thanks to a geographic information system (GIS).


Construction et enrichissement automatique d'ontologie \`a partir de ressources externes

Abstract: Automatic construction of ontologies from text is generally based on retrieving text content. For a much more rich ontology we extend these approaches by taking into account the document structure and some external resources (like thesaurus of indexing terms of near domain). In this paper we describe how these external resources are at first analyzed and then exploited. This method has been applied on a geographical domain and the benefit has been evaluated.


Caract\'erisation des d\'efauts d'une surface sph\'erique par d\'ecomposition modale

Abstract: The [ISO 1101] standard specifies the form errors with geometrical tolerances using the zone concept.To complete this concept, we present a generic method which adapts to any geometry and allows to describe any kind of errors. Thus,we can dissociate the part errors according to reference categories: position, orientation,form, waviness and roughnesses. Starting from a cloud of poinds representing the error measurement, the "modal" method decompose, like Fourier series,this error in a sum of sorted errors according to the ircomplexity degree (a number of "wavinesses"). In addition, we propose to show, on a simple example, that according to error complexity to be characterized, an interpolation by the modal method allows to optimize the measuring strategy.


A proposition of 3D inertial tolerancing to consider the statistical combination of the location and orientation deviations

Abstract: Tolerancing of assembly mechanisms is a major interest in the product life cycle. One can distinguish several models with growing complexity, from 1-dimensional (1D) to 3-dimensional (3D) (including form deviations), and two main tolerancing assumptions, the worst case and the statistical hypothesis. This paper presents an approach to 3D statistical tolerancing using a new acceptance criterion. Our approach is based on the 1D inertial acceptance criterion that is extended to 3D and form acceptance. The modal characterisation is used to describe the form deviation of a geometry as the combination of elementary deviations (location, orientation and form). The proposed 3D statistical tolerancing is applied on a simple mechanism with lever arm. It is also compared to the traditional worst-case tolerancing using a tolerance zone.


Optimization of a Classical Stamping Progression by Modal Correction of Anisotropy Ears

Abstract: This work is a development from the Inetforsmep European project. We proposed to realize a global optimization of a deep drawing industrial progression (made of several stages) for a cup manufacture. The objectives of the process were the thickness decrease and the geometrical parameters (especially the height). This paper improves on this previous work in the aim of mastering the contour error. From the optimal configuration, we expect to cut down the amount of the needed material and the number of forming operations. Our action is focused on the appearance of unexpected undulations (ears) located on the rim of the cups during forming due to a nonuniform crystallographic texture. Those undulations can cause a significant amount of scraps, productivity loss, and cost during manufacture. In this paper, this phenomenon causes the use of four forming operations for the cup manufacture. The aim is to cut down from four to two forming stages by defining an optimal blank (size and shape). The advantage is to reduce the cost of the tool manufacturing and to minimize the needed material (by suppressing the part flange). The chosen approach consists in defining a particular description of the ears' part by modal decomposition and then simulating several blank shapes and sizes generated by discrete cosine transformation (DCT). The use of a numerical simulation for the forming operation and the design of an experiment technique allow mathematical links between the ears' formation and the DCT coefficients. An optimization is then possible by using mathematical links. This original approach leads the ears' amplitude to be reduced by a factor of 10, with only 15 numerical experiments. Moreover, we have limited the number of forming stages from 4 to 2 with a minimal material use.


Inertial tolerancing and capability indices in an assembly production

Abstract: Traditional tolerancing considers the conformity of a batch when the batch satisfies the specifications. The characteristic is considered for itself and not according to its incidence in the assembly. Inertial tolerancing proposes another alternative of tolerancing in order to guarantee the final assembly characteristic. The inertia I2 = \sqrt{\delta^2 + \sigma^2} is not toleranced by a tolerance interval but by a scalar representing the maximum inertia that the characteristic should not exceed. We detail how to calculate the inertial tolerances according to two cases, one aims to guarantee an inertia of the assembly characteristic the other a tolerance interval on the assembly characteristic by a Cpk capability index, in the particular but common case of uniform tolerances or more general with non uniform tolerances. An example will be detailed to show the results of the different tolerancing methods.


Dendritic Cells for SYN Scan Detection

Abstract: Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and key to activation of the human immune system, behaviour which has been abstracted to form the Dendritic Cell Algorithm (DCA). In algorithmic terms, individual DCs perform multi-sensor data fusion, asynchronously correlating the the fused data signals with a secondary data stream. Aggregate output of a population of cells, is analysed and forms the basis of an anomaly detection system. In this paper the DCA is applied to the detection of outgoing port scans using TCP SYN packets. Results show that detection can be achieved with the DCA, yet some false positives can be encountered when simultaneously scanning and using other network services. Suggestions are made for using adaptive signals to alleviate this uncovered problem.


Systems of Linear Equations over $\mathbb{F}_2$ and Problems Parameterized Above Average

Abstract: In the problem Max Lin, we are given a system $Az=b$ of $m$ linear equations with $n$ variables over $\mathbb{F}_2$ in which each equation is assigned a positive weight and we wish to find an assignment of values to the variables that maximizes the excess, which is the total weight of satisfied equations minus the total weight of falsified equations. Using an algebraic approach, we obtain a lower bound for the maximum excess. Max Lin Above Average (Max Lin AA) is a parameterized version of Max Lin introduced by Mahajan et al. (Proc. IWPEC'06 and J. Comput. Syst. Sci. 75, 2009). In Max Lin AA all weights are integral and we are to decide whether the maximum excess is at least $k$, where $k$ is the parameter. It is not hard to see that we may assume that no two equations in $Az=b$ have the same left-hand side and $n={\rm rank A}$. Using our maximum excess results, we prove that, under these assumptions, Max Lin AA is fixed-parameter tractable for a wide special case: $m\le 2^{p(n)}$ for an arbitrary fixed function $p(n)=o(n)$. Max $r$-Lin AA is a special case of Max Lin AA, where each equation has at most $r$ variables. In Max Exact $r$-SAT AA we are given a multiset of $m$ clauses on $n$ variables such that each clause has $r$ variables and asked whether there is a truth assignment to the $n$ variables that satisfies at least $(1-2^{-r})m + k2^{-r}$ clauses. Using our maximum excess results, we prove that for each fixed $r\ge 2$, Max $r$-Lin AA and Max Exact $r$-SAT AA can be solved in time $2^{O(k \log k)}+m^{O(1)}.$ This improves $2^{O(k^2)}+m^{O(1)}$-time algorithms for the two problems obtained by Gutin et al. (IWPEC 2009) and Alon et al. (SODA 2010), respectively.


A Data Capsule Framework For Web Services: Providing Flexible Data Access Control To Users

Abstract: This paper introduces the notion of a secure data capsule, which refers to an encapsulation of sensitive user information (such as a credit card number) along with code that implements an interface suitable for the use of such information (such as charging for purchases) by a service (such as an online merchant). In our capsule framework, users provide their data in the form of such capsules to web services rather than raw data. Capsules can be deployed in a variety of ways, either on a trusted third party or the user's own computer or at the service itself, through the use of a variety of hardware or software modules, such as a virtual machine monitor or trusted platform module: the only requirement is that the deployment mechanism must ensure that the user's data is only accessed via the interface sanctioned by the user. The framework further allows an user to specify policies regarding which services or machines may host her capsule, what parties are allowed to access the interface, and with what parameters. The combination of interface restrictions and policy control lets us bound the impact of an attacker who compromises the service to gain access to the user's capsule or a malicious insider at the service itself.


