Diffusion framework for geometric and photometric data fusion in non-rigid shape analysis

Abstract: In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fail.


Discrete Time Elastic Vector Spaces

Abstract: We propose in this paper a framework dedicated to the construction of what we call time elastic inner products that allows embedding sets of non-uniformly sampled multivariate time series of varying lengths into vector space structures. This framework is based on a recursive definition that covers the case of multiple embedded time elastic dimensions. We prove that such inner products exist in our framework and show how a simple instance of this inner product class operates on some toy applications, while generalizing the Euclidean inner product.


Meaning Negotiation as Inference

Abstract: Meaning negotiation (MN) is the general process with which agents reach an agreement about the meaning of a set of terms. Artificial Intelligence scholars have dealt with the problem of MN by means of argumentations schemes, beliefs merging and information fusion operators, and ontology alignment but the proposed approaches depend upon the number of participants. In this paper, we give a general model of MN for an arbitrary number of agents, in which each participant discusses with the others her viewpoint by exhibiting it in an actual set of constraints on the meaning of the negotiated terms. We call this presentation of individual viewpoints an angle. The agents do not aim at forming a common viewpoint but, instead, at agreeing about an acceptable common angle. We analyze separately the process of MN by two agents (\emph{bilateral} or \emph{pairwise} MN) and by more than two agents (\emph{multiparty} MN), and we use game theoretic models to understand how the process develops in both cases: the models are Bargaining Game for bilateral MN and English Auction for multiparty MN. We formalize the process of reaching such an agreement by giving a deduction system that comprises of rules that are consistent and adequate for representing MN.


Existential witness extraction in classical realizability and via a negative translation

Abstract: We show how to extract existential witnesses from classical proofs using Krivine's classical realizability---where classical proofs are interpreted as lambda-terms with the call/cc control operator. We first recall the basic framework of classical realizability (in classical second-order arithmetic) and show how to extend it with primitive numerals for faster computations. Then we show how to perform witness extraction in this framework, by discussing several techniques depending on the shape of the existential formula. In particular, we show that in the Sigma01-case, Krivine's witness extraction method reduces to Friedman's through a well-suited negative translation to intuitionistic second-order arithmetic. Finally we discuss the advantages of using call/cc rather than a negative translation, especially from the point of view of an implementation.


Throw One's Cake --- and Have It Too

Abstract: We consider the problem of fairly dividing a heterogeneous cake between a number of players with different tastes. In this setting, it is known that fairness requirements may result in a suboptimal division from the social welfare standpoint. Here, we show that in some cases, discarding some of the cake and fairly dividing only the remainder may be socially preferable to any fair division of the entire cake. We study this phenomenon, providing asymptotically-tight bounds on the social improvement achievable by such discarding.


BitTorrent Swarm Analysis through Automation and Enhanced Logging

Abstract: Peer-to-Peer protocols currently form the most heavily used protocol class in the Internet, with BitTorrent, the most popular protocol for content distribution, as its flagship. A high number of studies and investigations have been undertaken to measure, analyse and improve the inner workings of the BitTorrent protocol. Approaches such as tracker message analysis, network probing and packet sniffing have been deployed to understand and enhance BitTorrent's internal behaviour. In this paper we present a novel approach that aims to collect, process and analyse large amounts of local peer information in BitTorrent swarms. We classify the information as periodic status information able to be monitored in real time and as verbose logging information to be used for subsequent analysis. We have designed and implemented a retrieval, storage and presentation infrastructure that enables easy analysis of BitTorrent protocol internals. Our approach can be employed both as a comparison tool, as well as a measurement system of how network characteristics and protocol implementation influence the overall BitTorrent swarm performance. We base our approach on a framework that allows easy swarm creation and control for different BitTorrent clients. With the help of a virtualized infrastructure and a client-server software layer we are able to create, command and manage large sized BitTorrent swarms. The framework allows a user to run, schedule, start, stop clients within a swarm and collect information regarding their behavior.


Relating Church-Style and Curry-Style Subtyping

Abstract: Type theories with higher-order subtyping or singleton types are examples of systems where computation rules for variables are affected by type information in the context. A complication for these systems is that bounds declared in the context do not interact well with the logical relation proof of completeness or termination. This paper proposes a natural modification to the type syntax for F-Omega-Sub, adding variable's bound to the variable type constructor, thereby separating the computational behavior of the variable from the context. The algorithm for subtyping in F-Omega-Sub can then be given on types without context or kind information. As a consequence, the metatheory follows the general approach for type systems without computational information in the context, including a simple logical relation definition without Kripke-style indexing by context. This new presentation of the system is shown to be equivalent to the traditional presentation without bounds on the variable type constructor.


Intersection Logic in sequent calculus style

Abstract: The intersection type assignment system has been designed directly as deductive system for assigning formulae of the implicative and conjunctive fragment of the intuitionistic logic to terms of lambda-calculus. But its relation with the logic is not standard. Between all the logics that have been proposed as its foundation, we consider ISL, which gives a logical interpretation of the intersection by splitting the intuitionistic conjunction into two connectives, with a local and global behaviour respectively, being the intersection the local one. We think ISL is a logic interesting by itself, and in order to support this claim we give a sequent calculus formulation of it, and we prove that it enjoys the cut elimination property.


Sound and Complete Typing for lambda-mu

Abstract: In this paper we define intersection and union type assignment for Parigot's calculus lambda-mu. We show that this notion is complete (i.e. closed under subject-expansion), and show also that it is sound (i.e. closed under subject-reduction). This implies that this notion of intersection-union type assignment is suitable to define a semantics.


Intersection types for unbind and rebind

Abstract: We define a type system with intersection types for an extension of lambda-calculus with unbind and rebind operators. In this calculus, a term with free variables, representing open code, can be packed into an "unbound" term, and passed around as a value. In order to execute inside code, an unbound term should be explicitly rebound at the point where it is used. Unbinding and rebinding are hierarchical, that is, the term can contain arbitrarily nested unbound terms, whose inside code can only be executed after a sequence of rebinds has been applied. Correspondingly, types are decorated with levels, and a term has type decorated with k if it needs k rebinds in order to reduce to a value. With intersection types we model the fact that a term can be used differently in contexts providing different numbers of unbinds. In particular, top-level terms, that is, terms not requiring unbinds to reduce to values, should have a value type, that is, an intersection type where at least one element has level 0. With the proposed intersection type system we get soundness under the call-by-value strategy, an issue which was not resolved by previous type systems.


Untangling Typechecking of Intersections and Unions

Abstract: Intersection and union types denote conjunctions and disjunctions of properties. Using bidirectional typechecking, intersection types are relatively straightforward, but union types present challenges. For union types, we can case-analyze a subterm of union type when it appears in evaluation position (replacing the subterm with a variable, and checking that term twice under appropriate assumptions). This technique preserves soundness in a call-by-value semantics. Sadly, there are so many choices of subterms that a direct implementation is not practical. But carefully transforming programs into let-normal form drastically reduces the number of choices. The key results are soundness and completeness: a typing derivation (in the system with too many subterm choices) exists for a program if and only if a derivation exists for the let-normalized program.


Session Types = Intersection Types + Union Types

Abstract: We propose a semantically grounded theory of session types which relies on intersection and union types. We argue that intersection and union types are natural candidates for modeling branching points in session types and we show that the resulting theory overcomes some important defects of related behavioral theories. In particular, intersections and unions provide a native solution to the problem of computing joins and meets of session types. Also, the subtyping relation turns out to be a pre-congruence, while this is not always the case in related behavioral theories.


Equality, Quasi-Implicit Products, and Large Eliminations

Abstract: This paper presents a type theory with a form of equality reflection: provable equalities can be used to coerce the type of a term. Coercions and other annotations, including implicit arguments, are dropped during reduction of terms. We develop the metatheory for an undecidable version of the system with unannotated terms. We then devise a decidable system with annotated terms, justified in terms of the unannotated system. Finally, we show how the approach can be extended to account for large eliminations, using what we call quasi-implicit products.


Parameter Optimization of Multi-Agent Formations based on LQR Design

Abstract: In this paper we study the optimal formation control of multiple agents whose interaction parameters are adjusted upon a cost function consisting of both the control energy and the geometrical performance. By optimizing the interaction parameters and by the linear quadratic regulation(LQR) controllers, the upper bound of the cost function is minimized. For systems with homogeneous agents interconnected over sparse graphs, distributed controllers are proposed that inherit the same underlying graph as the one among agents. For the more general case, a relaxed optimization problem is considered so as to eliminate the nonlinear constraints. Using the subgradient method, interaction parameters among agents are optimized under the constraint of a sparse graph, and the optimum of the cost function is a better result than the one when agents interacted only through the control channel. Numerical examples are provided to validate the effectiveness of the method and to illustrate the geometrical performance of the system.


Spectrum Management for Cognitive Radio based on Genetics Algorithm

Abstract: Spectrum scarceness is one of the major challenges that the present world is facing. The efficient use of existing licensed spectrum is becoming most critical as growing demand of the radio spectrum. Different researches show that the use of licensed are not utilized inefficiently. It has been also shown that primary user does not use more than 70% of the licensed frequency band most of the time. Many researchers are trying to found the techniques that efficiently utilize the under-utilized licensed spectrum. One of the approaches is the use of "Cognitive Radio". This allows the radio to learn from its environment, changing certain parameters. Based on this knowledge the radio can dynamically exploit the spectrum holes in the licensed band of the spectrum. This paper w i l l focus on the performance of spectrum allocation technique, based on popular meta-heuristics Genetics Algorithm and analyzing the performance of this technique using Mat Lab.


High-Confidence Predictions under Adversarial Uncertainty

Abstract: We study the setting in which the bits of an unknown infinite binary sequence x are revealed sequentially to an observer. We show that very limited assumptions about x allow one to make successful predictions about unseen bits of x. First, we study the problem of successfully predicting a single 0 from among the bits of x. In our model we have only one chance to make a prediction, but may do so at a time of our choosing. We describe and motivate this as the problem of a frog who wants to cross a road safely. Letting N_t denote the number of 1s among the first t bits of x, we say that x is "eps-weakly sparse" if lim inf (N_t/t) <= eps. Our main result is a randomized algorithm that, given any eps-weakly sparse sequence x, predicts a 0 of x with success probability as close as desired to 1 - \eps. Thus we can perform this task with essentially the same success probability as under the much stronger assumption that each bit of x takes the value 1 independently with probability eps. We apply this result to show how to successfully predict a bit (0 or 1) under a broad class of possible assumptions on the sequence x. The assumptions are stated in terms of the behavior of a finite automaton M reading the bits of x. We also propose and solve a variant of the well-studied "ignorant forecasting" problem. For every eps > 0, we give a randomized forecasting algorithm S_eps that, given sequential access to a binary sequence x, makes a prediction of the form: "A p fraction of the next N bits will be 1s." (The algorithm gets to choose p, N, and the time of the prediction.) For any fixed sequence x, the forecast fraction p is accurate to within +-eps with probability 1 - eps.


Adaptive Submodular Optimization under Matroid Constraints

Abstract: Many important problems in discrete optimization require maximization of a monotonic submodular function subject to matroid constraints. For these problems, a simple greedy algorithm is guaranteed to obtain near-optimal solutions. In this article, we extend this classic result to a general class of adaptive optimization problems under partial observability, where each choice can depend on observations resulting from past choices. Specifically, we prove that a natural adaptive greedy algorithm provides a $1/(p+1)$ approximation for the problem of maximizing an adaptive monotone submodular function subject to $p$ matroid constraints, and more generally over arbitrary $p$-independence systems. We illustrate the usefulness of our result on a complex adaptive match-making application.


Extensional Collapse Situations I: non-termination and unrecoverable errors

Abstract: We consider a simple model of higher order, functional computation over the booleans. Then, we enrich the model in order to encompass non-termination and unrecoverable errors, taken separately or jointly. We show that the models so defined form a lattice when ordered by the extensional collapse situation relation, introduced in order to compare models with respect to the amount of "intensional information" that they provide on computation. The proofs are carried out by exhibiting suitable applied {\lambda}-calculi, and by exploiting the fundamental lemma of logical relations.


Thermal Analysis of Climate Regions using Remote Sensing and Grid Computing

Abstract: The analysis of climate regions is very important for designers and architects, because the increase in density and built up spaces and reduction in open spaces and green lands induce the increase of heat, especially in an urban area, deteriorating the environment and causing health problems. This study analyzes the Land Surface Temperature (LST) differences in the region of Dobrogea, Romania, and compares with the land use and land cover types using TM and ETM+ data of 1989 and 2000. As the analysis is performed on large data sets, we used Grid Computing to implement a service for using on Computational Grids with a Web-based client interface, which will be greatly useful and convenient for those who are studying the ground thermal environment and heat island effects by using Landsat TM/ETM+ bands, and have typical workstations, with no special computing and storing resources for computationally intensive satellite image processing and no license for a commercial image processing tool. Based on the satellite imagery, the paper also addresses a Supervised Classification algorithm and the computation of two indices of great value in water resources management, Normalized Difference Vegetation Index (NDVI), respectively Land Surface Emissivity (LSE).


An automaton over data words that captures EMSO logic

Abstract: We develop a general framework for the specification and implementation of systems whose executions are words, or partial orders, over an infinite alphabet. As a model of an implementation, we introduce class register automata, a one-way automata model over words with multiple data values. Our model combines register automata and class memory automata. It has natural interpretations. In particular, it captures communicating automata with an unbounded number of processes, whose semantics can be described as a set of (dynamic) message sequence charts. On the specification side, we provide a local existential monadic second-order logic that does not impose any restriction on the number of variables. We study the realizability problem and show that every formula from that logic can be effectively, and in elementary time, translated into an equivalent class register automaton.


A Context-theoretic Framework for Compositionality in Distributional Semantics

Abstract: Techniques in which words are represented as vectors have proved useful in many applications in computational linguistics, however there is currently no general semantic formalism for representing meaning in terms of vectors. We present a framework for natural language semantics in which words, phrases and sentences are all represented as vectors, based on a theoretical analysis which assumes that meaning is determined by context. In the theoretical analysis, we define a corpus model as a mathematical abstraction of a text corpus. The meaning of a string of words is assumed to be a vector representing the contexts in which it occurs in the corpus model. Based on this assumption, we can show that the vector representations of words can be considered as elements of an algebra over a field. We note that in applications of vector spaces to representing meanings of words there is an underlying lattice structure; we interpret the partial ordering of the lattice as describing entailment between meanings. We also define the context-theoretic probability of a string, and, based on this and the lattice structure, a degree of entailment between strings. We relate the framework to existing methods of composing vector-based representations of meaning, and show that our approach generalises many of these, including vector addition, component-wise multiplication, and the tensor product.


Conflict Packing: an unifying technique to obtain polynomial kernels for editing problems on dense instances

Abstract: We develop a technique that we call Conflict Packing in the context of kernelization, obtaining (and improving) several polynomial kernels for editing problems on dense instances. We apply this technique on several well-studied problems: Feedback Arc Set in (Bipartite) Tournaments, Dense Rooted Triplet Inconsistency and Betweenness in Tournaments. For the former, one is given a (bipartite) tournament $T = (V,A)$ and seeks a set of at most $k$ arcs whose reversal in $T$ results in an acyclic (bipartite) tournament. While a linear vertex-kernel is already known for the first problem, using the Conflict Packing allows us to find a so-called safe partition, the central tool of the kernelization algorithm in, with simpler arguments. For the case of bipartite tournaments, the same technique allows us to obtain a quadratic vertex-kernel. Again, such a kernel was already known to exist, using the concept of so-called bimodules. We believe however that providing an unifying technique to cope with such problems is interesting. Regarding Dense Rooted Triplet Inconsistency, one is given a set of vertices $V$ and a dense collection $\mathcal{R}$ of rooted binary trees over three vertices of $V$ and seeks a rooted tree over $V$ containing all but at most $k$ triplets from $\mathcal{R}$. As a main consequence of our technique, we prove that the Dense Rooted Triplet Inconsistency problem admits a linear vertex-kernel. This result improves the best known bound of $O(k^2)$ vertices for this problem. Finally, we use this technique to obtain a linear vertex-kernel for Betweenness in Tournaments, where one is given a set of vertices $V$ and a dense collection $\mathcal{R}$ of so-called betweenness triplets and seeks a linear ordering of the vertices containing all but at most $k$ triplets from $\mathcal{R}$.


Team-building with Answer Set Programming in the Gioia-Tauro Seaport

Abstract: (To appear in Theory and Practice of Logic Programming (TPLP).) The seaport of Gioia Tauro is the largest transshipment terminal of the Mediterranean coast. A crucial management task for the companies operating in the seaport is team building: the problem of properly allocating the available personnel for serving the incoming ships. Teams have to be carefully arranged in order to meet several constraints, such as allocation of the employees with the appropriate skills, fair distribution of the working load, and turnover of the heavy/dangerous roles. This makes team building a hard and expensive task requiring several hours per day of manual preparation. In this paper we present a system based on Answer Set Programming (ASP) for the automatic generation of the teams of employees in the seaport of Gioia Tauro. The system is currently exploited in the Gioia Tauro seaport by ICO BLG, a company specialized in automobile logistics.


Tight bounds on the randomized communication complexity of symmetric XOR functions in one-way and SMP models

Abstract: We study the communication complexity of symmetric XOR functions, namely functions $f: \{0,1\}^n \times \{0,1\}^n \rightarrow \{0,1\}$ that can be formulated as $f(x,y)=D(|x\oplus y|)$ for some predicate $D: \{0,1,...,n\} \rightarrow \{0,1\}$, where $|x\oplus y|$ is the Hamming weight of the bitwise XOR of $x$ and $y$. We give a public-coin randomized protocol in the Simultaneous Message Passing (SMP) model, with the communication cost matching the known lower bound for the \emph{quantum} and \emph{two-way} model up to a logarithm factor. As a corollary, this closes a quadratic gap between quantum lower bound and randomized upper bound for the one-way model, answering an open question raised in Shi and Zhang \cite{SZ09}.