A Grey-Box Approach to Automated Mechanism Design

Abstract: Auctions play an important role in electronic commerce, and have been used to solve problems in distributed computing. Automated approaches to designing effective auction mechanisms are helpful in reducing the burden of traditional game theoretic, analytic approaches and in searching through the large space of possible auction mechanisms. This paper presents an approach to automated mechanism design (AMD) in the domain of double auctions. We describe a novel parametrized space of double auctions, and then introduce an evolutionary search method that searches this space of parameters. The approach evaluates auction mechanisms using the framework of the TAC Market Design Game and relates the performance of the markets in that game to their constituent parts using reinforcement learning. Experiments show that the strongest mechanisms we found using this approach not only win the Market Design Game against known, strong opponents, but also exhibit desirable economic properties when they run in isolation.


Face Recognition by Fusion of Local and Global Matching Scores using DS Theory: An Evaluation with Uni-classifier and Multi-classifier Paradigm

Abstract: Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore decoupling the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. This paper presents a robust face recognition technique based on the extraction and matching of SIFT features related to independent face areas. Both a global and local (as recognition from parts) matching strategy is proposed. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. In order to reduce the identification errors, the Dempster-Shafer decision theory is applied to fuse the two matching techniques. The proposed algorithms are evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition techniques also in the case of partially occluded faces or with missing information.


Feature Level Clustering of Large Biometric Database

Abstract: This paper proposes an efficient technique for partitioning large biometric database during identification. In this technique feature vector which comprises of global and local descriptors extracted from offline signature are used by fuzzy clustering technique to partition the database. As biometric features posses no natural order of sorting, thus it is difficult to index them alphabetically or numerically. Hence, some supervised criteria is required to partition the search space. At the time of identification the fuzziness criterion is introduced to find the nearest clusters for declaring the identity of query sample. The system is tested using bin-miss rate and performs better in comparison to traditional k-means approach.


Face Identification by SIFT-based Complete Graph Topology

Abstract: This paper presents a new face identification system based on Graph Matching Technique on SIFT features extracted from face images. Although SIFT features have been successfully used for general object detection and recognition, only recently they were applied to face recognition. This paper further investigates the performance of identification techniques based on Graph matching topology drawn on SIFT features which are invariant to rotation, scaling and translation. Face projections on images, represented by a graph, can be matched onto new images by maximizing a similarity function taking into account spatial distortions and the similarities of the local features. Two graph based matching techniques have been investigated to deal with false pair assignment and reducing the number of features to find the optimal feature set between database and query face SIFT features. The experimental results, performed on the BANCA database, demonstrate the effectiveness of the proposed system for automatic face identification.


SIFT-based Ear Recognition by Fusion of Detected Keypoints from Color Similarity Slice Regions

Abstract: Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT) as feature descriptor for structural representation of ear images. In order to make it more robust to user authentication, only the regions having color probabilities in a certain ranges are considered for invariant SIFT feature extraction, where the K-L divergence is used for keeping color consistency. Ear skin color model is formed by Gaussian mixture model and clustering the ear color pattern using vector quantization. Finally, K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of reference model and probe ear images. After segmentation of ear images in some color slice regions, SIFT keypoints are extracted and an augmented vector of extracted SIFT features are created for matching, which is accomplished between a pair of reference model and probe ear images. The proposed technique has been tested on the IITK Ear database and the experimental results show improvements in recognition accuracy while invariant features are extracted from color slice regions to maintain the robustness of the system.


Feature Level Fusion of Biometrics Cues: Human Identification with Doddingtons Caricature

Abstract: This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The fused set is encoded by K-medoids partitioning approach with less number of feature points in the set. K-medoids partition the whole dataset into clusters to minimize the error between data points belonging to the clusters and its center. Reduced feature set is used to match between two biometric sets. Matching scores are generated using wolf-lamb user-dependent feature weighting scheme introduced by Doddington. The technique is tested to exhibit its robust performance.


Fusion of Multiple Matchers using SVM for Offline Signature Identification

Abstract: This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising.


Detecting Motifs in System Call Sequences

Abstract: The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify unknown motifs which repeat within time series data. The power of the algorithm is derived from its use of a small number of parameters with minimal assumptions. The algorithm searches from a completely neutral perspective that is independent of the data being analysed, and the underlying motifs. In this paper the motif tracking algorithm is applied to the search for patterns within sequences of low level system calls between the Linux kernel and the operating system's user space. The MTA is able to compress data found in large system call data sets to a limited number of motifs which summarise that data. The motifs provide a resource from which a profile of executed processes can be built. The potential for these profiles and new implications for security research are highlighted. A higher level call system language for measuring similarity between patterns of such calls is also suggested.


Some improved results on communication between information systems

Abstract: To study the communication between information systems, Wang et al. [C. Wang, C. Wu, D. Chen, Q. Hu, and C. Wu, Communicating between information systems, Information Sciences 178 (2008) 3228-3239] proposed two concepts of type-1 and type-2 consistent functions. Some properties of such functions and induced relation mappings have been investigated there. In this paper, we provide an improvement of the aforementioned work by disclosing the symmetric relationship between type-1 and type-2 consistent functions. We present more properties of consistent functions and induced relation mappings and improve upon several deficient assertions in the original work. In particular, we unify and extend type-1 and type-2 consistent functions into the so-called neighborhood-consistent functions. This provides a convenient means for studying the communication between information systems based on various neighborhoods.


\'Etude et traitement automatique de l'anglais du XVIIe si\`ecle : outils morphosyntaxiques et dictionnaires

Abstract: In this article, we record the main linguistic differences or singularities of 17th century English, analyse them morphologically and syntactically and propose equivalent forms in contemporary English. We show how 17th century texts may be transcribed into modern English, combining the use of electronic dictionaries with rules of transcription implemented as transducers. Apr\`es avoir expos\'e la constitution du corpus, nous recensons les principales diff\'erences ou particularit\'es linguistiques de la langue anglaise du XVIIe si\`ecle, les analysons du point de vue morphologique et syntaxique et proposons des \'equivalents en anglais contemporain (AC). Nous montrons comment nous pouvons effectuer une transcription automatique de textes anglais du XVIIe si\`ecle en anglais moderne, en combinant l'utilisation de dictionnaires \'electroniques avec des r\`egles de transcriptions impl\'ement\'ees sous forme de transducteurs.


"Mind your p's and q's": or the peregrinations of an apostrophe in 17th Century English

Abstract: If the use of the apostrophe in contemporary English often marks the Saxon genitive, it may also indicate the omission of one or more let-ters. Some writers (wrongly?) use it to mark the plural in symbols or abbreviations, visual-ised thanks to the isolation of the morpheme "s". This punctuation mark was imported from the Continent in the 16th century. During the 19th century its use was standardised. However the rules of its usage still seem problematic to many, including literate speakers of English. "All too often, the apostrophe is misplaced", or "errant apostrophes are springing up every-where" is a complaint that Internet users fre-quently come across when visiting grammar websites. Many of them detail its various uses and misuses, and attempt to correct the most common mistakes about it, especially its mis-use in the plural, called greengrocers' apostro-phes and humorously misspelled "greengro-cers apostrophe's". While studying English travel accounts published in the seventeenth century, we noticed that the different uses of this symbol may accompany various models of metaplasms. We were able to highlight the linguistic variations of some lexemes, and trace the origin of modern grammar rules gov-erning its usage.


Recognition and translation Arabic-French of Named Entities: case of the Sport places

Abstract: The recognition of Arabic Named Entities (NE) is a problem in different domains of Natural Language Processing (NLP) like automatic translation. Indeed, NE translation allows the access to multilingual in-formation. This translation doesn't always lead to expected result especially when NE contains a person name. For this reason and in order to ameliorate translation, we can transliterate some part of NE. In this context, we propose a method that integrates translation and transliteration together. We used the linguis-tic NooJ platform that is based on local grammars and transducers. In this paper, we focus on sport domain. We will firstly suggest a refinement of the typological model presented at the MUC Conferences we will describe the integration of an Arabic transliteration module into translation system. Finally, we will detail our method and give the results of the evaluation.


VRAC: Theory #1

Abstract: In order to make full use of geographic routing techniques developed for sensor networks, nodes must be localized. However, traditional localization and virtual localization techniques are dependent either on expensive and sometimes unavailable hardware (e.g. GPS) or on sophisticated localization calculus (e.g. triangulation) which are both error-prone and with a costly overhead. Instead of actually localizing nodes in the physical two-dimensional Euclidean space, we use directly the raw distance to a set of anchors to produce multi-dimensional coordinates. We prove that the image of the physical two-dimensional Euclidean space is a two-dimensional surface, and we show that it is possible to adapt geographic routing strategies on this surface, simply, efficiently and successfully.


Morphological study of Albanian words, and processing with NooJ

Abstract: We are developing electronic dictionaries and transducers for the automatic processing of the Albanian Language. We will analyze the words inside a linear segment of text. We will also study the relationship between units of sense and units of form. The composition of words takes different forms in Albanian. We have found that morphemes are frequently concatenated or simply juxtaposed or contracted. The inflected grammar of NooJ allows constructing the dictionaries of flexed forms (declensions or conjugations). The diversity of word structures requires tools to identify words created by simple concatenation, or to treat contractions. The morphological tools of NooJ allow us to create grammatical tools to represent and treat these phenomena. But certain problems exceed the morphological analysis and must be represented by syntactical grammars.


Miniaturized wireless sensor network

Abstract: This paper addresses an overview of the wireless sensor networks. It is shown that MEMS/NEMS technologies and SIP concept are well suited for advanced architectures. It is also shown analog architectures have to be compatible with digital signal techniques to develop smart network of microsystem.


Software defined radio layer for IR-UWB systems in Wireless Sensor Network Context

Abstract: This paper addresses the radio interface problematic for MANET (Mobile Ad-hoc NETwork) applications. Here we propose to study the radio reconfigurability in order to provide a unique physical layer which is able to deal with all MANET applications. For implementing this reconfigurable physical layer, we propose to use Impulse Radio Ultra WideBand (IRUWB). This paper presents also our two level design approach for obtaining our reconfigurable IR-UWB receiver on FPGA (Field Programmable Gate Array).


Study of Reconfigurable Mostly Digital Radio for Manet

Abstract: We introduce the radio reconfigurability thanks to IRUWB mostly digital architecture for MANET context. This particular context implies some constraints on the radio interface such as low cost, low power, small dimensions and simplicity. Here, we propose an implementation of dynamic reconfigurable receiver on ASIC, and FPGA, after having explained the advantages of mostly digital radio for reconfigurability. In this paper, by studying our prototypes, we could prove that reconfigurability is on the contrary with MANET constraints needs. The proposed solution allows data rate, radio range, energy and spectrum occupation reconfigurability.


SOPC Co-Design Platform for UWB Systems in Wireless Sensor Network Context

Abstract: This paper presents our approach of the radio interface problematic for Wireless Sensor Network. We introduce the WSN context and constraints associated. We propose an IR-UWB solution and illustrate why it could be a viable solution for WSN. A high level modelling and simulation platform for IR-UWB radio interface is proposed on Matlab. It allows us to determine according to BER versus Eb/N0 criteria and the WSN constraints what kind of design is more adequate. Moreover, a co-design co-simulation platform Matlab VHDL is proposed here. Using this platform we designed IR-UWB transceiver having reconfigurable capabilities, such as data rate reconfiguration, time hopping code, spectrum occupation and radio range reconfiguration.


Individual focus and knowledge contribution

Abstract: Before contributing new knowledge, individuals must attain requisite background knowledge or skills through schooling, training, practice, and experience. Given limited time, individuals often choose either to focus on few areas, where they build deep expertise, or to delve less deeply and distribute their attention and efforts across several areas. In this paper we measure the relationship between the narrowness of focus and the quality of contribution across a range of both traditional and recent knowledge sharing media, including scholarly articles, patents, Wikipedia, and online question and answer forums. Across all systems, we observe a small but significant positive correlation between focus and quality.


Minimum and maximum against k lies

Abstract: A neat 1972 result of Pohl asserts that [3n/2]-2 comparisons are sufficient, and also necessary in the worst case, for finding both the minimum and the maximum of an n-element totally ordered set. The set is accessed via an oracle for pairwise comparisons. More recently, the problem has been studied in the context of the Renyi-Ulam liar games, where the oracle may give up to k false answers. For large k, an upper bound due to Aigner shows that (k+O(\sqrt{k}))n comparisons suffice. We improve on this by providing an algorithm with at most (k+1+C)n+O(k^3) comparisons for some constant C. The known lower bounds are of the form (k+1+c_k)n-D, for some constant D, where c_0=0.5, c_1=23/32=0.71875, and c_k=\Omega(2^{-5k/4}) as k goes to infinity.


Simulation Platform for Wireless Sensor Networks Based on Impulse Radio Ultra Wide Band

Abstract: Impulse Radio Ultra Wide Band (IR-UWB) is a promising technology to address Wireless Sensor Network (WSN) constraints. However, existing network simulation tools do not provide a complete WSN simulation architecture, with the IR-UWB specificities at the PHYsical (PHY) and the Medium Access Control (MAC) layers. In this paper, we propose a WSN simulation architecture based on the IR-UWB technique. At the PHY layer, we take into account the pulse collision by dealing with the pulse propagation delay. We also modelled MAC protocols specific to IRUWB, for WSN applications. To completely fit the WSN simulation requirements, we propose a generic and reusable sensor and sensing channel model. Most of the WSN application performances can be evaluated thanks to the proposed simulation architecture. The proposed models are implemented on a scalable and well known network simulator: Global Mobile Information System Simulator (GloMoSim). However, they can be reused for all other packet based simulation platforms.


Medium Access Control for Wireless Sensor Networks based on Impulse Radio Ultra Wideband

Abstract: This paper describes a detailed performance evaluation of distributed Medium Access Control (MAC) protocols for Wireless Sensor Networks based on Impulse Radio Ultra Wideband (IR-UWB) Physical layer (PHY). Two main classes of Medium Access Control protocol have been considered: Slotted and UnSlotted with reliability. The reliability is based on Automatic Repeat ReQuest (ARQ). The performance evaluation is performed using a complete Wireless Sensor Networks (WSN) simulator built on the Global Mobile Information System Simulator (GloMoSim). The optimal operating parameters are first discussed for IR-UWB in terms of slot size, retransmission delay and the number of retransmission, then a comparison between IR-UWB and other transmission techniques in terms of reliability latency and power efficiency.