Tight Bounds on Information Dissemination in Sparse Mobile Networks

Abstract: Motivated by the growing interest in mobile systems, we study the dynamics of information dissemination between agents moving independently on a plane. Formally, we consider $k$ mobile agents performing independent random walks on an $n$-node grid. At time $0$, each agent is located at a random node of the grid and one agent has a rumor. The spread of the rumor is governed by a dynamic communication graph process ${G_t(r) | t \geq 0}$, where two agents are connected by an edge in $G_t(r)$ iff their distance at time $t$ is within their transmission radius $r$. Modeling the physical reality that the speed of radio transmission is much faster than the motion of the agents, we assume that the rumor can travel throughout a connected component of $G_t$ before the graph is altered by the motion. We study the broadcast time $T_B$ of the system, which is the time it takes for all agents to know the rumor. We focus on the sparse case (below the percolation point $r_c \approx \sqrt{n/k}$) where, with high probability, no connected component in $G_t$ has more than a logarithmic number of agents and the broadcast time is dominated by the time it takes for many independent random walks to meet each other. Quite surprisingly, we show that for a system below the percolation point the broadcast time does not depend on the relation between the mobility speed and the transmission radius. In fact, we prove that $T_B = \tilde{O}(n / \sqrt{k})$ for any $0 \leq r < r_c$, even when the transmission range is significantly larger than the mobility range in one step, giving a tight characterization up to logarithmic factors. Our result complements a recent result of Peres et al. (SODA 2011) who showed that above the percolation point the broadcast time is polylogarithmic in $k$.


A Secure Web-Based File Exchange Server: Software Requirements Specification Document

Abstract: This document presents brief software specification of a secure file exchange system prototype involving mutual authentication of the users via their browser and the application server with PKI-based certificates as credentials, the use of LDAP for credential management, and authentication between the application and database servers to maintain a high level of trust between all parties.


Design and Implementation of a Secure Web-Based File Exchange Server: Specification Design Document

Abstract: We report on the software engineering design and implementation of an web- and LDAP-based secure file exchange system with bi-directional authentication of all parties involved in the process that is the user's browsers and the application server mutually authenticate, and the application and database servers authenticate using certificates, credentials, etcs. with the directory service provided by LDAP using open-source technologies.


Sweeping an oval to a vanishing point

Abstract: Given a convex region in the plane, and a sweep-line as a tool, what is best way to reduce the region to a single point by a sequence of sweeps? The problem of sweeping points by orthogonal sweeps was first studied in [2]. Here we consider the following \emph{slanted} variant of sweeping recently introduced in [1]: In a single sweep, the sweep-line is placed at a start position somewhere in the plane, then moved continuously according to a sweep vector $\vec v$ (not necessarily orthogonal to the sweep-line) to another parallel end position, and then lifted from the plane. The cost of a sequence of sweeps is the sum of the lengths of the sweep vectors. The (optimal) sweeping cost of a region is the infimum of the costs over all finite sweeping sequences for that region. An optimal sweeping sequence for a region is one with a minimum total cost, if it exists. Another parameter of interest is the number of sweeps. We show that there exist convex regions for which the optimal sweeping cost cannot be attained by two sweeps. This disproves a conjecture of Bousany, Karker, O'Rourke, and Sparaco stating that two sweeps (with vectors along the two adjacent sides of a minimum-perimeter enclosing parallelogram) always suffice [1]. Moreover, we conjecture that for some convex regions, no finite sweeping sequence is optimal. On the other hand, we show that both the 2-sweep algorithm based on minimum-perimeter enclosing rectangle and the 2-sweep algorithm based on minimum-perimeter enclosing parallelogram achieve a $4/\pi \approx 1.27$ approximation in this sweeping model.


Close the Gaps: A Learning-while-Doing Algorithm for a Class of Single-Product Revenue Management Problems

Abstract: We consider a retailer selling a single product with limited on-hand inventory over a finite selling season. Customer demand arrives according to a Poisson process, the rate of which is influenced by a single action taken by the retailer (such as price adjustment, sales commission, advertisement intensity, etc.). The relationship between the action and the demand rate is not known in advance. However, the retailer is able to learn the optimal action "on the fly" as she maximizes her total expected revenue based on the observed demand reactions. Using the pricing problem as an example, we propose a dynamic "learning-while-doing" algorithm that only involves function value estimation to achieve a near-optimal performance. Our algorithm employs a series of shrinking price intervals and iteratively tests prices within that interval using a set of carefully chosen parameters. We prove that the convergence rate of our algorithm is among the fastest of all possible algorithms in terms of asymptotic "regret" (the relative loss comparing to the full information optimal solution). Our result closes the performance gaps between parametric and non-parametric learning and between a post-price mechanism and a customer-bidding mechanism. Important managerial insight from this research is that the values of information on both the parametric form of the demand function as well as each customer's exact reservation price are less important than prior literature suggests. Our results also suggest that firms would be better off to perform dynamic learning and action concurrently rather than sequentially.


On Approximating the Riemannian 1-Center

Abstract: In this paper, we generalize the simple Euclidean 1-center approximation algorithm of Badoiu and Clarkson (2003) to Riemannian geometries and study accordingly the convergence rate. We then show how to instantiate this generic algorithm to two particular cases: (1) hyperbolic geometry, and (2) Riemannian manifold of symmetric positive definite matrices.


Interface Theories for (A)synchronously Communicating Modal I/O-Transition Systems

Abstract: Interface specifications play an important role in component-based software development. An interface theory is a formal framework supporting composition, refinement and compatibility of interface specifications. We present different interface theories which use modal I/O-transition systems as their underlying domain for interface specifications: synchronous interface theories, which employ a synchronous communication schema, as well as a novel interface theory for asynchronous communication where components communicate via FIFO-buffers.


Contracts for Abstract Processes in Service Composition

Abstract: Contracts are a well-established approach for describing and analyzing behavioral aspects of web service compositions. The theory of contracts comes equipped with a notion of compatibility between clients and servers that ensures that every possible interaction between compatible clients and servers will complete successfully. It is generally agreed that real applications often require the ability of exposing just partial descriptions of their behaviors, which are usually known as abstract processes. We propose a formal characterization of abstraction as an extension of the usual symbolic bisimulation and we recover the notion of abstraction in the context of contracts.


An Algebra of Synchronous Scheduling Interfaces

Abstract: In this paper we propose an algebra of synchronous scheduling interfaces which combines the expressiveness of Boolean algebra for logical and functional behaviour with the min-max-plus arithmetic for quantifying the non-functional aspects of synchronous interfaces. The interface theory arises from a realisability interpretation of intuitionistic modal logic (also known as Curry-Howard-Isomorphism or propositions-as-types principle). The resulting algebra of interface types aims to provide a general setting for specifying type-directed and compositional analyses of worst-case scheduling bounds. It covers synchronous control flow under concurrent, multi-processing or multi-threading execution and permits precise statements about exactness and coverage of the analyses supporting a variety of abstractions. The paper illustrates the expressiveness of the algebra by way of some examples taken from network flow problems, shortest-path, task scheduling and worst-case reaction times in synchronous programming.


A Few Considerations on Structural and Logical Composition in Specification Theories

Abstract: Over the last 20 years a large number of automata-based specification theories have been proposed for modeling of discrete,real-time and probabilistic systems. We have observed a lot of shared algebraic structure between these formalisms. In this short abstract, we collect results of our work in progress on describing and systematizing the algebraic assumptions in specification theories.


Online Adaptive Decision Fusion Framework Based on Entropic Projections onto Convex Sets with Application to Wildfire Detection in Video

Abstract: In this paper, an Entropy functional based online Adaptive Decision Fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several sub-algorithms each of which yielding its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights which are updated online according to an active fusion method based on performing entropic projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video based wildfire detection system is developed to evaluate the performance of the algorithm in handling the problems where data arrives sequentially. In this case, the oracle is the security guard of the forest lookout tower verifying the decision of the combined algorithm. Simulation results are presented. The EADF framework is also tested with a standard dataset.


Fractional counting of citations in research evaluation: A cross- and interdisciplinary assessment of the Tsinghua University in Beijing

Abstract: In the case of the scientometric evaluation of multi- or interdisciplinary units one risks to compare apples with oranges: each paper has to be assessed in comparison to an appropriate reference set. We suggest that the set of citing papers can be considered as the relevant representation of the field of impact. In order to normalize for differences in citation behavior among fields, citations can be fractionally counted proportionately to the length of the reference lists in the citing papers. This new method enables us to compare among units with different disciplinary affiliations at the paper level and also to assess the statistical significance of differences among sets. Twenty-seven departments of the Tsinghua University in Beijing are thus compared. Among them, the Department of Chinese Language and Linguistics is upgraded from the 19th to the second position in the ranking. The overall impact of 19 of the 27 departments is not significantly different at the 5% level when thus normalized for different citation potentials.


Mobility Control for Machine-to-Machine LTE Systems

Abstract: In this paper, we propose an efficient mobility control algorithm for the downlink multi-cell orthogonal frequency division multiplexing access (OFDMA) system for co-channel interference reduction. It divides each cell into several areas. The mobile nodes in each area find their own optimal position according to their present location. Both the signal to interference plus noise ratio (SINR) and the capacity for each node are increased by the proposed mobility control algorithm. Simulation results say that, even the frequency reuse factor (FRF) is equal to 1, the average capacity is improved after applying the mobility control algorithm, compared to existing partial frequency reuse (PFR) scheme.