Channel Capacity Limitations versus Hardware Implementation for UWB Impulse Radio Communications

Abstract: Starting from the Shannon channel capacity, we propose an IR-UWB channel capacity based on the delay spread for multipath time variant channels. This IR-UWB channel capacity is obtained from the no ISI (Inter Symbol Interference) assumption and for binary modulations. The impact of the kind of implementation is considered on the IR-UWB channel capacity. This study is lead for mixed and mostly digital implementation. The key parameters and theirs impacts on the channel capacity are exposed in each case: the data converters for mostly digital implementations and the pulse generator capabilities for mixed implementations. Finally, these two implementations are compared from a data rate point of view. Their behaviors regarding an increase of the operating frequency are also studied.


Performance Evaluation of Impluse Radio Ultra Wide Band Wireless Sensor Networks

Abstract: This paper presents a performance evaluation of Wireless Sensor Networks (WSN) based on Impulse Radio Ultra Wideband (IR-UWB) over a new simulation platform developed for this purpose. The simulation platform is built on an existing network simulator: Global Mobile Information System Simulator (GloMoSim). It mainly focuses on the accurately modeling of IR-UWB PHYsical (PHY) and Medium Access Control (MAC) layer. Pulse collision is modeled according to the used time hopping sequence (THS) and the pulse propagation delay in order to increase the simulation fidelity. It also includes a detection and identification application based on a new sensing channel and new sensor device models. The proposed architecture is generic so it can be reused for any simulation platform. The performance evaluation is based on one of the typical WSN applications: local area protection, where sensor nodes are densely scattered in an access regulated area in order to detect, identify and report non authorized accesses to a base station for analysis. Two networks topologies using different protocol stacks are investigated. Their performance evaluation is presented in terms of reliability and latency.


New methodology to design advanced MR-IRUWB communication system

Abstract: A new model is proposed giving the channel capability of a MB-IR-UWB system versus the number of subband and the duty cycle. The architecture simulated shows data rate ranging from 1.434 Gbits/s to 0.9 Gbits/s for 16 to 10 subbands and duty cycle ranging from 20% to 12%.


Recherche de relations spatio-temporelles : une m\'ethode bas\'ee sur l'analyse de corpus textuels

Abstract: This paper presents a work package realized for the G\'eOnto project. A new method is proposed for an enrichment of a first geographical ontology developed beforehand. This method relies on text analysis by lexico-syntactic patterns. From the retrieve of n-ary relations the method automatically detect those involved in a spatial and/or temporal relation in a context of a description of journeys.


An Optimal Algorithm for the Indirect Covering Subtree Problem

Abstract: We consider the indirect covering subtree problem (Kim et al., 1996). The input is an edge weighted tree graph along with customers located at the nodes. Each customer is associated with a radius and a penalty. The goal is to locate a tree-shaped facility such that the sum of setup and penalty cost is minimized. The setup cost equals the sum of edge lengths taken by the facility and the penalty cost is the sum of penalties of all customers whose distance to the facility exceeds their radius. The indirect covering subtree problem generalizes the single maximum coverage location problem on trees where the facility is a node rather than a subtree. Indirect covering subtree can be solved in $O(n\log^2 n)$ time (Kim et al., 1996). A slightly faster algorithm for single maximum coverage location with a running time of $O(n\log^2n/\log\log n)$ has been provided (Spoerhase and Wirth, 2009). We achieve time $O(n\log n)$ for indirect covering subtree thereby providing the fastest known algorithm for both problems. Our result implies also faster algorithms for competitive location problems such as $(1,X)$-medianoid and $(1,p)$-centroid on trees. We complement our result by a lower bound of $\Omega(n\log n)$ for single maximum coverage location and $(1,X)$-medianoid on a real-number RAM model showing that our algorithm is optimal in running time.


Performance Analysis of m-retry BEB based DCF under Unsaturated Traffic Condition

Abstract: The IEEE 802.11 standard offers a cheap and promising solution for small scale wireless networks. Due to the self configuring nature, WLANs do not require large scale infrastructure deployment, and are scalable and easily maintainable which incited its popularity in both literature and industry. In real environment, these networks operate mostly under unsaturated condition. We investigate performance of such a network with m-retry limit BEB based DCF. We consider imperfect channel with provision for power capture. Our method employs a Markov model and represents the most common performance measures in terms of network parameters making the model and mathematical analysis useful in network design and planning. We also explore the effects of packet error, network size, initial contention window, and retry limit on overall performance of WLANs.


FORMT: Form-based Mutation Testing of Logical Specifications

Abstract: The draft paper defines a system, which is capable of maintaining bases of test cases for logical specifications. The specifications, which are subject to this system are transformed from their original shape in first-order logic to form-based expressions as originally introduced in logics of George Spencer-Brown. The innovation comes from the operations the system provides when injecting faults - so-called mutations - to the specifications. The system presented here applies to logical specifications from areas as different as programming, ontologies or hardware specifications.


IR-UWB Channel Capacity for Analog and Mostly Digital Implementation

Abstract: The impact of the type of implementation is considered on the IR-UWB channel capacity. This study is lead for analog and mostly digital implementation. Key parameters and theirs impacts on the channel capacity are exposed in each case: data converters for mostly digital implementations and pulse generators capabilities for analog implementations. These two implementations are compared from a data rate point of view. Their behaviors regarding an increase of the operating frequency are also studied


Detecting Danger: Applying a Novel Immunological Concept to Intrusion Detection Systems

Abstract: In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, anti-virus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, have focused on the human immune system (HIS). The human immune system provides a high level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will improve the performance of real intrusion detection systems. This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological paradigm, Danger Theory, and how this concept is inspiring artificial immune systems (AIS). Applications within the context of computer security are outlined drawing direct reference to the underlying principles of Danger Theory and finally, the current state of intrusion detection systems is discussed and improvements suggested.


Simplifying Parallelization of Scientific Codes by a Function-Centric Approach in Python

Abstract: The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallel communication is implemented. We provide specific examples on such layers of code, and these examples may act as templates for parallelizing a wide set of serial scientific codes. The use of Python for parallelization is motivated by the fact that the language is well suited for reusing existing serial codes programmed in other languages. The extreme flexibility of Python with regard to handling functions makes it very easy to wrap up decomposed computational tasks of a serial scientific application as Python functions. Many parallelization-specific components can be implemented as generic Python functions, which may take as input those functions that perform concrete computational tasks. The overall programming effort needed by this parallelization approach is rather limited, and the resulting parallel Python scripts have a compact and clean structure. The usefulness of the parallelization approach is exemplified by three different classes of applications in natural and social sciences.


Aggregating Algorithm competing with Banach lattices

Abstract: The paper deals with on-line regression settings with signals belonging to a Banach lattice. Our algorithms work in a semi-online setting where all the inputs are known in advance and outcomes are unknown and given step by step. We apply the Aggregating Algorithm to construct a prediction method whose cumulative loss over all the input vectors is comparable with the cumulative loss of any linear functional on the Banach lattice. As a by-product we get an algorithm that takes signals from an arbitrary domain. Its cumulative loss is comparable with the cumulative loss of any predictor function from Besov and Triebel-Lizorkin spaces. We describe several applications of our setting.