Multi-Level Steganography: Improving Hidden Communication in Networks

Abstract: The paper presents Multi-Level Steganography (MLS), which defines a new concept for hidden communication in telecommunication networks. In MLS, at least two steganographic methods are utilised simultaneously, in such a way that one method (called the upper-level) serves as a carrier for the second one (called the lower-level). Such a relationship between two (or more) information hiding solutions has several potential benefits. The most important is that the lower-level method steganographic bandwidth can be utilised to make the steganogram unreadable even after the detection of the upper-level method: e.g., it can carry a cryptographic key that deciphers the steganogram carried by the upper-level one. It can also be used to provide the steganogram with integrity. Another important benefit is that the lower-layer method may be used as a signalling channel in which to exchange information that affects the way that the upper-level method functions, thus possibly making the steganographic communication harder to detect. The prototype of MLS for IP networks was also developed, and the experimental results are included in this paper.


It Is NL-complete to Decide Whether a Hairpin Completion of Regular Languages Is Regular

Abstract: The hairpin completion is an operation on formal languages which is inspired by the hairpin formation in biochemistry. Hairpin formations occur naturally within DNA-computing. It has been known that the hairpin completion of a regular language is linear context-free, but not regular, in general. However, for some time it is was open whether the regularity of the hairpin completion of a regular language is is decidable. In 2009 this decidability problem has been solved positively by providing a polynomial time algorithm. In this paper we improve the complexity bound by showing that the decision problem is actually NL-complete. This complexity bound holds for both, the one-sided and the two-sided hairpin completions.


A zero-one SUBEXP-dimension law for BPP

Abstract: We show that BPP has either SUBEXP-dimension zero (randomness is easy) or BPP=EXP (randomness is intractable).


Using Feature Weights to Improve Performance of Neural Networks

Abstract: Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant features using feature selection, an algorithm can be given this knowledge of feature importance based on expert opinion or prior learning. Learning can be faster and more accurate if learners take feature importance into account. Correlation aided Neural Networks (CANN) is presented which is such an algorithm. CANN treats feature importance as the correlation coefficient between the target attribute and the features. CANN modifies normal feed-forward Neural Network to fit both correlation values and training data. Empirical evaluation shows that CANN is faster and more accurate than applying the two step approach of feature selection and then using normal learning algorithms.


A Generalized Method for Integrating Rule-based Knowledge into Inductive Methods Through Virtual Sample Creation

Abstract: Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been shown to perform better than inductive learners. However, there is no general method to include domain knowledge into all inductive learning algorithms as all hybrid methods are highly specialized for a particular algorithm. We present an algorithm that will take domain knowledge in the form of propositional rules, generate artificial examples from the rules and also remove instances likely to be flawed. This enriched dataset then can be used by any learning algorithm. Experimental results of different scenarios are shown that demonstrate this method to be more effective than simple inductive learning.


Distributed Algorithm to Locate Critical Nodes to Network Robustness based on Spectral Analysis

Abstract: We propose an algorithm to locate the most critical nodes to network robustness. Such critical nodes may be thought of as those most related to the notion of network centrality. Our proposal relies only on a localized spectral analysis of a limited subnetwork centered at each node in the network. We also present a procedure allowing the navigation from any node towards a critical node following only local information computed by the proposed algorithm. Experimental results confirm the effectiveness of our proposal considering networks of different scales and topological characteristics.


A Novel Template-Based Learning Model

Abstract: This article presents a model which is capable of learning and abstracting new concepts based on comparing observations and finding the resemblance between the observations. In the model, the new observations are compared with the templates which have been derived from the previous experiences. In the first stage, the objects are first represented through a geometric description which is used for finding the object boundaries and a descriptor which is inspired by the human visual system and then they are fed into the model. Next, the new observations are identified through comparing them with the previously-learned templates and are used for producing new templates. The comparisons are made based on measures like Euclidean or correlation distance. The new template is created by applying onion-pealing algorithm. The algorithm consecutively uses convex hulls which are made by the points representing the objects. If the new observation is remarkably similar to one of the observed categories, it is no longer utilized in creating a new template. The existing templates are used to provide a description of the new observation. This description is provided in the templates space. Each template represents a dimension of the feature space. The degree of the resemblance each template bears to each object indicates the value associated with the object in that dimension of the templates space. In this way, the description of the new observation becomes more accurate and detailed as the time passes and the experiences increase. We have used this model for learning and recognizing the new polygons in the polygon space. Representing the polygons was made possible through employing a geometric method and a method inspired by human visual system. Various implementations of the model have been compared. The evaluation results of the model prove its efficiency in learning and deriving new templates.


Jancar's formal system for deciding bisimulation of first-order grammars and its non-soundness

Abstract: We construct an example of proof within the main formal system from arXiv:1010.4760v3, which is intended to capture the bisimulation equivalence for non-deterministic first-order grammars, and show that its conclusion is semantically false. We then locate and analyze the flawed argument in the soundness (meta)-proof of the above reference.


Geometric representations for minimalist grammars

Abstract: We reformulate minimalist grammars as partial functions on term algebras for strings and trees. Using filler/role bindings and tensor product representations, we construct homomorphisms for these data structures into geometric vector spaces. We prove that the structure-building functions as well as simple processors for minimalist languages can be realized by piecewise linear operators in representation space. We also propose harmony, i.e. the distance of an intermediate processing step from the final well-formed state in representation space, as a measure of processing complexity. Finally, we illustrate our findings by means of two particular arithmetic and fractal representations.


On Sharing Viral Video over an Ad Hoc Wireless Network

Abstract: We consider the problem of broadcasting a viral video (a large file) over an ad hoc wireless network (e.g., students in a campus). Many smartphones are GPS enabled, and equipped with peer-to-peer (ad hoc) transmission mode, allowing them to wirelessly exchange files over short distances rather than use the carrier's WAN. The demand for the file however is transmitted through the social network (e.g., a YouTube link posted on Facebook). To address this coupled-network problem (demand on the social network; bandwidth on the wireless network) where the two networks have different topologies, we propose a file dissemination algorithm. In our scheme, users query their social network to find geographically nearby friends that have the desired file, and utilize the underlying ad hoc network to route the data via multi-hop transmissions. We show that for many popular models for social networks, the file dissemination time scales sublinearly with n; the number of users, compared to the linear scaling required if each user who wants the file must download it from the carrier's WAN.


A Color Image Digital Watermarking Scheme Based on SOFM

Abstract: Digital watermarking technique has been presented and widely researched to solve some important issues in the digital world, such as copyright protection, copy protection and content authentication. Several robust watermarking schemes based on vector quantization (VQ) have been presented. In this paper, we present a new digital image watermarking method based on SOFM vector quantizer for color images. This method utilizes the codebook partition technique in which the watermark bit is embedded into the selected VQ encoded block. The main feature of this scheme is that the watermark exists both in VQ compressed image and in the reconstructed image. The watermark extraction can be performed without the original image. The watermark is hidden inside the compressed image, so much transmission time and storage space can be saved when the compressed data are transmitted over the Internet. Simulation results demonstrate that the proposed method has robustness against various image processing operations without sacrificing compression performance and the computational speed.


Simulation of Self-Assembly in the Abstract Tile Assembly Model with ISU TAS

Abstract: Since its introduction by Erik Winfree in 1998, the abstract Tile Assembly Model (aTAM) has inspired a wealth of research. As an abstract model for tile based self-assembly, it has proven to be remarkably powerful and expressive in terms of the structures which can self-assemble within it. As research has progressed in the aTAM, the self-assembling structures being studied have become progressively more complex. This increasing complexity, along with a need for standardization of definitions and tools among researchers, motivated the development of the Iowa State University Tile Assembly Simulator (ISU TAS). ISU TAS is a graphical simulator and tile set editor for designing and building 2-D and 3-D aTAM tile assembly systems and simulating their self-assembly. This paper reviews the features and functionality of ISU TAS and describes how it can be used to further research into the complexities of the aTAM. Software and source code are available at http://www.cs.iastate.edu/~lnsa.


Strict Authentication Watermarking with JPEG Compression (SAW-JPEG) for Medical Images

Abstract: This paper proposes a strict authentication watermarking for medical images. In this scheme, we define region of interest (ROI) by taking the smallest rectangle around an image. The watermark is generated from hashing the area of interest. The embedding region is considered to be outside the region of interest as to preserve the area from distortion as a result from watermarking. The strict authentication watermarking is robust to some degree of JPEG compression (SAW-JPEG). JPEG compression will be reviewed. To embed a watermark in the spatial domain, we have to make sure that the embedded watermark will survive JPEG quantization process. The watermarking scheme, including data embedding, extracting and verifying procedure were presented. Experimental results showed that such a scheme could embed and extract the watermark at a high compression rate. The watermark is robust to a high compression rate up to 90.6%. The JPEG image quality threshold is 60 for the least significant bit embedding. The image quality threshold is increased to 61 for 2nd and 3rd LSB manipulations.