Performance and Stability of the Chelonia Storage Cloud

Abstract: In this paper we present the Chelonia storage cloud middleware. It was designed to fill the requirements gap between those of large, sophisticated scientific collaborations which have adopted the grid paradigm for their distributed storage needs, and of corporate business communities which are gravitating towards the cloud paradigm. The similarities to and differences between Chelonia and several well-known grid- and cloud-based storage solutions are commented. The design of Chelonia has been chosen to optimize high reliability and scalability of an integrated system of heterogeneous, geographically dispersed storage sites and the ability to easily expand the system dynamically. The architecture and implementation in term of web-services running inside the Advanced Resource Connector Hosting Environment Dameon (ARC HED) are described. We present results of tests in both local-area and wide-area networks that demonstrate the fault-tolerance, stability and scalability of Chelonia.


Gradual sub-lattice reduction and a new complexity for factoring polynomials

Abstract: We present a lattice algorithm specifically designed for some classical applications of lattice reduction. The applications are for lattice bases with a generalized knapsack-type structure, where the target vectors are boundably short. For such applications, the complexity of the algorithm improves traditional lattice reduction by replacing some dependence on the bit-length of the input vectors by some dependence on the bound for the output vectors. If the bit-length of the target vectors is unrelated to the bit-length of the input, then our algorithm is only linear in the bit-length of the input entries, which is an improvement over the quadratic complexity floating-point LLL algorithms. To illustrate the usefulness of this algorithm we show that a direct application to factoring univariate polynomials over the integers leads to the first complexity bound improvement since 1984. A second application is algebraic number reconstruction, where a new complexity bound is obtained as well.


Using CODEQ to Train Feed-forward Neural Networks

Abstract: CODEQ is a new, population-based meta-heuristic algorithm that is a hybrid of concepts from chaotic search, opposition-based learning, differential evolution and quantum mechanics. CODEQ has successfully been used to solve different types of problems (e.g. constrained, integer-programming, engineering) with excellent results. In this paper, CODEQ is used to train feed-forward neural networks. The proposed method is compared with particle swarm optimization and differential evolution algorithms on three data sets with encouraging results.


Approximations to the MMI criterion and their effect on lattice-based MMI

Abstract: Maximum mutual information (MMI) is a model selection criterion used for hidden Markov model (HMM) parameter estimation that was developed more than twenty years ago as a discriminative alternative to the maximum likelihood criterion for HMM-based speech recognition. It has been shown in the speech recognition literature that parameter estimation using the current MMI paradigm, lattice-based MMI, consistently outperforms maximum likelihood estimation, but this is at the expense of undesirable convergence properties. In particular, recognition performance is sensitive to the number of times that the iterative MMI estimation algorithm, extended Baum-Welch, is performed. In fact, too many iterations of extended Baum-Welch will lead to degraded performance, despite the fact that the MMI criterion improves at each iteration. This phenomenon is at variance with the analogous behavior of maximum likelihood estimation -- at least for the HMMs used in speech recognition -- and it has previously been attributed to `over fitting'. In this paper, we present an analysis of lattice-based MMI that demonstrates, first of all, that the asymptotic behavior of lattice-based MMI is much worse than was previously understood, i.e. it does not appear to converge at all, and, second of all, that this is not due to `over fitting'. Instead, we demonstrate that the `over fitting' phenomenon is the result of standard methodology that exacerbates the poor behavior of two key approximations in the lattice-based MMI machinery. We also demonstrate that if we modify the standard methodology to improve the validity of these approximations, then the convergence properties of lattice-based MMI become benign without sacrificing improvements to recognition accuracy.


Maximum $\Delta$-edge-colorable subgraphs of class II graphs

Abstract: A graph $G$ is class II, if its chromatic index is at least $\Delta+1$. Let $H$ be a maximum $\Delta$-edge-colorable subgraph of $G$. The paper proves best possible lower bounds for $\frac{|E(H)|}{|E(G)|}$, and structural properties of maximum $\Delta$-edge-colorable subgraphs. It is shown that every set of vertex-disjoint cycles of a class II graph with $\Delta\geq3$ can be extended to a maximum $\Delta$-edge-colorable subgraph. Simple graphs have a maximum $\Delta$-edge-colorable subgraph such that the complement is a matching. Furthermore, a maximum $\Delta$-edge-colorable subgraph of a simple graph is always class I.


Towards Social Profile Based Overlays

Abstract: Online social networking has quickly become one of the most common activities of Internet users. As social networks evolve, they encourage users to share more information, requiring the users, in turn, to place more trust into social networks. Peer-to-peer (P2P) overlays provide an environment that can return ownership of information, trust, and control to the users, away from centralized third-party social networks. In this paper, we present a novel concept, social profile overlays, which enable users to share their profile only with trusted peers in a scalable, reliable, and private manner. Each user's profile consists of a unique private, secure overlay, where members of that overlay have a friendship with the overlay owner. Profile data is made available without regard to the online state of the profile owner through the use of the profile overlay's distributed data store. Privacy and security are enforced through the use of a public key infrastructure (PKI), where the role of certificate authority (CA) is handled by the overlay owner and each member of the overlay has a CA-signed certificate. All members of the social network join a common public or directory overlay facilitating friend discovery and bootstrap connections into profile overlays. We define interfaces and present tools that can be used to implement this system, as well as explore some of the challenges related to it.


MADMX: A Novel Strategy for Maximal Dense Motif Extraction

Abstract: We develop, analyze and experiment with a new tool, called MADMX, which extracts frequent motifs, possibly including don't care characters, from biological sequences. We introduce density, a simple and flexible measure for bounding the number of don't cares in a motif, defined as the ratio of solid (i.e., different from don't care) characters to the total length of the motif. By extracting only maximal dense motifs, MADMX reduces the output size and improves performance, while enhancing the quality of the discoveries. The efficiency of our approach relies on a newly defined combining operation, dubbed fusion, which allows for the construction of maximal dense motifs in a bottom-up fashion, while avoiding the generation of nonmaximal ones. We provide experimental evidence of the efficiency and the quality of the motifs returned by MADMX


On Event Structure in the Torn Dress

Abstract: Using Pustejovsky's "The Syntax of Event Structure" and Fong's "On Mending a Torn Dress" we give a glimpse of a Pustejovsky-like analysis to some example sentences in Fong. We attempt to give a framework for semantics to the noun phrases and adverbs as appropriate as well as the lexical entries for all words in the examples and critique both papers in light of our findings and difficulties.


Homomorphisms between fuzzy information systems revisited

Abstract: Recently, Wang et al. discussed the properties of fuzzy information systems under homomorphisms in the paper [C. Wang, D. Chen, L. Zhu, Homomorphisms between fuzzy information systems, Applied Mathematics Letters 22 (2009) 1045-1050], where homomorphisms are based upon the concepts of consistent functions and fuzzy relation mappings. In this paper, we classify consistent functions as predecessor-consistent and successor-consistent, and then proceed to present more properties of consistent functions. In addition, we improve some characterizations of fuzzy relation mappings provided by Wang et al.


Towards a Unified Framework for Declarative Structured Communications

Abstract: We present a unified framework for the declarative analysis of structured communications. By relying on a (timed) concurrent constraint programming language, we show that in addition to the usual operational techniques from process calculi, the analysis of structured communications can elegantly exploit logic-based reasoning techniques. We introduce a declarative interpretation of the language for structured communications proposed by Honda, Vasconcelos, and Kubo. Distinguishing features of our approach are: the possibility of including partial information (constraints) in the session model; the use of explicit time for reasoning about session duration and expiration; a tight correspondence with logic, which formally relates session execution and linear-time temporal logic formulas.


Session-Based Programming for Parallel Algorithms: Expressiveness and Performance

Abstract: This paper investigates session programming and typing of benchmark examples to compare productivity, safety and performance with other communications programming languages. Parallel algorithms are used to examine the above aspects due to their extensive use of message passing for interaction, and their increasing prominence in algorithmic research with the rising availability of hardware resources such as multicore machines and clusters. We contribute new benchmark results for SJ, an extension of Java for type-safe, binary session programming, against MPJ Express, a Java messaging system based on the MPI standard. In conclusion, we observe that (1) despite rich libraries and functionality, MPI remains a low-level API, and can suffer from commonly perceived disadvantages of explicit message passing such as deadlocks and unexpected message types, and (2) the benefits of high-level session abstraction, which has significant impact on program structure to improve readability and reliability, and session type-safety can greatly facilitate the task of communications programming whilst retaining competitive performance.


Execution Models for Choreographies and Cryptoprotocols

Abstract: A choreography describes a transaction in which several principals interact. Since choreographies frequently describe business processes affecting substantial assets, we need a security infrastructure in order to implement them safely. As part of a line of work devoted to generating cryptoprotocols from choreographies, we focus here on the execution models suited to the two levels. We give a strand-style semantics for choreographies, and propose a special execution model in which choreography-level messages are faithfully delivered exactly once. We adapt this model to handle multiparty protocols in which some participants may be compromised. At level of cryptoprotocols, we use the standard Dolev-Yao execution model, with one alteration. Since many implementations use a "nonce cache" to discard multiply delivered messages, we provide a semantics for at-most-once delivery.


Programming Idioms for Transactional Events

Abstract: Transactional events (TE) are an extension of Concurrent ML (CML), a programming model for synchronous message-passing. Prior work has focused on TE's formal semantics and its implementation. This paper considers programming idioms, particularly those that vary unexpectedly from the corresponding CML idioms. First, we solve a subtle problem with client-server protocols in TE. Second, we argue that CML's wrap and guard primitives do not translate well to TE, and we suggest useful workarounds. Finally, we discuss how to rewrite CML protocols that use abort actions.


Towards the Safe Programming of Wireless Sensor Networks

Abstract: Sensor networks are rather challenging to deploy, program, and debug. Current programming languages for these platforms suffer from a significant semantic gap between their specifications and underlying implementations. This fact precludes the development of (type-)safe applications, which would potentially simplify the task of programming and debugging deployed networks. In this paper we define a core calculus for programming sensor networks and propose to use it as an assembly language for developing type-safe, high-level programming languages.


Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

Abstract: The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research.


A Concurrent Language with a Uniform Treatment of Regions and Locks

Abstract: A challenge for programming language research is to design and implement multi-threaded low-level languages providing static guarantees for memory safety and freedom from data races. Towards this goal, we present a concurrent language employing safe region-based memory management and hierarchical locking of regions. Both regions and locks are treated uniformly, and the language supports ownership transfer, early deallocation of regions and early release of locks in a safe manner.


Type Inference for Deadlock Detection in a Multithreaded Polymorphic Typed Assembly Language

Abstract: We previously developed a polymorphic type system and a type checker for a multithreaded lock-based polymorphic typed assembly language (MIL) that ensures that well-typed programs do not encounter race conditions. This paper extends such work by taking into consideration deadlocks. The extended type system verifies that locks are acquired in the proper order. Towards this end we require a language with annotations that specify the locking order. Rather than asking the programmer (or the compiler's backend) to specifically annotate each newly introduced lock, we present an algorithm to infer the annotations. The result is a type checker whose input language is non-decorated as before, but that further checks that programs are exempt from deadlocks.


Discovery of Convoys in Trajectory Databases

Abstract: As mobile devices with positioning capabilities continue to proliferate, data management for so-called trajectory databases that capture the historical movements of populations of moving objects becomes important. This paper considers the querying of such databases for convoys, a convoy being a group of objects that have traveled together for some time. More specifically, this paper formalizes the concept of a convoy query using density-based notions, in order to capture groups of arbitrary extents and shapes. Convoy discovery is relevant for real-life applications in throughput planning of trucks and carpooling of vehicles. Although there has been extensive research on trajectories in the literature, none of this can be applied to retrieve correctly exact convoy result sets. Motivated by this, we develop three efficient algorithms for convoy discovery that adopt the well-known filter-refinement framework. In the filter step, we apply line-simplification techniques on the trajectories and establish distance bounds between the simplified trajectories. This permits efficient convoy discovery over the simplified trajectories without missing any actual convoys. In the refinement step, the candidate convoys are further processed to obtain the actual convoys. Our comprehensive empirical study offers insight into the properties of the paper's proposals and demonstrates that the proposals are effective and efficient on real-world trajectory data.


The WebStand Project

Abstract: In this paper we present the state of advancement of the French ANR WebStand project. The objective of this project is to construct a customizable XML based warehouse platform to acquire, transform, analyze, store, query and export data from the web, in particular mailing lists, with the final intension of using this data to perform sociological studies focused on social groups of World Wide Web, with a specific emphasis on the temporal aspects of this data. We are currently using this system to analyze the standardization process of the W3C, through its social network of standard setters.


A Framework for Agile Development of Component-Based Applications

Abstract: Agile development processes and component-based software architectures are two software engineering approaches that contribute to enable the rapid building and evolution of applications. Nevertheless, few approaches have proposed a framework to combine agile and component-based development, allowing an application to be tested throughout the entire development cycle. To address this problematic, we have built CALICO, a model-based framework that allows applications to be safely developed in an iterative and incremental manner. The CALICO approach relies on the synchronization of a model view, which specifies the application properties, and a runtime view, which contains the application in its execution context. Tests on the application specifications that require values only known at runtime, are automatically integrated by CALICO into the running application, and the captured needed values are reified at execution time to resume the tests and inform the architect of potential problems. Any modification at the model level that does not introduce new errors is automatically propagated to the running system, allowing the safe evolution of the application. In this paper, we illustrate the CALICO development process with a concrete example and provide information on the current implementation of our framework.


Modelling Mobility: A Discrete Revolution

Abstract: We introduce a new approach to model and analyze \emph{Mobility}. It is fully based on discrete mathematics and yields a class of mobility models, called the \emph{Markov Trace} Model. This model can be seen as the discrete version of the \emph{Random Trip} Model including all variants of the \emph{Random Way-Point} Model \cite{L06}. We derive fundamental properties and \emph{explicit} analytical formulas for the \emph{stationary distributions} yielded by the Markov Trace Model. Such results can be exploited to compute formulas and properties for concrete cases of the Markov Trace Model by just applying counting arguments. We apply the above general results to the discrete version of the \emph{Manhattan Random Way-Point} over a square of bounded size. We get formulas for the total stationary distribution and for two important \emph{conditional} ones: the agent spatial and destination distributions. Our method makes the analysis of complex mobile systems a feasible task. As a further evidence of this important fact, we first model a complex vehicular-mobile system over a set of crossing streets. Several concrete issues are implemented such as parking zones, traffic lights, and variable vehicle speeds. By using a \emph{modular} version of the Markov Trace Model, we get explicit formulas for the stationary distributions yielded by this vehicular-mobile model as well.