Proceedings Third International Workshop on Classical Logic and Computation

Abstract: The fact that classical mathematical proofs of simply existential statements can be read as programs was established by Goedel and Kreisel half a century ago. But the possibility of extracting useful computational content from classical proofs was taken seriously only from the 1990s on when it was discovered that proof interpretations based on Goedel's and Kreisel's ideas can provide new nontrivial algorithms and numerical results, and the Curry-Howard correspondence can be extended to classical logic via programming concepts such as continuations and control operators. The workshop series "Classical Logic and Computation" aims to support a fruitful exchange of ideas between the various lines of research on computational aspects of classical logic. This volume contains the abstracts of the invited lectures and the accepted contributed papers of the third CL&C workshop which was held jointly with the workshop "Program Extraction and Constructive Mathematics" at the University of Brno in August 21-22, 2010, as a satellite of CSL and MFCS. The workshops were held in honour of Helmut Schwichtenberg who became "professor emeritus" in September 2010. The topics of the papers include the foundations, optimizations and applications of proof interpretations such as Hilbert's epsilon substitution method, Goedel's functional interpretation, learning based realizability and negative translations as well as special calculi and theories capturing computational and complexity-theoretic aspects of classical logic such as the lambda-mu-calculus, applicative theories, sequent-calculi, resolution and cut-elimination


Competitive and Deterministic Embeddings of Virtual Networks

Abstract: Network virtualization is an important concept to overcome the ossification of today's Internet as it facilitates innovation also in the network core and as it promises a more efficient use of the given resources and infrastructure. Virtual networks (VNets) provide an abstraction of the physical network: multiple VNets may cohabit the same physical network, but can be based on completely different protocol stacks (also beyond IP). One of the main challenges in network virtualization is the efficient admission control and embedding of VNets. The demand for virtual networks (e.g., for a video conference) can be hard to predict, and once the request is accepted, the specification / QoS guarantees must be ensured throughout the VNet's lifetime. This requires an admission control algorithm which only selects high-benefit VNets in times of scarce resources, and an embedding algorithm which realizes the VNet in such a way that the likelihood that future requests can be embedded as well is maximized. This article describes a generic algorithm for the online VNet embedding problem which does not rely on any knowledge of the future VNet requests but whose performance is competitive to an optimal offline algorithm that has complete knowledge of the request sequence in advance: the so-called competitive ratio is, loosely speaking, logarithmic in the sum of the resources. Our algorithm is generic in the sense that it supports multiple traffic models, multiple routing models, and even allows for nonuniform benefits and durations of VNet requests.


Highlights from the SOAP project survey. What Scientists Think about Open Access Publishing

Abstract: The SOAP (Study of Open Access Publishing) project has run a large-scale survey of the attitudes of researchers on, and the experiences with, open access publishing. Around forty thousands answers were collected across disciplines and around the world, showing an overwhelming support for the idea of open access, while highlighting funding and (perceived) quality as the main barriers to publishing in open access journals. This article serves as an introduction to the survey and presents this and other highlights from a preliminary analysis of the survey responses. To allow a maximal re-use of the information collected by this survey, the data are hereby released under a CC0 waiver, so to allow libraries, publishers, funding agencies and academics to further analyse risks and opportunities, drivers and barriers, in the transition to open access publishing.


Parsimonious Flooding in Geometric Random-Walks

Abstract: We study the information spreading yielded by the \emph{(Parsimonious) $1$-Flooding Protocol} in geometric Mobile Ad-Hoc Networks. We consider $n$ agents on a convex plane region of diameter $D$ performing independent random walks with move radius $\rho$. At any time step, every active agent $v$ informs every non-informed agent which is within distance $R$ from $v$ ($R>0$ is the transmission radius). An agent is only active at the time step immediately after the one in which has been informed and, after that, she is removed. At the initial time step, a source agent is informed and we look at the \emph{completion time} of the protocol, i.e., the first time step (if any) in which all agents are informed. This random process is equivalent to the well-known \emph{Susceptible-Infective-Removed ($SIR$}) infection process in Mathematical Epidemiology. No analytical results are available for this random process over any explicit mobility model. The presence of removed agents makes this process much more complex than the (standard) flooding. We prove optimal bounds on the completion time depending on the parameters $n$, $D$, $R$, and $\rho$. The obtained bounds hold with high probability. We remark that our method of analysis provides a clear picture of the dynamic shape of the information spreading (or infection wave) over the time.


A Chronology of Torah Cryptography

Abstract: Regarding some papers and notes submitted to, or presented at, the second congress of the International Torah Codes Society in Jerusalem, Israel, June 2000.


A Panorama on Multiscale Geometric Representations, Intertwining Spatial, Directional and Frequency Selectivity

Abstract: The richness of natural images makes the quest for optimal representations in image processing and computer vision challenging. The latter observation has not prevented the design of image representations, which trade off between efficiency and complexity, while achieving accurate rendering of smooth regions as well as reproducing faithful contours and textures. The most recent ones, proposed in the past decade, share an hybrid heritage highlighting the multiscale and oriented nature of edges and patterns in images. This paper presents a panorama of the aforementioned literature on decompositions in multiscale, multi-orientation bases or dictionaries. They typically exhibit redundancy to improve sparsity in the transformed domain and sometimes its invariance with respect to simple geometric deformations (translation, rotation). Oriented multiscale dictionaries extend traditional wavelet processing and may offer rotation invariance. Highly redundant dictionaries require specific algorithms to simplify the search for an efficient (sparse) representation. We also discuss the extension of multiscale geometric decompositions to non-Euclidean domains such as the sphere or arbitrary meshed surfaces. The etymology of panorama suggests an overview, based on a choice of partially overlapping "pictures". We hope that this paper will contribute to the appreciation and apprehension of a stream of current research directions in image understanding.


Analysing the Control Software of the Compact Muon Solenoid Experiment at the Large Hadron Collider

Abstract: The control software of the CERN Compact Muon Solenoid experiment contains over 30,000 finite state machines. These state machines are organised hierarchically: commands are sent down the hierarchy and state changes are sent upwards. The sheer size of the system makes it virtually impossible to fully understand the details of its behaviour at the macro level. This is fuelled by unclarities that already exist at the micro level. We have solved the latter problem by formally describing the finite state machines in the mCRL2 process algebra. The translation has been implemented using the ASF+SDF meta-environment, and its correctness was assessed by means of simulations and visualisations of individual finite state machines and through formal verification of subsystems of the control software. Based on the formalised semantics of the finite state machines, we have developed dedicated tooling for checking properties that can be verified on finite state machines in isolation.


SmartInt: Using Mined Attribute Dependencies to Integrate Fragmented Web Databases

Abstract: Many web databases can be seen as providing partial and overlapping information about entities in the world. To answer queries effectively, we need to integrate the information about the individual entities that are fragmented over multiple sources. At first blush this is just the inverse of traditional database normalization problem - rather than go from a universal relation to normalized tables, we want to reconstruct the universal relation given the tables (sources). The standard way of reconstructing the entities will involve joining the tables. Unfortunately, because of the autonomous and decentralized way in which the sources are populated, they often do not have Primary Key - Foreign Key relations. While tables may share attributes, naive joins over these shared attributes can result in reconstruction of many spurious entities thus seriously compromising precision. Our system, \smartint\ is aimed at addressing the problem of data integration in such scenarios. Given a query, our system uses the Approximate Functional Dependencies (AFDs) to piece together a tree of relevant tables to answer it. The result tuples produced by our system are able to strike a favorable balance between precision and recall.


Accurate Performance Analysis of Opportunistic Decode-and-Forward Relaying

Abstract: In this paper, we investigate an opportunistic relaying scheme where the selected relay assists the source-destination (direct) communication. In our study, we consider a regenerative opportunistic relaying scheme in which the direct path can be considered unusable, and takes into account the effect of the possible erroneously detected and transmitted data at the best relay. We first derive statistics based on exact probability density function (PDF) of each hop. Then, the PDFs are used to determine accurate closed form expressions for end-to-end bit-error rate (BER) of binary phase-shift keying (BPSK) modulation. Furthermore, we evaluate the asymptotical performance analysis and the diversity order is deduced. Finally, we validate our analysis by showing that performance simulation results coincide with our analytical results over different network architectures.


A practical guide to Message Structures: a modelling technique for information systems analysis and design

Abstract: Despite the increasing maturity of model-driven software development (MDD), some research challenges remain open in the field of information systems (IS). For instance, there is a need to improve modelling techniques so that they cover several development stages in an integrated way, and they facilitate the transition from analysis to design. This paper presents Message Structures, a technique for the specification of communicative interactions between the IS and organisational actors. This technique can be used both in the analysis stage and in the design stage. During analysis, it allows abstracting from the technology that will support the IS, and to complement business process diagramming techniques with the specification of the communicational needs of the organisation. During design, Message Structures serves two purposes: (i) it allows to systematically derive a specification of the IS memory (e.g. a UML class diagram), (ii) and it allows to reason the user interface design using abstract patterns. This technique is part of Communication Analysis, a communication-oriented requirements engineering method, but it can be adopted in order to extend widely-used business process and functional requirements modelling techniques (e.g. BPMN, Use Cases). Moreover, the paper presents two tools that support Message Structures, one uses the Xtext technology, and the other uses the Eclipse Modelling Framework. Industrial experience has shown us that the technique can be adopted and applied in complex projects.