Heuristic Contraction Hierarchies with Approximation Guarantee

Abstract: We present a new heuristic point-to-point routing algorithm based on contraction hierarchies (CH). Given an epsilon >= 0, we can prove that the length of the path computed by our algorithm is at most (1+epsilon) times the length of the optimal (shortest) path. CH is based on node contraction: removing nodes from a network and adding shortcut edges to preserve shortest path distances. Our algorithm tries to avoid shortcuts even when a replacement path is epsilon times longer.


Odds-On Trees

Abstract: Let R^d -> A be a query problem over R^d for which there exists a data structure S that can compute P(q) in O(log n) time for any query point q in R^d. Let D be a probability measure over R^d representing a distribution of queries. We describe a data structure called the odds-on tree, of size O(n^\epsilon) that can be used as a filter that quickly computes P(q) for some query values q in R^d and relies on S for the remaining queries. With an odds-on tree, the expected query time for a point drawn according to D is O(H*+1), where H* is a lower-bound on the expected cost of any linear decision tree that solves P. Odds-on trees have a number of applications, including distribution-sensitive data structures for point location in 2-d, point-in-polytope testing in d dimensions, ray shooting in simple polygons, ray shooting in polytopes, nearest-neighbour queries in R^d, point-location in arrangements of hyperplanes in R^d, and many other geometric searching problems that can be solved in the linear-decision tree model. A standard lifting technique extends these results to algebraic decision trees of constant degree. A slightly different version of odds-on trees yields similar results for orthogonal searching problems that can be solved in the comparison tree model.


Towards a Heuristic Categorization of Prepositional Phrases in English with WordNet

Abstract: This document discusses an approach and its rudimentary realization towards automatic classification of PPs; the topic, that has not received as much attention in NLP as NPs and VPs. The approach is a rule-based heuristics outlined in several levels of our research. There are 7 semantic categories of PPs considered in this document that we are able to classify from an annotated corpus.


The "Hot Potato" Case: Challenges in Multiplayer Pervasive Games Based on Ad hoc Mobile Sensor Networks and the Experimental Evaluation of a Prototype Game

Abstract: In this work, we discuss multiplayer pervasive games that rely on the use of ad hoc mobile sensor networks. The unique feature in such games is that players interact with each other and their surrounding environment by using movement and presence as a means of performing game-related actions, utilizing sensor devices. We discuss the fundamental issues and challenges related to these type of games and the scenarios associated with them. We also present and evaluate an example of such a game, called the "Hot Potato", developed using the Sun SPOT hardware platform. We provide a set of experimental results, so as to both evaluate our implementation and also to identify issues that arise in pervasive games which utilize sensor network nodes, which show that there is great potential in this type of games.


An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets

Abstract: As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Specifically, we develop a novel methodology to identify a meaningful support threshold s* for a dataset, such that the number of itemsets with support at least s* represents a substantial deviation from what would be expected in a random dataset with the same number of transactions and the same individual item frequencies. These itemsets can then be flagged as statistically significant with a small false discovery rate. We present extensive experimental results to substantiate the effectiveness of our methodology.


A Logical Temporal Relational Data Model

Abstract: Time is one of the most difficult aspects to handle in real world applications such as database systems. Relational database management systems proposed by Codd offer very little built-in query language support for temporal data management. The model itself incorporates neither the concept of time nor any theory of temporal semantics. Many temporal extensions of the relational model have been proposed and some of them are also implemented. This paper offers a brief introduction to temporal database research. We propose a conceptual model for handling time varying attributes in the relational database model with minimal temporal attributes.


A CHAID Based Performance Prediction Model in Educational Data Mining

Abstract: The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for students' performance so as to identify the slow learners and study the influence of the dominant factors on their academic performance. In the present investigation, a survey cum experimental methodology was adopted to generate a database and it was constructed from a primary and a secondary source. While the primary data was collected from the regular students, the secondary data was gathered from the school and office of the Chief Educational Officer (CEO). A total of 1000 datasets of the year 2006 from five different schools in three different districts of Tamilnadu were collected. The raw data was preprocessed in terms of filling up missing values, transforming values in one form into another and relevant attribute/ variable selection. As a result, we had 772 student records, which were used for CHAID prediction model construction. A set of prediction rules were extracted from CHIAD prediction model and the efficiency of the generated CHIAD prediction model was found. The accuracy of the present model was compared with other model and it has been found to be satisfactory.


Interconnection between 802.15.4 Devices and IPv6: Implications and Existing Approaches

Abstract: The increasing role of home automation in routine life and the rising demand for sensor networks enhanced wireless personal area networks (WPANs) development, pervasiveness of wireless & wired network, and research. Soon arose the need of implementing the Internet Protocol in these devices in order to WPAN standards, raising the way for questions on how to provide seamless communication between wired and wireless technologies. After a quick overview of the Low-rate WPAN standard (IEEE 802.15.4) and the Zigbee stack, this paper focuses on understanding the implications when interconnecting low powered IEEE 802.15.4 devices and a wired IPv6 domain. Subsequently the focus will be on existing approaches to connect LoWPAN devices to the internet and on how these approaches try to solve these challenges, concluding with a critical analysis of interoperability problems.


A Comparative Study of Removal Noise from Remote Sensing Image

Abstract: This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN). Different noise densities have been removed between 10% to 60% by using five types of filters as Mean Filter (MF), Adaptive Wiener Filter (AWF), Gaussian Filter (GF), Standard Median Filter (SMF) and Adaptive Median Filter (AMF). The same is applied to the Saturn remote sensing image and they are compared with one another. The comparative study is conducted with the help of Mean Square Errors (MSE) and Peak-Signal to Noise Ratio (PSNR). So as to choose the base method for removal of noise from remote sensing image.


A Performance Study of GA and LSH in Multiprocessor Job Scheduling

Abstract: Multiprocessor task scheduling is an important and computationally difficult problem. This paper proposes a comparison study of genetic algorithm and list scheduling algorithm. Both algorithms are naturally parallelizable but have heavy data dependencies. Based on experimental results, this paper presents a detailed analysis of the scalability, advantages and disadvantages of each algorithm. Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uni-processor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. In multiprocessor systems, an efficient scheduling of a parallel program onto the processors that minimizes the entire execution time is vital for achieving a high performance. This scheduling problem is known to be NP- Hard. In multiprocessor scheduling problem, a given program is to be scheduled in a given multiprocessor system such that the program's execution time is minimized. The last job must be completed as early as possible. Genetic algorithm (GA) is one of the widely used techniques for constrained optimization.


Finding Sequential Patterns from Large Sequence Data

Abstract: Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Sequential pattern mining finds sets of data items that occur together frequently in some sequences. Sequential pattern mining, which extracts frequent subsequences from a sequence database, has attracted a great deal of interest during the recent data mining research because it is the basis of many applications, such as: web user analysis, stock trend prediction, DNA sequence analysis, finding language or linguistic patterns from natural language texts, and using the history of symptoms to predict certain kind of disease. The diversity of the applications may not be possible to apply a single sequential pattern model to all these problems. Each application may require a unique model and solution. A number of research projects were established in recent years to develop meaningful sequential pattern models and efficient algorithms for mining these patterns. In this paper, we theoretically provided a brief overview three types of sequential patterns model.


Realistic Approach towards Quantitative Analysis and Simulation of EEHC-Based Routing for Wireless Sensor Networks

Abstract: This paper presents the realistic approach towards the quantitative analysis and simulation of Energy Efficient Hierarchical Cluster (EEHC)-based routing for wireless sensor networks. Here the efforts have been done to combine analytical hardware model with the modified EEHC-based routing model. The dependence of various performance metrics like: optimum number of clusters, Energy Consumption, and Energy consumed per round etc. based on analytical hardware sensor model and EEHC model has been presented.


Performance Investigation of Virtual Private Networks with Different Bandwidth Allocations

Abstract: A Virtual Private Network (VPN) provides private network connections over a publicly accessible shared network. The effective allocation of bandwidth for VPNs assumes significance in the present scenario due to varied traffic. Each VPN endpoint specifies bounds on the total amount of traffic that it is likely to send or receive at any time. The network provider tailors the VPN so that there is sufficient bandwidth for any traffic matrix that is consistent with these bounds. The approach incorporates the use of Ad-hoc On demand Distance Vector (AODV) protocol, with a view to accomplish an enhancement in the performance of the mobile networks. The NS2 based simulation results are evaluated in terms of its metrics for different bandwidth allocations, besides analyzing its performance in the event of exigencies such as link failures. The results highlight the suitability of the proposed strategy in the context of real time applications.


Performance Analysis of Software to Hardware Task Migration in Codesign

Abstract: The complexity of multimedia applications in terms of intensity of computation and heterogeneity of treated data led the designers to embark them on multiprocessor systems on chip. The complexity of these systems on one hand and the expectations of the consumers on the other hand complicate the designers job to conceive and supply strong and successful systems in the shortest deadlines. They have to explore the different solutions of the design space and estimate their performances in order to deduce the solution that respects their design constraints. In this context, we propose the modeling of one of the design space possible solutions: the software to hardware task migration. This modeling exploits the synchronous dataflow graphs to take into account the different migration impacts and estimate their performances in terms of throughput.


Dimensionality Reduction: An Empirical Study on the Usability of IFE-CF (Independent Feature Elimination- by C-Correlation and F-Correlation) Measures

Abstract: The recent increase in dimensionality of data has thrown a great challenge to the existing dimensionality reduction methods in terms of their effectiveness. Dimensionality reduction has emerged as one of the significant preprocessing steps in machine learning applications and has been effective in removing inappropriate data, increasing learning accuracy, and improving comprehensibility. Feature redundancy exercises great influence on the performance of classification process. Towards the better classification performance, this paper addresses the usefulness of truncating the highly correlated and redundant attributes. Here, an effort has been made to verify the utility of dimensionality reduction by applying LVQ (Learning Vector Quantization) method on two Benchmark datasets of 'Pima Indian Diabetic patients' and 'Lung cancer patients'.


Establishment of Relationships between Material Design and Product Design Domains by Hybrid FEM-ANN Technique

Abstract: In this paper, research on AI based modeling technique to optimize development of new alloys with necessitated improvements in properties and chemical mixture over existing alloys as per functional requirements of product is done. The current research work novels AI in lieu of predictions to establish association between material and product customary. Advanced computational simulation techniques like CFD, FEA interrogations are made viable to authenticate product dynamics in context to experimental investigations. Accordingly, the current research is focused towards binding relationships between material design and product design domains. The input to feed forward back propagation prediction network model constitutes of material design features. Parameters relevant to product design strategies are furnished as target outputs. The outcomes of ANN shows good sign of correlation between material and product design domains. The study enriches a new path to illustrate material factors at the time of new product development.


Mining The Successful Binary Combinations: Methodology and A Simple Case Study

Abstract: The importance of finding the characteristics leading to either a success or a failure is one of the driving forces of data mining. The various application areas of finding success/failure factors cover vast variety of areas such as credit risk evaluation and granting loans, micro array analysis, health factors and health risk factors, and parameter combination leading to a product success. This paper presents a new approach for making inferences about dichotomous data. The objective is to determine rules that lead to a certain result. The method consists of four phases: in the first phase, the data is processed into a binary format of a truth table, in the second phase; rules are found by utilizing an algorithm that minimizes Boolean functions. In the third phase the rules are checked and filtered. In the fourth phase, simple rules that involve one to two features are revealed.


Towards Public Key Infrastructure less authentication in Session Initiation Protocol

Abstract: The Session Initiation Protocol (SIP) has become the most predominant protocol for Voice over Internet Protocol (VoIP) signaling. Security of SIP is an important consideration for VoIP communication as the traffic is transmitted over the insecure IP network. And the authentication process in SIP ranges from pre-shared secret based solutions to Public Key Infrastructure (PKI) based solution. However, due to the limitations in PKI based solutions, some PKI less authentications mechanisms are proposed. This paper aims to present an overview of different authentication methods used in or together with SIP. We start by highlighting the security issues in SIP in the context of VoIP communication. Then we illustrate the current activities regarding the SIP authentication mechanisms including the recent developments in the research community and standardization efforts within the Internet Engineering Task Force (IETF). Finally we analyze the security aspects of these approaches.


Node Disjoint Multipath Routing Considering Link and Node Stability protocol: A characteristic Evaluation

Abstract: Mobile Ad hoc Networks are highly dynamic networks. Quality of Service (QoS) routing in such networks is usually limited by the network breakage due to either node mobility or energy depletion of the mobile nodes. Also, to fulfill certain quality parameters, presence of multiple node-disjoint paths becomes essential. Such paths aid in the optimal traffic distribution and reliability in case of path breakages. Thus, to cater various challenges in QoS routing in Mobile Add hoc Networks, a Node Disjoint Multipath Routing Considering Link and Node Stability (NDMLNR) protocol has been proposed by the authors. The metric used to select the paths takes into account the stability of the nodes and the corresponding links. This paper studies various challenges in the QoS routing and presents the characteristic evaluation of NDMLNR w.r.t various existing protocols in this area.


Efficient Password-Typed Key Agreement Scheme

Abstract: In this paper, we will study Lee, Kim and Yoo, a verifier password typed key agreement scheme and demonstrate that the scheme is not secure. Then, the authors will propose an enhanced verifier typed key agreement scheme relied on Lee, Kim and Yoo scheme and demonstrate that the propose scheme resists against password guessing attack and stolen verifier attack. The authors are claimed that the proposed scheme is more secure and efficient compare with Lee, Kim and Yoo.


Existence and Global Logarithmic Stability of Impulsive Neural Networks with Time Delay

Abstract: The stability and convergence of the neural networks are the fundamental characteristics in the Hopfield type networks. Since time delay is ubiquitous in most physical and biological systems, more attention is being made for the delayed neural networks. The inclusion of time delay into a neural model is natural due to the finite transmission time of the interactions. The stability analysis of the neural networks depends on the Lyapunov function and hence it must be constructed for the given system. In this paper we have made an attempt to establish the logarithmic stability of the impulsive delayed neural networks by constructing suitable Lyapunov function.