Approximating the Influence of a monotone Boolean function in O(\sqrt{n}) query complexity

Abstract: The {\em Total Influence} ({\em Average Sensitivity) of a discrete function is one of its fundamental measures. We study the problem of approximating the total influence of a monotone Boolean function \ifnum\plusminus=1 $f: \{\pm1\}^n \longrightarrow \{\pm1\}$, \else $f: \bitset^n \to \bitset$, \fi which we denote by $I[f]$. We present a randomized algorithm that approximates the influence of such functions to within a multiplicative factor of $(1\pm \eps)$ by performing $O(\frac{\sqrt{n}\log n}{I[f]} \poly(1/\eps)) $ queries. % \mnote{D: say something about technique?} We also prove a lower bound of % $\Omega(\frac{\sqrt{n/\log n}}{I[f]})$ $\Omega(\frac{\sqrt{n}}{\log n \cdot I[f]})$ on the query complexity of any constant-factor approximation algorithm for this problem (which holds for $I[f] = \Omega(1)$), % and $I[f] = O(\sqrt{n}/\log n)$), hence showing that our algorithm is almost optimal in terms of its dependence on $n$. For general functions we give a lower bound of $\Omega(\frac{n}{I[f]})$, which matches the complexity of a simple sampling algorithm.


RISC and CISC

Abstract: Comparison of RISC & CISC in details, encompassing the addressing modes, evolution, definitions and characteristics. Pre - RISC design is also elaborated. Both the architectures are explained with the help of example. Analysis is made based on performance.


Maintaining Arrays of Contiguous Objects

Abstract: In this paper we consider methods for dynamically storing a set of different objects ("modules") in a physical array. Each module requires one free contiguous subinterval in order to be placed. Items are inserted or removed, resulting in a fragmented layout that makes it harder to insert further modules. It is possible to relocate modules, one at a time, to another free subinterval that is contiguous and does not overlap with the current location of the module. These constraints clearly distinguish our problem from classical memory allocation. We present a number of algorithmic results, including a bound of Theta(n^2) on physical sorting if there is a sufficiently large free space and sum up NP-hardness results for arbitrary initial layouts. For online scenarios in which modules arrive one at a time, we present a method that requires O(1) moves per insertion or deletion and amortized cost O(m_i log M) per insertion or deletion, where m_i is the module's size, M is the size of the largest module and costs for moves are linear in the size of a module.


Connection errors in networks of linear features and the application of geometrical reduction in spatial data algorithms

Abstract: We present a study on connection errors in networks of linear features and methods of error detection. We model networks with special connection specifications as networks with hierarchically connected features and define errors considering the spatial relationships and the functionality of the network elements. A general definition of the problem of the detection of connection errors which takes into account the functionality of the network elements is discussed. Then a series of spatial algorithms that solve different aspects of the problem is presented. We also define and analyze the notion of geometrical reduction as a method of achieving efficient performance. In the last section the undecidability of algorithmic error correction is discussed.


Efficient Algorithms for Searching Optimal Shortened Cyclic Single-Burst-Correcting Codes

Abstract: In a previous work it was shown that the best measure for the efficiency of a single burst-correcting code is obtained using the Gallager bound as opposed to the Reiger bound. In this paper, an efficient algorithm that searches for the best (shortened) cyclic burst-correcting codes is presented. Using this algorithm, extensive tables that either tie existing constructions or improve them are obtained for burst lengths up to b=10.


The Computing of Digital Ecosystems

Abstract: A primary motivation for our research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. Here, we discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems (MASs), Service-Oriented Architectures (SOAs), and distributed evolutionary computing (DEC). The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, considering the self-organised diversity of its evolving agent populations relative to the user request behaviour.


Interactive Learning Based Realizability and 1-Backtracking Games

Abstract: We prove that interactive learning based classical realizability (introduced by Aschieri and Berardi for first order arithmetic) is sound with respect to Coquand game semantics. In particular, any realizer of an implication-and-negation-free arithmetical formula embodies a winning recursive strategy for the 1-Backtracking version of Tarski games. We also give examples of realizer and winning strategy extraction for some classical proofs. We also sketch some ongoing work about how to extend our notion of realizability in order to obtain completeness with respect to Coquand semantics, when it is restricted to 1-Backtracking games.


On Various Negative Translations

Abstract: Several proof translations of classical mathematics into intuitionistic mathematics have been proposed in the literature over the past century. These are normally referred to as negative translations or double-negation translations. Among those, the most commonly cited are translations due to Kolmogorov, Godel, Gentzen, Kuroda and Krivine (in chronological order). In this paper we propose a framework for explaining how these different translations are related to each other. More precisely, we define a notion of a (modular) simplification starting from Kolmogorov translation, which leads to a partial order between different negative translations. In this derived ordering, Kuroda and Krivine are minimal elements. Two new minimal translations are introduced, with Godel and Gentzen translations sitting in between Kolmogorov and one of these new translations.


Superdeduction in Lambda-Bar-Mu-Mu-Tilde

Abstract: Superdeduction is a method specially designed to ease the use of first-order theories in predicate logic. The theory is used to enrich the deduction system with new deduction rules in a systematic, correct and complete way. A proof-term language and a cut-elimination reduction already exist for superdeduction, both based on Christian Urban's work on classical sequent calculus. However the computational content of Christian Urban's calculus is not directly related to the (lambda-calculus based) Curry-Howard correspondence. In contrast the Lambda bar mu mu tilde calculus is a lambda-calculus for classical sequent calculus. This short paper is a first step towards a further exploration of the computational content of superdeduction proofs, for we extend the Lambda bar mu mu tilde calculus in order to obtain a proofterm langage together with a cut-elimination reduction for superdeduction. We also prove strong normalisation for this extension of the Lambda bar mu mu tilde calculus.


An applicative theory for FPH

Abstract: In this paper we introduce an applicative theory which characterizes the polynomial hierarchy of time.


Relating Sequent Calculi for Bi-intuitionistic Propositional Logic

Abstract: Bi-intuitionistic logic is the conservative extension of intuitionistic logic with a connective dual to implication. It is sometimes presented as a symmetric constructive subsystem of classical logic. In this paper, we compare three sequent calculi for bi-intuitionistic propositional logic: (1) a basic standard-style sequent calculus that restricts the premises of implication-right and exclusion-left inferences to be single-conclusion resp. single-assumption and is incomplete without the cut rule, (2) the calculus with nested sequents by Gore et al., where a complete class of cuts is encapsulated into special "unnest" rules and (3) a cut-free labelled sequent calculus derived from the Kripke semantics of the logic. We show that these calculi can be translated into each other and discuss the ineliminable cuts of the standard-style sequent calculus.


Dialectica Interpretation with Marked Counterexamples

Abstract: Goedel's functional "Dialectica" interpretation can be used to extract functional programs from non-constructive proofs in arithmetic by employing two sorts of higher-order witnessing terms: positive realisers and negative counterexamples. In the original interpretation decidability of atoms is required to compute the correct counterexample from a set of candidates. When combined with recursion, this choice needs to be made for every step in the extracted program, however, in some special cases the decision on negative witnesses can be calculated only once. We present a variant of the interpretation in which the time complexity of extracted programs can be improved by marking the chosen witness and thus avoiding recomputation. The achieved effect is similar to using an abortive control operator to interpret computational content of non-constructive principles.


Failure of A Mix Network

Abstract: A mix network by Wikstrom fails in correctness, provable privacy and soundness. Its claimed advantages in security and efficiency are compromised. The analysis in this paper illustrates that although the first two failures may be fixed by modifying the shuffling protocol, the last one is too serious to fix at a tolerable cost. Especially, an attack is proposed to show how easily soundness of the shuffling scheme can be compromised. Moreover, the most surprising discovery in this paper is that it is formally illustrated that in practice it is impossible to fix soundness of the shuffling scheme by Wikstrom.


Resource Bounded Measure

Abstract: A general theory of resource-bounded measurability and measure is developed. Starting from any feasible probability measure $\nu$ on the Cantor space $\C$ and any suitable complexity class $C \subseteq \C$, the theory identifies the subsets of $\C$ that are $\nu$-measurable in $C$ and assigns measures to these sets, thereby endowing $C$ with internal measure-theoretic structure. Classes to which the theory applies include various exponential time and space complexity classes, the class of all decidable languages, and the Cantor space itself, on which the resource-bounded theory is shown to agree with the classical theory. The sets that are $\nu$-measurable in $C$ are shown to form an algebra relative to which $\nu$-measure is well-behaved. This algebra is also shown to be complete and closed under sufficiently uniform infinitary unions and intersections, and $\nu$-measure in $C$ is shown to have the appropriate additivity and monotone convergence properties with respect to such infinitary operations. A generalization of the classical Kolmogorov zero-one law is proven, showing that when $\nu$ is any feasible coin-toss probability measure on $\C$, every set that is $\nu$-measurable in $C$ and (like most complexity classes) invariant under finite alterations must have $\nu$-measure 0 or $\nu$-measure 1 in $C$. The theory is presented here is based on resource-bounded martingale splitting operators, which are type-2 functionals, each of which maps $\N \times {\cal D}_\nu$ into ${\cal D}_\nu \times {\cal D}_\nu$, where ${\cal D}_\nu$ is the set of all $\nu$-martingales. This type-2 aspect of the theory appears to be essential for general $\nu$-measure in complexity classes $C$, but the sets of $\nu$-measure 0 or 1 in C are shown to be characterized by the success conditions for martingales (type-1 functions) that have been used in resource-bounded measure to date.


A Human-Centric Approach to Group-Based Context-Awareness

Abstract: The emerging need for qualitative approaches in context-aware information processing calls for proper modeling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of the current approaches to context-awareness either lack a solid theoretical basis for modeling or ignore important requirements such as modularity, high-order uncertainty management and group-based context-awareness. Therefore, their real-world application and extendability remains limited. In this paper, we present f-Context as a service-based context-awareness framework, based on language-action perspective (LAP) theory for modeling. Then we identify some of the complex, informational parts of context which contain high-order uncertainties due to differences between members of the group in defining them. An agent-based perceptual computer architecture is proposed for implementing f-Context that uses computing with words (CWW) for handling uncertainty. The feasibility of f-Context is analyzed using a realistic scenario involving a group of mobile users. We believe that the proposed approach can open the door to future research on context-awareness by offering a theoretical foundation based on human communication, and a service-based layered architecture which exploits CWW for context-aware, group-based and platform-independent access to information systems.


Ray-Based Reflectance Model for Diffraction

Abstract: We present a novel method of simulating wave effects in graphics using ray--based renderers with a new function: the Wave BSDF (Bidirectional Scattering Distribution Function). Reflections from neighboring surface patches represented by local BSDFs are mutually independent. However, in many surfaces with wavelength-scale microstructures, interference and diffraction requires a joint analysis of reflected wavefronts from neighboring patches. We demonstrate a simple method to compute the BSDF for the entire microstructure, which can be used independently for each patch. This allows us to use traditional ray--based rendering pipelines to synthesize wave effects of light and sound. We exploit the Wigner Distribution Function (WDF) to create transmissive, reflective, and emissive BSDFs for various diffraction phenomena in a physically accurate way. In contrast to previous methods for computing interference, we circumvent the need to explicitly keep track of the phase of the wave by using BSDFs that include positive as well as negative coefficients. We describe and compare the theory in relation to well understood concepts in rendering and demonstrate a straightforward implementation. In conjunction with standard raytracers, such as PBRT, we demonstrate wave effects for a range of scenarios such as multi--bounce diffraction materials, holograms and reflection of high frequency surfaces.


Developing a New Approach for Arabic Morphological Analysis and Generation

Abstract: Arabic morphological analysis is one of the essential stages in Arabic Natural Language Processing. In this paper we present an approach for Arabic morphological analysis. This approach is based on Arabic morphological automaton (AMAUT). The proposed technique uses a morphological database realized using XMODEL language. Arabic morphology represents a special type of morphological systems because it is based on the concept of scheme to represent Arabic words. We use this concept to develop the Arabic morphological automata. The proposed approach has development standardization aspect. It can be exploited by NLP applications such as syntactic and semantic analysis, information retrieval, machine translation and orthographical correction. The proposed approach is compared with Xerox Arabic Analyzer and Smrz Arabic Analyzer.


Compressed String Dictionaries

Abstract: The problem of storing a set of strings --- a string dictionary --- in compact form appears naturally in many cases. While classically it has represented a small part of the whole data to be processed (e.g., for Natural Language processing or for indexing text collections), more recent applications in Web engines, Web mining, RDF graphs, Internet routing, Bioinformatics, and many others, make use of very large string dictionaries, whose size is a significant fraction of the whole data. Thus novel approaches to compress them efficiently are necessary. In this paper we experimentally compare time and space performance of some existing alternatives, as well as new ones we propose. We show that space reductions of up to 20% of the original size of the strings is possible while supporting fast dictionary searches.


Reduce to the Max: A Simple Approach for Massive-Scale Privacy-Preserving Collaborative Network Measurements (Extended Version)

Abstract: Privacy-preserving techniques for distributed computation have been proposed recently as a promising framework in collaborative inter-domain network monitoring. Several different approaches exist to solve such class of problems, e.g., Homomorphic Encryption (HE) and Secure Multiparty Computation (SMC) based on Shamir's Secret Sharing algorithm (SSS). Such techniques are complete from a computation-theoretic perspective: given a set of private inputs, it is possible to perform arbitrary computation tasks without revealing any of the intermediate results. In fact, HE and SSS can operate also on secret inputs and/or provide secret outputs. However, they are computationally expensive and do not scale well in the number of players and/or in the rate of computation tasks. In this paper we advocate the use of "elementary" (as opposite to "complete") Secure Multiparty Computation (E-SMC) procedures for traffic monitoring. E-SMC supports only simple computations with private input and public output, i.e., it can not handle secret input nor secret (intermediate) output. Such a simplification brings a dramatic reduction in complexity and enables massive-scale implementation with acceptable delay and overhead. Notwithstanding its simplicity, we claim that an E-SMC scheme is sufficient to perform a great variety of computation tasks of practical relevance to collaborative network monitoring, including, e.g., anonymous publishing and set operations. This is achieved by combining a E-SMC scheme with data structures like Bloom Filters and bitmap strings.


The complexity of Free-Flood-It on 2xn boards

Abstract: We consider the complexity of problems related to the combinatorial game Free-Flood-It, in which players aim to make a coloured graph monochromatic with the minimum possible number of flooding operations. Our main result is that computing the length of an optimal sequence is fixed parameter tractable (with the number of colours present as a parameter) when restricted to rectangular 2xn boards. We also show that, when the number of colours is unbounded, the problem remains NP-hard on such boards. This resolves a question of Clifford, Jalsenius, Montanaro and Sach (2010).


T2Script Programming Language

Abstract: Event-driven programming is used in many fields of modern Computer Science. In event-driven programming languages user interacts with a program by triggering the events. We propose a new approach that we denote command-event driven programming in which the user interacts with a program by means of events and commands. We describe a new programming language, T2Script, which is based on command-event driven paradigm. T2Script has been already implemented and used in one of industrial products. We describe the rationale, basic concepts and advanced programming techniques of new T2Script language. We evaluate the new language and show what advantages and limitations it has.


How Unique and Traceable are Usernames?

Abstract: Suppose you find the same username on different online services, what is the probability that these usernames refer to the same physical person? This work addresses what appears to be a fairly simple question, which has many implications for anonymity and privacy on the Internet. One possible way of estimating this probability would be to look at the public information associated to the two accounts and try to match them. However, for most services, these information are chosen by the users themselves and are often very heterogeneous, possibly false and difficult to collect. Furthermore, several websites do not disclose any additional public information about users apart from their usernames (e.g., discus- sion forums or Blog comments), nonetheless, they might contain sensitive information about users. This paper explores the possibility of linking users profiles only by looking at their usernames. The intuition is that the probability that two usernames refer to the same physical person strongly depends on the "entropy" of the username string itself. Our experiments, based on crawls of real web services, show that a significant portion of the users' profiles can be linked using their usernames. To the best of our knowledge, this is the first time that usernames are considered as a source of information when profiling users on the Internet.


A 4/3-approximation for TSP on cubic 3-edge-connected graphs

Abstract: We provide a polynomial time 4/3 approximation algorithm for TSP on metrics arising from the metric completion of cubic 3-edge connected graphs.


An Overview of the Security Concerns in Enterprise Cloud Computing

Abstract: Deploying cloud computing in an enterprise infrastructure bring significant security concerns. Successful implementation of cloud computing in an enterprise requires proper planning and understanding of emerging risks, threats, vulnerabilities, and possible countermeasures. We believe enterprise should analyze the company/organization security risks, threats, and available countermeasures before adopting this technology. In this paper, we have discussed security risks and concerns in cloud computing and enlightened steps that an enterprise can take to reduce security risks and protect their resources. We have also explained cloud computing strengths/benefits, weaknesses, and applicable areas in information risk management.


Optimal Pricing in Networks with Externalities

Abstract: We study the optimal pricing strategies of a monopolist selling a divisible good (service) to consumers that are embedded in a social network. A key feature of our model is that consumers experience a (positive) local network effect. In particular, each consumer's usage level depends directly on the usage of her neighbors in the social network structure. Thus, the monopolist's optimal pricing strategy may involve offering discounts to certain agents, who have a central position in the underlying network. First, we consider a setting where the monopolist can offer individualized prices and derive an explicit characterization of the optimal price for each consumer as a function of her network position. In particular, we show that it is optimal for the monopolist to charge each agent a price that is proportional to her Bonacich centrality in the social network. In the second part of the paper, we discuss the optimal strategy of a monopolist that can only choose a single uniform price for the good and derive an algorithm polynomial in the number of agents to compute such a price. Thirdly, we assume that the monopolist can offer the good in two prices, full and discounted, and study the problem of determining which set of consumers should be given the discount. We show that the problem is NP-hard, however we provide an explicit characterization of the set of agents that should be offered the discounted price. Next, we describe an approximation algorithm for finding the optimal set of agents. We show that if the profit is nonnegative under any feasible price allocation, the algorithm guarantees at least 88% of the optimal profit. Finally, we highlight the value of network information by comparing the profits of a monopolist that does not take into account the network effects when choosing her pricing policy to those of a monopolist that uses this information optimally.


Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing

Abstract: Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing information-theoretic exploration strategies for learning GP-based environmental field maps adopt the non-Markovian problem structure and consequently scale poorly with the length of history of observations. Hence, it becomes computationally impractical to use these strategies for in situ, real-time active sampling. To ease this computational burden, this paper presents a Markov-based approach to efficient information-theoretic path planning for active sampling of GP-based fields. We analyze the time complexity of solving the Markov-based path planning problem, and demonstrate analytically that it scales better than that of deriving the non-Markovian strategies with increasing length of planning horizon. For a class of exploration tasks called the transect sampling task, we provide theoretical guarantees on the active sampling performance of our Markov-based policy, from which ideal environmental field conditions and sampling task settings can be established to limit its performance degradation due to violation of the Markov assumption. Empirical evaluation on real-world temperature and plankton density field data shows that our Markov-based policy can generally achieve active sampling performance comparable to that of the widely-used non-Markovian greedy policies under less favorable realistic field conditions and task settings while enjoying significant computational gain over them.


Analysis of Web Logs and Web User in Web Mining

Abstract: Log files contain information about User Name, IP Address, Time Stamp, Access Request, number of Bytes Transferred, Result Status, URL that Referred and User Agent. The log files are maintained by the web servers. By analysing these log files gives a neat idea about the user. This paper gives a detailed discussion about these log files, their formats, their creation, access procedures, their uses, various algorithms used and the additional parameters that can be used in the log files which in turn gives way to an effective mining. It also provides the idea of creating an extended log file and learning the user behaviour.


A correspondence-less approach to matching of deformable shapes

Abstract: Finding a match between partially available deformable shapes is a challenging problem with numerous applications. The problem is usually approached by computing local descriptors on a pair of shapes and then establishing a point-wise correspondence between the two. In this paper, we introduce an alternative correspondence-less approach to matching fragments to an entire shape undergoing a non-rigid deformation. We use diffusion geometric descriptors and optimize over the integration domains on which the integral descriptors of the two parts match. The problem is regularized using the Mumford-Shah functional. We show an efficient discretization based on the Ambrosio-Tortorelli approximation generalized to triangular meshes. Experiments demonstrating the success of the proposed method are presented.


Polarized Montagovian Semantics for the Lambek-Grishin calculus

Abstract: Grishin proposed enriching the Lambek calculus with multiplicative disjunction (par) and coresiduals. Applications to linguistics were discussed by Moortgat, who spoke of the Lambek-Grishin calculus (LG). In this paper, we adapt Girard's polarity-sensitive double negation embedding for classical logic to extract a compositional Montagovian semantics from a display calculus for focused proof search in LG. We seize the opportunity to illustrate our approach alongside an analysis of extraction, providing linguistic motivation for linear distributivity of tensor over par, thus answering a question of Kurtonina&Moortgat. We conclude by comparing our proposal to the continuation semantics of Bernardi&Moortgat, corresponding to call-by- name and call-by-value evaluation strategies.


A New Semantic Web Approach for Constructing, Searching and Modifying Ontology Dynamically

Abstract: Semantic web is the next generation web, which concerns the meaning of web documents It has the immense power to pull out the most relevant information from the web pages, which is also meaningful to any user, using software agents. In today's world, agent communication is not possible if concerned ontology is changed a little. We have pointed out this very problem and developed an Ontology Purification System to help agent communication. In our system you can send queries and view the search results. If it can't meet the criteria then it finds out the mismatched elements. Modification is done within a second and you can see the difference. That's why we emphasis on the word dynamic. When Administrator is updating the system, at the same time that updation is visible to the user.


Co-Designing Multi-Packet Reception, Network Coding, and MAC Using a Simple Predictive Model

Abstract: We design a cross-layer approach to optimize the joint use of multi-packet reception and network coding, in order to relieve congestion. We construct a model for the behavior of the 802.11 MAC and apply it to several key canonical topology components and their extensions to any number of nodes. The results obtained from this model match the available experimental results, which are for routing and opportunistic network coding, with fidelity. Using this model, we show that fairness allocation by the MAC can seriously impact performance; hence, we devise a new MAC that not only substantially improves throughput relative to the current 802.11 MAC, but also provides fairness to flows of information rather than to nodes. We show that the proper combination of network coding, multi-packet reception, and our new MAC protocol achieves super-additive throughput gains of up to 6.3 times that of routing alone with the use of the standard 802.11 MAC. Finally, we extend the model to analyze the asymptotic behavior of our new MAC as the number of nodes increases.


Statistical Compressed Sensing of Gaussian Mixture Models

Abstract: A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is introduced. SCS based on Gaussian models is investigated in depth. For signals that follow a single Gaussian model, with Gaussian or Bernoulli sensing matrices of O(k) measurements, considerably smaller than the O(k log(N/k)) required by conventional CS based on sparse models, where N is the signal dimension, and with an optimal decoder implemented via linear filtering, significantly faster than the pursuit decoders applied in conventional CS, the error of SCS is shown tightly upper bounded by a constant times the best k-term approximation error, with overwhelming probability. The failure probability is also significantly smaller than that of conventional sparsity-oriented CS. Stronger yet simpler results further show that for any sensing matrix, the error of Gaussian SCS is upper bounded by a constant times the best k-term approximation with probability one, and the bound constant can be efficiently calculated. For Gaussian mixture models (GMMs), that assume multiple Gaussian distributions and that each signal follows one of them with an unknown index, a piecewise linear estimator is introduced to decode SCS. The accuracy of model selection, at the heart of the piecewise linear decoder, is analyzed in terms of the properties of the Gaussian distributions and the number of sensing measurements. A maximum a posteriori expectation-maximization algorithm that iteratively estimates the Gaussian models parameters, the signals model selection, and decodes the signals, is presented for GMM-based SCS. In real image sensing applications, GMM-based SCS is shown to lead to improved results compared to conventional CS, at a considerably lower computational cost.


Using Planetlab to Implement Multicast at the Application Level

Abstract: Application-layer multicast implements the multicast functionality at the application layer. The main goal of application-layer multicast is to construct and maintain efficient distribution structures between endhosts. In this paper we focus on the implementation of an application-layer multicast network using PlanetLab. We observe that the total time required to measure network latency over TCP is influenced dramatically by the TCP connection time. We argue that end-host distribution is not only influenced by the quality of network links but also by the time required to make connections between nodes. We provide several solutions to decrease the total end-host distribution time.


Scheduling in a random environment: stability and asymptotic optimality

Abstract: We investigate the scheduling of a common resource between several concurrent users when the feasible transmission rate of each user varies randomly over time. Time is slotted and users arrive and depart upon service completion. This may model for example the flow-level behavior of end-users in a narrowband HDR wireless channel (CDMA 1xEV-DO). As performance criteria we consider the stability of the system and the mean delay experienced by the users. Given the complexity of the problem we investigate the fluid-scaled system, which allows to obtain important results and insights for the original system: (1) We characterize for a large class of scheduling policies the stability conditions and identify a set of maximum stable policies, giving in each time slot preference to users being in their best possible channel condition. We find in particular that many opportunistic scheduling policies like Score-Based, Proportionally Best or Potential Improvement are stable under the maximum stability conditions, whereas the opportunistic scheduler Relative-Best or the cmu-rule are not. (2) We show that choosing the right tie-breaking rule is crucial for the performance (e.g. average delay) as perceived by a user. We prove that a policy is asymptotically optimal if it is maximum stable and the tie-breaking rule gives priority to the user with the highest departure probability. We will refer to such tie-breaking rule as myopic. (3) We derive the growth rates of the number of users in the system in overload settings under various policies, which give additional insights on the performance. (4) We conclude that simple priority-index policies with the myopic tie-breaking rule, are stable and asymptotically optimal. All our findings are validated with extensive numerical experiments.


The VC-Dimension of Queries and Selectivity Estimation Through Sampling

Abstract: We develop a novel method, based on the statistical concept of the Vapnik-Chervonenkis dimension, to evaluate the selectivity (output cardinality) of SQL queries - a crucial step in optimizing the execution of large scale database and data-mining operations. The major theoretical contribution of this work, which is of independent interest, is an explicit bound to the VC-dimension of a range space defined by all possible outcomes of a collection (class) of queries. We prove that the VC-dimension is a function of the maximum number of Boolean operations in the selection predicate and of the maximum number of select and join operations in any individual query in the collection, but it is neither a function of the number of queries in the collection nor of the size (number of tuples) of the database. We leverage on this result and develop a method that, given a class of queries, builds a concise random sample of a database, such that with high probability the execution of any query in the class on the sample provides an accurate estimate for the selectivity of the query on the original large database. The error probability holds simultaneously for the selectivity estimates of all queries in the collection, thus the same sample can be used to evaluate the selectivity of multiple queries, and the sample needs to be refreshed only following major changes in the database. The sample representation computed by our method is typically sufficiently small to be stored in main memory. We present extensive experimental results, validating our theoretical analysis and demonstrating the advantage of our technique when compared to complex selectivity estimation techniques used in PostgreSQL and the Microsoft SQL Server.